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VA Ann Arbor Immunotherapy Stewardship Program
Purpose
To compare vial utilization and spending between fixed and weight-based dosing of pembrolizumab in Veterans. Promote and assess pembrolizumab extended interval dosing.
Background
FDA approved pembrolizumab label change from weight-based to fixed dosing without evidence of fixed-dosing’s superiority. Retrospective studies demonstrate equivalent outcomes for 2 mg/kg every 3 weeks (Q3W), 200 mg Q3W, 4 mg/kg every 6 weeks (Q6W), and 400 mg Q6W.
Methods
In July 2024 VAAAHS (VA Ann Arbor Healthcare System) initiated an immunotherapy stewardship quality improvement program to deprescribe unnecessary pembrolizumab units and promote extended-interval dosing. Specific interventions included order template modification and targeted outreach to key stakeholders.
Data Analysis
All pembrolizumab doses administered at VAAAHS between July 1, 2024 (launch) and March 31, 2025 (data cutoff) were extracted from EHR. Drug utilization, spending, and healthcare contact hours averted were compared to a fixed-dosing counterfactual.
Results
Sixty-three Veterans received 286 total pembrolizumab doses, of which 107 (37.4%) were Q6W and 179 (62.6%) were Q3W. In total, 741 vials were utilized, against expectation of 786 (5.7% reduction), reflecting approximately $182,000 in savings (annualized, $243,000) and 86.5% of the theoretical maximum savings were captured. Q6W’s share of all doses rose from 27.3% in July 2024 to 53.8% in March 2025. Amongst monotherapy, Q6W’s share rose from 60.0% in July 2024 to 86.7% in March 2025. Q6W adoption saved 381 Veteran-healthcare contact hours, not including travel time.
Conclusions
Stewardship efforts reduced unnecessary pembrolizumab utilization and spending while saving Veterans and VAAAHS providers’ time. Continued provider reinforcement, preparation for Oracle/ Cerner implementation, VISN expansion, refinement of pembrolizumab dose-banding, and development of dose bands for other immunotherapies are underway.
Significance
National implementation would improve Veteran convenience and quality of life, enable reductions in drug and resource costs, and enhance clinic throughput.
Purpose
To compare vial utilization and spending between fixed and weight-based dosing of pembrolizumab in Veterans. Promote and assess pembrolizumab extended interval dosing.
Background
FDA approved pembrolizumab label change from weight-based to fixed dosing without evidence of fixed-dosing’s superiority. Retrospective studies demonstrate equivalent outcomes for 2 mg/kg every 3 weeks (Q3W), 200 mg Q3W, 4 mg/kg every 6 weeks (Q6W), and 400 mg Q6W.
Methods
In July 2024 VAAAHS (VA Ann Arbor Healthcare System) initiated an immunotherapy stewardship quality improvement program to deprescribe unnecessary pembrolizumab units and promote extended-interval dosing. Specific interventions included order template modification and targeted outreach to key stakeholders.
Data Analysis
All pembrolizumab doses administered at VAAAHS between July 1, 2024 (launch) and March 31, 2025 (data cutoff) were extracted from EHR. Drug utilization, spending, and healthcare contact hours averted were compared to a fixed-dosing counterfactual.
Results
Sixty-three Veterans received 286 total pembrolizumab doses, of which 107 (37.4%) were Q6W and 179 (62.6%) were Q3W. In total, 741 vials were utilized, against expectation of 786 (5.7% reduction), reflecting approximately $182,000 in savings (annualized, $243,000) and 86.5% of the theoretical maximum savings were captured. Q6W’s share of all doses rose from 27.3% in July 2024 to 53.8% in March 2025. Amongst monotherapy, Q6W’s share rose from 60.0% in July 2024 to 86.7% in March 2025. Q6W adoption saved 381 Veteran-healthcare contact hours, not including travel time.
Conclusions
Stewardship efforts reduced unnecessary pembrolizumab utilization and spending while saving Veterans and VAAAHS providers’ time. Continued provider reinforcement, preparation for Oracle/ Cerner implementation, VISN expansion, refinement of pembrolizumab dose-banding, and development of dose bands for other immunotherapies are underway.
Significance
National implementation would improve Veteran convenience and quality of life, enable reductions in drug and resource costs, and enhance clinic throughput.
Purpose
To compare vial utilization and spending between fixed and weight-based dosing of pembrolizumab in Veterans. Promote and assess pembrolizumab extended interval dosing.
Background
FDA approved pembrolizumab label change from weight-based to fixed dosing without evidence of fixed-dosing’s superiority. Retrospective studies demonstrate equivalent outcomes for 2 mg/kg every 3 weeks (Q3W), 200 mg Q3W, 4 mg/kg every 6 weeks (Q6W), and 400 mg Q6W.
Methods
In July 2024 VAAAHS (VA Ann Arbor Healthcare System) initiated an immunotherapy stewardship quality improvement program to deprescribe unnecessary pembrolizumab units and promote extended-interval dosing. Specific interventions included order template modification and targeted outreach to key stakeholders.
Data Analysis
All pembrolizumab doses administered at VAAAHS between July 1, 2024 (launch) and March 31, 2025 (data cutoff) were extracted from EHR. Drug utilization, spending, and healthcare contact hours averted were compared to a fixed-dosing counterfactual.
Results
Sixty-three Veterans received 286 total pembrolizumab doses, of which 107 (37.4%) were Q6W and 179 (62.6%) were Q3W. In total, 741 vials were utilized, against expectation of 786 (5.7% reduction), reflecting approximately $182,000 in savings (annualized, $243,000) and 86.5% of the theoretical maximum savings were captured. Q6W’s share of all doses rose from 27.3% in July 2024 to 53.8% in March 2025. Amongst monotherapy, Q6W’s share rose from 60.0% in July 2024 to 86.7% in March 2025. Q6W adoption saved 381 Veteran-healthcare contact hours, not including travel time.
Conclusions
Stewardship efforts reduced unnecessary pembrolizumab utilization and spending while saving Veterans and VAAAHS providers’ time. Continued provider reinforcement, preparation for Oracle/ Cerner implementation, VISN expansion, refinement of pembrolizumab dose-banding, and development of dose bands for other immunotherapies are underway.
Significance
National implementation would improve Veteran convenience and quality of life, enable reductions in drug and resource costs, and enhance clinic throughput.
Assessing the Impact of Antidepressants on Cancer Treatment: A Retrospective Analysis of 14 Antineoplastic Agents
Assessing the Impact of Antidepressants on Cancer Treatment: A Retrospective Analysis of 14 Antineoplastic Agents
Cancer patients experience depression at rates > 5 times that of the general population.1-11 Despite an increase in palliative care use, depression rates continued to rise.2-4 Between 5% to 16% of outpatients, 4% to 14% of inpatients, and up to 49% of patients receiving palliative care experience depression.5 This issue also impacts families and caregivers.1 A 2021 meta-analysis found that 23% of active military personnel and 20% of veterans experience depression.11
Antidepressants approved by the US Food and Drug Administration (FDA) target the serotonin, norepinephrine, or dopamine systems and include boxed warnings about an increased risk of suicidal thoughts in adults aged 18 to 24 years.12,13 These medications are categorized into several classes: monoamine oxidase inhibitors (MAOIs), tricyclic antidepressants (TCAs), tetracyclic antidepressants (TeCAs), norepinephrine-dopamine reuptake inhibitors (NDRIs), selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), serotonin receptor modulators (SRMs), serotonin-melatonin receptor antagonists (SMRAs), and N—methyl-D-aspartate receptor antagonists (NMDARAs).14,15 The first FDA-approved antidepressants, iproniazid (an MAOI) and imipramine (a TCA) laid the foundation for the development of newer classes like SSRIs and SNRIs.15-17
Older antidepressants such as MAOIs and TCAs are used less due to their adverse effects (AEs) and drug interactions. MAOIs, such as iproniazid, selegiline, moclobemide, tranylcypromine, isocarboxazid, and phenelzine, have numerous AEs and drug interactions, making them unsuitable for first- or second-line treatment of depression.14,18-21 TCAs such as doxepin, amitriptyline, nortriptyline, imipramine, desipramine, clomipramine, trimipramine, protriptyline, maprotiline, and amoxapine have a narrow therapeutic index requiring careful monitoring for signs of toxicity such as QRS widening, tremors, or confusion. Despite the issues, TCAs are generally classified as second-line agents for major depressive disorder (MDD). TCAs have off-label uses for migraine prophylaxis, treatment of obsessive-compulsive disorder (OCD), insomnia, and chronic pain management first-line.14,22-29
Newer antidepressants, including TeCAs and NDRIs, are typically more effective, but also come with safety concerns. TeCAs like mirtazapine interact with several medications, including MAOIs, serotonin-increasing drugs, alcohol, cannabidiol, and marijuana. Mirtazapine is FDA-approved for the treatment of moderate to severe depression in adults. It is also used off-label to treat insomnia, panic disorder, posttraumatic stress disorder (PTSD), generalized anxiety disorder (GAD), social anxiety disorder (SAD), headaches, and migraines. Compared to other antidepressants, mirtazapine is effective for all stages of depression and addresses a broad range of related symptoms.14,30-34 NDRIs, such as bupropion, also interact with various medications, including MAOIs, other antidepressants, stimulants, and alcohol. Bupropion is FDA-approved for smoking cessation and to treat depression and SAD. It is also used off-label for depression- related bipolar disorder or sexual dysfunction, attention-deficit/hyperactivity disorder (ADHD), and obesity.14,35-42
SSRIs, SNRIs, and SRMs should be used with caution. SSRIs such as sertraline, citalopram, escitalopram, fluoxetine, paroxetine, and fluvoxamine are first-line treatments for depression and various psychiatric disorders due to their safety and efficacy. Common AEs of SSRIs include sexual dysfunction, sleep disturbances, weight changes, and gastrointestinal (GI) issues. SSRIs can prolong the QT interval, posing a risk of life-threatening arrhythmia, and may interact with other medications, necessitating treatment adjustments. The FDA approved SSRIs for MDD, GAD, bulimia nervosa, bipolar depression, OCD, panic disorder, premenstrual dysphoric disorder, treatment-resistant depression, PTSD, and SAD. Off-label uses include binge eating disorder, body dysmorphic disorder, fibromyalgia, premature ejaculation, paraphilias, autism, Raynaud phenomenon, and vasomotor symptoms associated with menopause. Among SSRIs, sertraline and escitalopram are noted for their effectiveness and tolerability.14,43-53
SNRIs, including duloxetine, venlafaxine, desvenlafaxine, milnacipran, and levomilnacipran, may increase bleeding risk, especially when taken with blood thinners. They can also elevate blood pressure, which may worsen if combined with stimulants. SNRIs may interact with other medications that affect serotonin levels, increasing the risk of serotonin syndrome when taken with triptans, pain medications, or other antidepressants.14 Desvenlafaxine has been approved by the FDA (but not by the European Medicines Agency).54-56 Duloxetine is FDA-approved for the treatment of depression, neuropathic pain, anxiety disorders, fibromyalgia, and musculoskeletal disorders. It is used off-label to treat chemotherapy-induced peripheral neuropathy and stress urinary incontinence.57-61 Venlafaxine is FDA-approved for depression, SAD, and panic disorder, and is prescribed off-label to treat ADHD, neuropathy, fibromyalgia, cataplexy, and PTSD, either alone or in combination with other medications.62,63 Milnacipran is not approved for MDD; levomilnacipran received approval in 2013.64
SRMs such as trazodone, nefazodone, vilazodone, and vortioxetine also function as serotonin reuptake inhibitors.14,15 Trazodone is FDA-approved for MDD. It has been used off-label to treat anxiety, Alzheimer disease, substance misuse, bulimia nervosa, insomnia, fibromyalgia, and PTSD when first-line SSRIs are ineffective. A notable AE of trazodone is orthostatic hypotension, which can lead to dizziness and increase the risk of falls, especially in geriatric patients.65-70 Nefazodone was discontinued in Europe in 2003 due to rare cases of liver toxicity but remains available in the US.71-74 Vilazodone and vortioxetine are FDA-approved.
The latest classes of antidepressants include SMRAs and NMDARAs.14 Agomelatine, an SMRA, was approved in Europe in 2009 but rejected by the FDA in 2011 due to liver toxicity.75 NMDARAs like esketamine and a combination of dextromethorphan and bupropion received FDA approval in 2019 and 2022, respectively.76,77
This retrospective study analyzes noncancer drugs used during systemic chemotherapy based on a dataset of 14 antineoplastic agents. It sought to identify the most dispensed noncancer drug groups, discuss findings, compare patients with and without antidepressant prescriptions, and examine trends in antidepressant use from 2002 to 2023. This analysis expands on prior research.78-81
Methods
The Walter Reed National Military Medical Center Institutional Review Board approved the study protocol and ensured compliance with the Health Insurance Portability and Accountability Act as an exempt protocol. The Joint Pathology Center (JPC) of the US Department of Defense (DoD) Cancer Registry Program and Military Health System (MHS) data experts from the Comprehensive Ambulatory/Professional Encounter Record (CAPER) and Pharmacy Data Transaction Service (PDTS) provided data for the analysis.
Data Sources
The JPC DoD Cancer Registry Program contains data from 1998 to 2024. CAPER and PDTS are part of the MHS Data Repository/Management Analysis and Reporting Tool database. Each observation in CAPER represents an ambulatory encounter at a military treatment facility (MTF). CAPER records are available from 2003 to 2024. PDTS records are available from 2002 to 2004. Each observation in PDTS represents a prescription filled for an MHS beneficiary, excluding those filled at international civilian pharmacies and inpatient pharmacy prescriptions.
This cross-sectional analysis requested data extraction for specific cancer drugs from the DoD Cancer Registry, focusing on treatment details, diagnosis dates, patient demographics, and physicians’ comments on AEs. After identifying patients, CAPER was used to identify additional health conditions. PDTS was used to compile a list of prescription medications filled during systemic cancer treatment or < 2 years postdiagnosis.
The 2016 Surveillance, Epidemiology, and End Results Program Coding and Staging Manual and International Classification of Diseases for Oncology, 3rd edition, 1st revision, were used to decode disease and cancer types.82,83 Data sorting and analysis were performed using Microsoft Excel. The percentage for the total was calculated by using the number of patients or data available within the subgroup divided by the total number of patients or data variables. To compare the mean number of dispensed antidepressants to those without antidepressants, a 2-tailed, 2-sample z test was used to calculate the P value and determine statistical significance (P < .05) using socscistatistics.com.
Data were extracted 3 times between 2021 and 2023. The initial 2021 protocol focused on erlotinib and gefitinib. A modified protocol in 2022 added paclitaxel, cisplatin, docetaxel, pemetrexed, and crizotinib; further modification in 2023 included 8 new antineoplastic agents and 2 anticoagulants. Sotorasib has not been prescribed in the MHS, and JPC lacks records for noncancer drugs. The 2023 dataset comprised 2210 patients with cancer treated with 14 antineoplastic agents; 2104 had documented diagnoses and 2113 had recorded prescriptions. Data for erlotinib, gefitinib, and paclitaxel have been published previously.78,79
Results
Of 2113 patients with recorded prescriptions, 1297 patients (61.4%) received 109 cancer drugs, including 96 antineoplastics, 7 disease-modifying antirheumatic agents, 4 biologic response modifiers, and 2 calcitonin gene-related peptides. Fourteen antineoplastic agents had complete data from JPC, while others were noted for combination therapies or treatment switches from the PDTS (Table 1). Seventy-six cancer drugs were prescribed with antidepressants in 489 patients (eAppendix).

The JPC provided 2242 entries for 2210 patients, ranging in age from 2 months to 88 years (mean, 56 years), documenting treatment from September 1988 to January 2023. Thirty-two patients had duplicate entries due to multiple cancer locations or occurrences. Of the 2242 patients, 1541 (68.7%) were aged > 50 years, 975 patients (43.5%) had cancers that were stage III or IV, and 1267 (56.5%) had cancers that were stage 0, I, II, or not applicable/unknown. There were 51 different types of cancer: breast, lung, testicular, endometrial, and ovarian were most common (n ≥ 100 patients). Forty-two cancer types were documented among 750 patients prescribed antidepressants (Table 2).

The CAPER database recorded 8882 unique diagnoses for 2104 patients, while PDTS noted 1089 unique prescriptions within 273 therapeutic codes for 2113 patients. Nine therapeutic codes (opiate agonists, adrenals, cathartics-laxatives, nonsteroidal anti-inflammatory agents, antihistamines for GI conditions, 5-HT3 receptor antagonists, analgesics and antipyretic miscellanea, antineoplastic agents, and proton-pump inhibitors) and 8 drugs (dexamethasone, prochlorperazine, ondansetron, docusate, acetaminophen, ibuprofen, oxycodone, and polyethylene glycol 3350) were associated with > 1000 patients (≥ 50%). Patients had between 1 and 275 unique health conditions and filled 1 to 108 prescriptions. The mean (SD) number of diagnoses and prescriptions was 50 (28) and 29 (12), respectively. Of the 273 therapeutic codes, 30 groups were analyzed, with others categorized into miscellaneous groups such as lotions, vaccines, and devices. Significant differences in mean number of prescriptions were found for patients taking antidepressants compared to those not (P < .05), except for anticonvulsants and antipsychotics (P = .12 and .09, respectively) (Table 3).

Antidepressants
Of the 2113 patients with recorded prescriptions, 750 (35.5%) were dispensed 17 different antidepressants. Among these 17 antidepressants, 183 (8.7%) patients received duloxetine, 158 (7.5%) received venlafaxine, 118 (5.6%) received trazodone, and 107 (5.1%) received sertraline (Figure 1, Table 4). Of the 750 patients, 509 (67.9%) received 1 antidepressant, 168 (22.4%) received 2, 60 (8.0%) received 3, and 13 (1.7%) received > 3. Combinations varied, but only duloxetine and trazodone were prescribed to > 10 patients.



Antidepressants were prescribed annually at an overall mean (SD) rate of 23% (5%) from 2003 to 2022 (Figure 2). Patients on antidepressants during systemic therapy had a greater number of diagnosed medical conditions and received more prescription medications compared to those not taking antidepressants (P < .001) (Figure 3). The 745 patients taking antidepressants in CAPER data had between 1 and 275 diagnosed medical issues, with a mean (SD) of 55 (31) vs a range of 1 to 209 and a mean (SD) of 46 (26) for the 1359 patients not taking antidepressants. The 750 patients on antidepressants in PDTS data had between 8 and 108 prescriptions dispensed, with a mean (SD) of 32 (12), vs a range of 1 to 65 prescriptions and a mean (SD) of 29 (12) for 1363 patients not taking antidepressants.


Discussion
The JPC DoD Cancer Registry includes information on cancer types, stages, treatment regimens, and physicians’ notes, while noncancer drugs are sourced from the PDTS database. The pharmacy uses a different documentation system, leading to varied classifications.
Database reliance has its drawbacks. For example, megestrol is coded as a cancer drug, although it’s primarily used for endometrial or gynecologic cancers. Many drugs have multiple therapeutic codes assigned to them, including 10 antineoplastic agents: diclofenac, Bacillus Calmette-Guérin (BCG), megestrol acetate, tamoxifen, anastrozole, letrozole, leuprolide, goserelin, degarelix, and fluorouracil. Diclofenac, BCG, and mitomycin have been repurposed for cancer treatment.84-87 From 2003 to 2023, diclofenac was prescribed to 350 patients for mild-to-moderate pain, with only 2 patients receiving it for cancer in 2018. FDA-approved for bladder cancer in 1990, BCG was prescribed for cancer treatment for 1 patient in 2021 after being used for vaccines between 2003 and 2018. Tamoxifen, used for hormone receptor-positive breast cancer from 2004 to 2017 with 53 patients, switched to estrogen agonist-antagonists from 2017 to 2023 with 123 patients. Only a few of the 168 patients were prescribed tamoxifen using both codes.88-91 Anastrozole and letrozole were coded as antiestrogens for 7 and 18 patients, respectively, while leuprolide and goserelin were coded as gonadotropins for 59 and 18 patients. Degarelix was coded as antigonadotropins, fluorouracil as skin and mucous membrane agents miscellaneous, and megestrol acetate as progestins for 7, 6, and 3 patients, respectively. Duloxetine was given to 186 patients, primarily for depression from 2005 to 2023, with 7 patients treated for fibromyalgia from 2022 to 2023.
Antidepressants Observed
Tables 1 and 5 provide insight into the FDA approval of 14 antineoplastics and antidepressants and their CYP metabolic pathways.92-122 In Table 4, the most prescribed antidepressant classes are SNRIs, SRMs, SSRIs, TeCAs, NDRIs, and TCAs. This trend highlights a preference for newer medications with weak CYP inhibition. A total of 349 patients were prescribed SSRIs, 343 SNRIs, 119 SRMs, 109 TCAs, 83 TeCAs, and 79 NDRIs. MAOIs, SMRAs, and NMDARAs were not observed in this dataset. While there are instances of dextromethorphan-bupropion and sertraline-escitalopram being dispensed together, it remains unclear whether these were NMDARA combinations.
Among the 14 specific antineoplastic agents, 10 are metabolized by CYP isoenzymes, primarily CYP3A4. Duloxetine neither inhibits nor is metabolized by CYP3A4, a reason it is often recommended, following venlafaxine.
Both duloxetine and venlafaxine are used off-label for chemotherapy-induced peripheral neuropathy related to paclitaxel and docetaxel. According to the CYP metabolized pathway, duloxetine tends to have more favorable DDIs than venlafaxine. In PDTS data, 371 patients were treated with paclitaxel and 180 with docetaxel, with respective antidepressant prescriptions of 156 and 70. Of the 156 patients dispensed paclitaxel, 62 (40%) were dispensed with duloxetine compared to 43 (28%) with venlafaxine. Of the 70 patients dispensed docetaxel, 23 (33%) received duloxetine vs 24 (34%) with venlafaxine.
Of 85 patients prescribed duloxetine, 75 received it with either paclitaxel or docetaxel (5 received both). Five patients had documented AEs (1 neuropathy related). Of 67 patients prescribed venlafaxine, 66 received it with either paclitaxel or docetaxel. Two patients had documented AEs (1 was neuropathy related, the same patient who received duloxetine). Of the 687 patients treated with paclitaxel and 337 with docetaxel in all databases, 4 experienced neuropathic AEs from both medications.79
Antidepressants can increase the risk of bleeding, especially when combined with blood thinners, and may elevate blood pressure, particularly alongside stimulants. Of the 554 patients prescribed 9 different anticoagulants, enoxaparin, apixaban, and rivaroxaban were the most common (each > 100 patients). Among these, 201 patients (36%) received both anticoagulants and antidepressants: duloxetine for 64 patients, venlafaxine for 30, trazodone for 35, and sertraline for 26. There were no data available to assess bleeding rates related to the evaluation of DDIs between these medication classes.
Antidepressants can be prescribed for erectile dysfunction. Of the 148 patients prescribed an antidepressant for erectile dysfunction, duloxetine, trazodone, and mirtazapine were the most common. Antidepressant preferences varied by cancer type. Duloxetine was the only antidepressant used for all types of cancer. Venlafaxine, duloxetine, trazodone, sertraline, and escitalopram were the most prescribed antidepressants for breast cancer, while duloxetine, mirtazapine, citalopram, sertraline, and trazodone were the most prescribed for lung cancer. Sertraline, duloxetine, trazodone, amitriptyline, and escitalopram were most common for testicular cancer. Duloxetine, venlafaxine, trazodone, amitriptyline, and sertraline were the most prescribed for endometrial cancer, while duloxetine, venlafaxine, amitriptyline, citalopram, and sertraline were most prescribed for ovarian cancer.
The broadness of International Statistical Classification of Diseases, Tenth Revision codes made it challenging to identify nondepression diagnoses in the analyzed population. However, if all antidepressants were prescribed to treat depression, service members with cancer exhibited a higher depression rate (35%) than the general population (25%). Of 2104 patients, 191 (9.1%) had mood disorders, and 706 (33.6%) had mental disorders: 346 (49.0%) had 1 diagnosis, and 360 (51.0%) had multiple diagnoses. The percentage of diagnoses varied yearly, with notable drops in 2003, 2007, 2011, 2014, and 2018, and peaks in 2006, 2008, 2013, 2017, and 2022. This fluctuation was influenced by events like the establishment of PDTS in 2002, the 2008 economic recession, a hospital relocation in 2011, the 2014 Ebola outbreak, and the COVID-19 pandemic. Although the number of patients receiving antidepressants increased from 2019 to 2022, the overall percentage of patients receiving them did not significantly change from 2003 to 2022, aligning with previous research.5,125
Many medications have potential uses beyond what is detailed in the prescribing information. Antidepressants can relieve pain, while pain medications may help with depression. Opioids were once thought to effectively treat depression, but this perspective has changed with a greater understanding of their risks, including misuse.126-131 Pain is a severe and often unbearable AE of cancer. Of 2113 patients, 92% received opioids; 34% received both opioids and antidepressants; 2% received only antidepressants; and 7% received neither. This study didn’t clarify whether those on opioids alone recognized their depression or if those on both were aware of their dependence. While SSRIs are generally not addictive, they can lead to physical dependence, and any medication can be abused if not managed properly.132-134
Conclusions
This retrospective study analyzes data from antineoplastic agents used in systemic cancer treatment between 1988 and 2023, with a particular focus on the use of antidepressants. Data on antidepressant prescriptions are incomplete and specific to these agents, which means the findings cannot be generalized to all antidepressants. Hence, the results indicate that patients taking antidepressants had more diagnosed health issues and received more medications compared to patients who were not on these drugs.
This study underscores the need for further research into the effects of antidepressants on cancer treatment, utilizing all data from the DoD Cancer Registry. Future research should explore DDIs between antidepressants and other cancer and noncancer medications, as this study did not assess AE documentation, unlike in studies involving erlotinib, gefitinib, and paclitaxel.78,79 Further investigation is needed to evaluate the impact of discontinuing antidepressant use during cancer treatment. This comprehensive overview provides insights for clinicians to help them make informed decisions regarding the prescription of antidepressants in the context of cancer treatment.
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Cancer patients experience depression at rates > 5 times that of the general population.1-11 Despite an increase in palliative care use, depression rates continued to rise.2-4 Between 5% to 16% of outpatients, 4% to 14% of inpatients, and up to 49% of patients receiving palliative care experience depression.5 This issue also impacts families and caregivers.1 A 2021 meta-analysis found that 23% of active military personnel and 20% of veterans experience depression.11
Antidepressants approved by the US Food and Drug Administration (FDA) target the serotonin, norepinephrine, or dopamine systems and include boxed warnings about an increased risk of suicidal thoughts in adults aged 18 to 24 years.12,13 These medications are categorized into several classes: monoamine oxidase inhibitors (MAOIs), tricyclic antidepressants (TCAs), tetracyclic antidepressants (TeCAs), norepinephrine-dopamine reuptake inhibitors (NDRIs), selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), serotonin receptor modulators (SRMs), serotonin-melatonin receptor antagonists (SMRAs), and N—methyl-D-aspartate receptor antagonists (NMDARAs).14,15 The first FDA-approved antidepressants, iproniazid (an MAOI) and imipramine (a TCA) laid the foundation for the development of newer classes like SSRIs and SNRIs.15-17
Older antidepressants such as MAOIs and TCAs are used less due to their adverse effects (AEs) and drug interactions. MAOIs, such as iproniazid, selegiline, moclobemide, tranylcypromine, isocarboxazid, and phenelzine, have numerous AEs and drug interactions, making them unsuitable for first- or second-line treatment of depression.14,18-21 TCAs such as doxepin, amitriptyline, nortriptyline, imipramine, desipramine, clomipramine, trimipramine, protriptyline, maprotiline, and amoxapine have a narrow therapeutic index requiring careful monitoring for signs of toxicity such as QRS widening, tremors, or confusion. Despite the issues, TCAs are generally classified as second-line agents for major depressive disorder (MDD). TCAs have off-label uses for migraine prophylaxis, treatment of obsessive-compulsive disorder (OCD), insomnia, and chronic pain management first-line.14,22-29
Newer antidepressants, including TeCAs and NDRIs, are typically more effective, but also come with safety concerns. TeCAs like mirtazapine interact with several medications, including MAOIs, serotonin-increasing drugs, alcohol, cannabidiol, and marijuana. Mirtazapine is FDA-approved for the treatment of moderate to severe depression in adults. It is also used off-label to treat insomnia, panic disorder, posttraumatic stress disorder (PTSD), generalized anxiety disorder (GAD), social anxiety disorder (SAD), headaches, and migraines. Compared to other antidepressants, mirtazapine is effective for all stages of depression and addresses a broad range of related symptoms.14,30-34 NDRIs, such as bupropion, also interact with various medications, including MAOIs, other antidepressants, stimulants, and alcohol. Bupropion is FDA-approved for smoking cessation and to treat depression and SAD. It is also used off-label for depression- related bipolar disorder or sexual dysfunction, attention-deficit/hyperactivity disorder (ADHD), and obesity.14,35-42
SSRIs, SNRIs, and SRMs should be used with caution. SSRIs such as sertraline, citalopram, escitalopram, fluoxetine, paroxetine, and fluvoxamine are first-line treatments for depression and various psychiatric disorders due to their safety and efficacy. Common AEs of SSRIs include sexual dysfunction, sleep disturbances, weight changes, and gastrointestinal (GI) issues. SSRIs can prolong the QT interval, posing a risk of life-threatening arrhythmia, and may interact with other medications, necessitating treatment adjustments. The FDA approved SSRIs for MDD, GAD, bulimia nervosa, bipolar depression, OCD, panic disorder, premenstrual dysphoric disorder, treatment-resistant depression, PTSD, and SAD. Off-label uses include binge eating disorder, body dysmorphic disorder, fibromyalgia, premature ejaculation, paraphilias, autism, Raynaud phenomenon, and vasomotor symptoms associated with menopause. Among SSRIs, sertraline and escitalopram are noted for their effectiveness and tolerability.14,43-53
SNRIs, including duloxetine, venlafaxine, desvenlafaxine, milnacipran, and levomilnacipran, may increase bleeding risk, especially when taken with blood thinners. They can also elevate blood pressure, which may worsen if combined with stimulants. SNRIs may interact with other medications that affect serotonin levels, increasing the risk of serotonin syndrome when taken with triptans, pain medications, or other antidepressants.14 Desvenlafaxine has been approved by the FDA (but not by the European Medicines Agency).54-56 Duloxetine is FDA-approved for the treatment of depression, neuropathic pain, anxiety disorders, fibromyalgia, and musculoskeletal disorders. It is used off-label to treat chemotherapy-induced peripheral neuropathy and stress urinary incontinence.57-61 Venlafaxine is FDA-approved for depression, SAD, and panic disorder, and is prescribed off-label to treat ADHD, neuropathy, fibromyalgia, cataplexy, and PTSD, either alone or in combination with other medications.62,63 Milnacipran is not approved for MDD; levomilnacipran received approval in 2013.64
SRMs such as trazodone, nefazodone, vilazodone, and vortioxetine also function as serotonin reuptake inhibitors.14,15 Trazodone is FDA-approved for MDD. It has been used off-label to treat anxiety, Alzheimer disease, substance misuse, bulimia nervosa, insomnia, fibromyalgia, and PTSD when first-line SSRIs are ineffective. A notable AE of trazodone is orthostatic hypotension, which can lead to dizziness and increase the risk of falls, especially in geriatric patients.65-70 Nefazodone was discontinued in Europe in 2003 due to rare cases of liver toxicity but remains available in the US.71-74 Vilazodone and vortioxetine are FDA-approved.
The latest classes of antidepressants include SMRAs and NMDARAs.14 Agomelatine, an SMRA, was approved in Europe in 2009 but rejected by the FDA in 2011 due to liver toxicity.75 NMDARAs like esketamine and a combination of dextromethorphan and bupropion received FDA approval in 2019 and 2022, respectively.76,77
This retrospective study analyzes noncancer drugs used during systemic chemotherapy based on a dataset of 14 antineoplastic agents. It sought to identify the most dispensed noncancer drug groups, discuss findings, compare patients with and without antidepressant prescriptions, and examine trends in antidepressant use from 2002 to 2023. This analysis expands on prior research.78-81
Methods
The Walter Reed National Military Medical Center Institutional Review Board approved the study protocol and ensured compliance with the Health Insurance Portability and Accountability Act as an exempt protocol. The Joint Pathology Center (JPC) of the US Department of Defense (DoD) Cancer Registry Program and Military Health System (MHS) data experts from the Comprehensive Ambulatory/Professional Encounter Record (CAPER) and Pharmacy Data Transaction Service (PDTS) provided data for the analysis.
Data Sources
The JPC DoD Cancer Registry Program contains data from 1998 to 2024. CAPER and PDTS are part of the MHS Data Repository/Management Analysis and Reporting Tool database. Each observation in CAPER represents an ambulatory encounter at a military treatment facility (MTF). CAPER records are available from 2003 to 2024. PDTS records are available from 2002 to 2004. Each observation in PDTS represents a prescription filled for an MHS beneficiary, excluding those filled at international civilian pharmacies and inpatient pharmacy prescriptions.
This cross-sectional analysis requested data extraction for specific cancer drugs from the DoD Cancer Registry, focusing on treatment details, diagnosis dates, patient demographics, and physicians’ comments on AEs. After identifying patients, CAPER was used to identify additional health conditions. PDTS was used to compile a list of prescription medications filled during systemic cancer treatment or < 2 years postdiagnosis.
The 2016 Surveillance, Epidemiology, and End Results Program Coding and Staging Manual and International Classification of Diseases for Oncology, 3rd edition, 1st revision, were used to decode disease and cancer types.82,83 Data sorting and analysis were performed using Microsoft Excel. The percentage for the total was calculated by using the number of patients or data available within the subgroup divided by the total number of patients or data variables. To compare the mean number of dispensed antidepressants to those without antidepressants, a 2-tailed, 2-sample z test was used to calculate the P value and determine statistical significance (P < .05) using socscistatistics.com.
Data were extracted 3 times between 2021 and 2023. The initial 2021 protocol focused on erlotinib and gefitinib. A modified protocol in 2022 added paclitaxel, cisplatin, docetaxel, pemetrexed, and crizotinib; further modification in 2023 included 8 new antineoplastic agents and 2 anticoagulants. Sotorasib has not been prescribed in the MHS, and JPC lacks records for noncancer drugs. The 2023 dataset comprised 2210 patients with cancer treated with 14 antineoplastic agents; 2104 had documented diagnoses and 2113 had recorded prescriptions. Data for erlotinib, gefitinib, and paclitaxel have been published previously.78,79
Results
Of 2113 patients with recorded prescriptions, 1297 patients (61.4%) received 109 cancer drugs, including 96 antineoplastics, 7 disease-modifying antirheumatic agents, 4 biologic response modifiers, and 2 calcitonin gene-related peptides. Fourteen antineoplastic agents had complete data from JPC, while others were noted for combination therapies or treatment switches from the PDTS (Table 1). Seventy-six cancer drugs were prescribed with antidepressants in 489 patients (eAppendix).

The JPC provided 2242 entries for 2210 patients, ranging in age from 2 months to 88 years (mean, 56 years), documenting treatment from September 1988 to January 2023. Thirty-two patients had duplicate entries due to multiple cancer locations or occurrences. Of the 2242 patients, 1541 (68.7%) were aged > 50 years, 975 patients (43.5%) had cancers that were stage III or IV, and 1267 (56.5%) had cancers that were stage 0, I, II, or not applicable/unknown. There were 51 different types of cancer: breast, lung, testicular, endometrial, and ovarian were most common (n ≥ 100 patients). Forty-two cancer types were documented among 750 patients prescribed antidepressants (Table 2).

The CAPER database recorded 8882 unique diagnoses for 2104 patients, while PDTS noted 1089 unique prescriptions within 273 therapeutic codes for 2113 patients. Nine therapeutic codes (opiate agonists, adrenals, cathartics-laxatives, nonsteroidal anti-inflammatory agents, antihistamines for GI conditions, 5-HT3 receptor antagonists, analgesics and antipyretic miscellanea, antineoplastic agents, and proton-pump inhibitors) and 8 drugs (dexamethasone, prochlorperazine, ondansetron, docusate, acetaminophen, ibuprofen, oxycodone, and polyethylene glycol 3350) were associated with > 1000 patients (≥ 50%). Patients had between 1 and 275 unique health conditions and filled 1 to 108 prescriptions. The mean (SD) number of diagnoses and prescriptions was 50 (28) and 29 (12), respectively. Of the 273 therapeutic codes, 30 groups were analyzed, with others categorized into miscellaneous groups such as lotions, vaccines, and devices. Significant differences in mean number of prescriptions were found for patients taking antidepressants compared to those not (P < .05), except for anticonvulsants and antipsychotics (P = .12 and .09, respectively) (Table 3).

Antidepressants
Of the 2113 patients with recorded prescriptions, 750 (35.5%) were dispensed 17 different antidepressants. Among these 17 antidepressants, 183 (8.7%) patients received duloxetine, 158 (7.5%) received venlafaxine, 118 (5.6%) received trazodone, and 107 (5.1%) received sertraline (Figure 1, Table 4). Of the 750 patients, 509 (67.9%) received 1 antidepressant, 168 (22.4%) received 2, 60 (8.0%) received 3, and 13 (1.7%) received > 3. Combinations varied, but only duloxetine and trazodone were prescribed to > 10 patients.



Antidepressants were prescribed annually at an overall mean (SD) rate of 23% (5%) from 2003 to 2022 (Figure 2). Patients on antidepressants during systemic therapy had a greater number of diagnosed medical conditions and received more prescription medications compared to those not taking antidepressants (P < .001) (Figure 3). The 745 patients taking antidepressants in CAPER data had between 1 and 275 diagnosed medical issues, with a mean (SD) of 55 (31) vs a range of 1 to 209 and a mean (SD) of 46 (26) for the 1359 patients not taking antidepressants. The 750 patients on antidepressants in PDTS data had between 8 and 108 prescriptions dispensed, with a mean (SD) of 32 (12), vs a range of 1 to 65 prescriptions and a mean (SD) of 29 (12) for 1363 patients not taking antidepressants.


Discussion
The JPC DoD Cancer Registry includes information on cancer types, stages, treatment regimens, and physicians’ notes, while noncancer drugs are sourced from the PDTS database. The pharmacy uses a different documentation system, leading to varied classifications.
Database reliance has its drawbacks. For example, megestrol is coded as a cancer drug, although it’s primarily used for endometrial or gynecologic cancers. Many drugs have multiple therapeutic codes assigned to them, including 10 antineoplastic agents: diclofenac, Bacillus Calmette-Guérin (BCG), megestrol acetate, tamoxifen, anastrozole, letrozole, leuprolide, goserelin, degarelix, and fluorouracil. Diclofenac, BCG, and mitomycin have been repurposed for cancer treatment.84-87 From 2003 to 2023, diclofenac was prescribed to 350 patients for mild-to-moderate pain, with only 2 patients receiving it for cancer in 2018. FDA-approved for bladder cancer in 1990, BCG was prescribed for cancer treatment for 1 patient in 2021 after being used for vaccines between 2003 and 2018. Tamoxifen, used for hormone receptor-positive breast cancer from 2004 to 2017 with 53 patients, switched to estrogen agonist-antagonists from 2017 to 2023 with 123 patients. Only a few of the 168 patients were prescribed tamoxifen using both codes.88-91 Anastrozole and letrozole were coded as antiestrogens for 7 and 18 patients, respectively, while leuprolide and goserelin were coded as gonadotropins for 59 and 18 patients. Degarelix was coded as antigonadotropins, fluorouracil as skin and mucous membrane agents miscellaneous, and megestrol acetate as progestins for 7, 6, and 3 patients, respectively. Duloxetine was given to 186 patients, primarily for depression from 2005 to 2023, with 7 patients treated for fibromyalgia from 2022 to 2023.
Antidepressants Observed
Tables 1 and 5 provide insight into the FDA approval of 14 antineoplastics and antidepressants and their CYP metabolic pathways.92-122 In Table 4, the most prescribed antidepressant classes are SNRIs, SRMs, SSRIs, TeCAs, NDRIs, and TCAs. This trend highlights a preference for newer medications with weak CYP inhibition. A total of 349 patients were prescribed SSRIs, 343 SNRIs, 119 SRMs, 109 TCAs, 83 TeCAs, and 79 NDRIs. MAOIs, SMRAs, and NMDARAs were not observed in this dataset. While there are instances of dextromethorphan-bupropion and sertraline-escitalopram being dispensed together, it remains unclear whether these were NMDARA combinations.
Among the 14 specific antineoplastic agents, 10 are metabolized by CYP isoenzymes, primarily CYP3A4. Duloxetine neither inhibits nor is metabolized by CYP3A4, a reason it is often recommended, following venlafaxine.
Both duloxetine and venlafaxine are used off-label for chemotherapy-induced peripheral neuropathy related to paclitaxel and docetaxel. According to the CYP metabolized pathway, duloxetine tends to have more favorable DDIs than venlafaxine. In PDTS data, 371 patients were treated with paclitaxel and 180 with docetaxel, with respective antidepressant prescriptions of 156 and 70. Of the 156 patients dispensed paclitaxel, 62 (40%) were dispensed with duloxetine compared to 43 (28%) with venlafaxine. Of the 70 patients dispensed docetaxel, 23 (33%) received duloxetine vs 24 (34%) with venlafaxine.
Of 85 patients prescribed duloxetine, 75 received it with either paclitaxel or docetaxel (5 received both). Five patients had documented AEs (1 neuropathy related). Of 67 patients prescribed venlafaxine, 66 received it with either paclitaxel or docetaxel. Two patients had documented AEs (1 was neuropathy related, the same patient who received duloxetine). Of the 687 patients treated with paclitaxel and 337 with docetaxel in all databases, 4 experienced neuropathic AEs from both medications.79
Antidepressants can increase the risk of bleeding, especially when combined with blood thinners, and may elevate blood pressure, particularly alongside stimulants. Of the 554 patients prescribed 9 different anticoagulants, enoxaparin, apixaban, and rivaroxaban were the most common (each > 100 patients). Among these, 201 patients (36%) received both anticoagulants and antidepressants: duloxetine for 64 patients, venlafaxine for 30, trazodone for 35, and sertraline for 26. There were no data available to assess bleeding rates related to the evaluation of DDIs between these medication classes.
Antidepressants can be prescribed for erectile dysfunction. Of the 148 patients prescribed an antidepressant for erectile dysfunction, duloxetine, trazodone, and mirtazapine were the most common. Antidepressant preferences varied by cancer type. Duloxetine was the only antidepressant used for all types of cancer. Venlafaxine, duloxetine, trazodone, sertraline, and escitalopram were the most prescribed antidepressants for breast cancer, while duloxetine, mirtazapine, citalopram, sertraline, and trazodone were the most prescribed for lung cancer. Sertraline, duloxetine, trazodone, amitriptyline, and escitalopram were most common for testicular cancer. Duloxetine, venlafaxine, trazodone, amitriptyline, and sertraline were the most prescribed for endometrial cancer, while duloxetine, venlafaxine, amitriptyline, citalopram, and sertraline were most prescribed for ovarian cancer.
The broadness of International Statistical Classification of Diseases, Tenth Revision codes made it challenging to identify nondepression diagnoses in the analyzed population. However, if all antidepressants were prescribed to treat depression, service members with cancer exhibited a higher depression rate (35%) than the general population (25%). Of 2104 patients, 191 (9.1%) had mood disorders, and 706 (33.6%) had mental disorders: 346 (49.0%) had 1 diagnosis, and 360 (51.0%) had multiple diagnoses. The percentage of diagnoses varied yearly, with notable drops in 2003, 2007, 2011, 2014, and 2018, and peaks in 2006, 2008, 2013, 2017, and 2022. This fluctuation was influenced by events like the establishment of PDTS in 2002, the 2008 economic recession, a hospital relocation in 2011, the 2014 Ebola outbreak, and the COVID-19 pandemic. Although the number of patients receiving antidepressants increased from 2019 to 2022, the overall percentage of patients receiving them did not significantly change from 2003 to 2022, aligning with previous research.5,125
Many medications have potential uses beyond what is detailed in the prescribing information. Antidepressants can relieve pain, while pain medications may help with depression. Opioids were once thought to effectively treat depression, but this perspective has changed with a greater understanding of their risks, including misuse.126-131 Pain is a severe and often unbearable AE of cancer. Of 2113 patients, 92% received opioids; 34% received both opioids and antidepressants; 2% received only antidepressants; and 7% received neither. This study didn’t clarify whether those on opioids alone recognized their depression or if those on both were aware of their dependence. While SSRIs are generally not addictive, they can lead to physical dependence, and any medication can be abused if not managed properly.132-134
Conclusions
This retrospective study analyzes data from antineoplastic agents used in systemic cancer treatment between 1988 and 2023, with a particular focus on the use of antidepressants. Data on antidepressant prescriptions are incomplete and specific to these agents, which means the findings cannot be generalized to all antidepressants. Hence, the results indicate that patients taking antidepressants had more diagnosed health issues and received more medications compared to patients who were not on these drugs.
This study underscores the need for further research into the effects of antidepressants on cancer treatment, utilizing all data from the DoD Cancer Registry. Future research should explore DDIs between antidepressants and other cancer and noncancer medications, as this study did not assess AE documentation, unlike in studies involving erlotinib, gefitinib, and paclitaxel.78,79 Further investigation is needed to evaluate the impact of discontinuing antidepressant use during cancer treatment. This comprehensive overview provides insights for clinicians to help them make informed decisions regarding the prescription of antidepressants in the context of cancer treatment.
Cancer patients experience depression at rates > 5 times that of the general population.1-11 Despite an increase in palliative care use, depression rates continued to rise.2-4 Between 5% to 16% of outpatients, 4% to 14% of inpatients, and up to 49% of patients receiving palliative care experience depression.5 This issue also impacts families and caregivers.1 A 2021 meta-analysis found that 23% of active military personnel and 20% of veterans experience depression.11
Antidepressants approved by the US Food and Drug Administration (FDA) target the serotonin, norepinephrine, or dopamine systems and include boxed warnings about an increased risk of suicidal thoughts in adults aged 18 to 24 years.12,13 These medications are categorized into several classes: monoamine oxidase inhibitors (MAOIs), tricyclic antidepressants (TCAs), tetracyclic antidepressants (TeCAs), norepinephrine-dopamine reuptake inhibitors (NDRIs), selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), serotonin receptor modulators (SRMs), serotonin-melatonin receptor antagonists (SMRAs), and N—methyl-D-aspartate receptor antagonists (NMDARAs).14,15 The first FDA-approved antidepressants, iproniazid (an MAOI) and imipramine (a TCA) laid the foundation for the development of newer classes like SSRIs and SNRIs.15-17
Older antidepressants such as MAOIs and TCAs are used less due to their adverse effects (AEs) and drug interactions. MAOIs, such as iproniazid, selegiline, moclobemide, tranylcypromine, isocarboxazid, and phenelzine, have numerous AEs and drug interactions, making them unsuitable for first- or second-line treatment of depression.14,18-21 TCAs such as doxepin, amitriptyline, nortriptyline, imipramine, desipramine, clomipramine, trimipramine, protriptyline, maprotiline, and amoxapine have a narrow therapeutic index requiring careful monitoring for signs of toxicity such as QRS widening, tremors, or confusion. Despite the issues, TCAs are generally classified as second-line agents for major depressive disorder (MDD). TCAs have off-label uses for migraine prophylaxis, treatment of obsessive-compulsive disorder (OCD), insomnia, and chronic pain management first-line.14,22-29
Newer antidepressants, including TeCAs and NDRIs, are typically more effective, but also come with safety concerns. TeCAs like mirtazapine interact with several medications, including MAOIs, serotonin-increasing drugs, alcohol, cannabidiol, and marijuana. Mirtazapine is FDA-approved for the treatment of moderate to severe depression in adults. It is also used off-label to treat insomnia, panic disorder, posttraumatic stress disorder (PTSD), generalized anxiety disorder (GAD), social anxiety disorder (SAD), headaches, and migraines. Compared to other antidepressants, mirtazapine is effective for all stages of depression and addresses a broad range of related symptoms.14,30-34 NDRIs, such as bupropion, also interact with various medications, including MAOIs, other antidepressants, stimulants, and alcohol. Bupropion is FDA-approved for smoking cessation and to treat depression and SAD. It is also used off-label for depression- related bipolar disorder or sexual dysfunction, attention-deficit/hyperactivity disorder (ADHD), and obesity.14,35-42
SSRIs, SNRIs, and SRMs should be used with caution. SSRIs such as sertraline, citalopram, escitalopram, fluoxetine, paroxetine, and fluvoxamine are first-line treatments for depression and various psychiatric disorders due to their safety and efficacy. Common AEs of SSRIs include sexual dysfunction, sleep disturbances, weight changes, and gastrointestinal (GI) issues. SSRIs can prolong the QT interval, posing a risk of life-threatening arrhythmia, and may interact with other medications, necessitating treatment adjustments. The FDA approved SSRIs for MDD, GAD, bulimia nervosa, bipolar depression, OCD, panic disorder, premenstrual dysphoric disorder, treatment-resistant depression, PTSD, and SAD. Off-label uses include binge eating disorder, body dysmorphic disorder, fibromyalgia, premature ejaculation, paraphilias, autism, Raynaud phenomenon, and vasomotor symptoms associated with menopause. Among SSRIs, sertraline and escitalopram are noted for their effectiveness and tolerability.14,43-53
SNRIs, including duloxetine, venlafaxine, desvenlafaxine, milnacipran, and levomilnacipran, may increase bleeding risk, especially when taken with blood thinners. They can also elevate blood pressure, which may worsen if combined with stimulants. SNRIs may interact with other medications that affect serotonin levels, increasing the risk of serotonin syndrome when taken with triptans, pain medications, or other antidepressants.14 Desvenlafaxine has been approved by the FDA (but not by the European Medicines Agency).54-56 Duloxetine is FDA-approved for the treatment of depression, neuropathic pain, anxiety disorders, fibromyalgia, and musculoskeletal disorders. It is used off-label to treat chemotherapy-induced peripheral neuropathy and stress urinary incontinence.57-61 Venlafaxine is FDA-approved for depression, SAD, and panic disorder, and is prescribed off-label to treat ADHD, neuropathy, fibromyalgia, cataplexy, and PTSD, either alone or in combination with other medications.62,63 Milnacipran is not approved for MDD; levomilnacipran received approval in 2013.64
SRMs such as trazodone, nefazodone, vilazodone, and vortioxetine also function as serotonin reuptake inhibitors.14,15 Trazodone is FDA-approved for MDD. It has been used off-label to treat anxiety, Alzheimer disease, substance misuse, bulimia nervosa, insomnia, fibromyalgia, and PTSD when first-line SSRIs are ineffective. A notable AE of trazodone is orthostatic hypotension, which can lead to dizziness and increase the risk of falls, especially in geriatric patients.65-70 Nefazodone was discontinued in Europe in 2003 due to rare cases of liver toxicity but remains available in the US.71-74 Vilazodone and vortioxetine are FDA-approved.
The latest classes of antidepressants include SMRAs and NMDARAs.14 Agomelatine, an SMRA, was approved in Europe in 2009 but rejected by the FDA in 2011 due to liver toxicity.75 NMDARAs like esketamine and a combination of dextromethorphan and bupropion received FDA approval in 2019 and 2022, respectively.76,77
This retrospective study analyzes noncancer drugs used during systemic chemotherapy based on a dataset of 14 antineoplastic agents. It sought to identify the most dispensed noncancer drug groups, discuss findings, compare patients with and without antidepressant prescriptions, and examine trends in antidepressant use from 2002 to 2023. This analysis expands on prior research.78-81
Methods
The Walter Reed National Military Medical Center Institutional Review Board approved the study protocol and ensured compliance with the Health Insurance Portability and Accountability Act as an exempt protocol. The Joint Pathology Center (JPC) of the US Department of Defense (DoD) Cancer Registry Program and Military Health System (MHS) data experts from the Comprehensive Ambulatory/Professional Encounter Record (CAPER) and Pharmacy Data Transaction Service (PDTS) provided data for the analysis.
Data Sources
The JPC DoD Cancer Registry Program contains data from 1998 to 2024. CAPER and PDTS are part of the MHS Data Repository/Management Analysis and Reporting Tool database. Each observation in CAPER represents an ambulatory encounter at a military treatment facility (MTF). CAPER records are available from 2003 to 2024. PDTS records are available from 2002 to 2004. Each observation in PDTS represents a prescription filled for an MHS beneficiary, excluding those filled at international civilian pharmacies and inpatient pharmacy prescriptions.
This cross-sectional analysis requested data extraction for specific cancer drugs from the DoD Cancer Registry, focusing on treatment details, diagnosis dates, patient demographics, and physicians’ comments on AEs. After identifying patients, CAPER was used to identify additional health conditions. PDTS was used to compile a list of prescription medications filled during systemic cancer treatment or < 2 years postdiagnosis.
The 2016 Surveillance, Epidemiology, and End Results Program Coding and Staging Manual and International Classification of Diseases for Oncology, 3rd edition, 1st revision, were used to decode disease and cancer types.82,83 Data sorting and analysis were performed using Microsoft Excel. The percentage for the total was calculated by using the number of patients or data available within the subgroup divided by the total number of patients or data variables. To compare the mean number of dispensed antidepressants to those without antidepressants, a 2-tailed, 2-sample z test was used to calculate the P value and determine statistical significance (P < .05) using socscistatistics.com.
Data were extracted 3 times between 2021 and 2023. The initial 2021 protocol focused on erlotinib and gefitinib. A modified protocol in 2022 added paclitaxel, cisplatin, docetaxel, pemetrexed, and crizotinib; further modification in 2023 included 8 new antineoplastic agents and 2 anticoagulants. Sotorasib has not been prescribed in the MHS, and JPC lacks records for noncancer drugs. The 2023 dataset comprised 2210 patients with cancer treated with 14 antineoplastic agents; 2104 had documented diagnoses and 2113 had recorded prescriptions. Data for erlotinib, gefitinib, and paclitaxel have been published previously.78,79
Results
Of 2113 patients with recorded prescriptions, 1297 patients (61.4%) received 109 cancer drugs, including 96 antineoplastics, 7 disease-modifying antirheumatic agents, 4 biologic response modifiers, and 2 calcitonin gene-related peptides. Fourteen antineoplastic agents had complete data from JPC, while others were noted for combination therapies or treatment switches from the PDTS (Table 1). Seventy-six cancer drugs were prescribed with antidepressants in 489 patients (eAppendix).

The JPC provided 2242 entries for 2210 patients, ranging in age from 2 months to 88 years (mean, 56 years), documenting treatment from September 1988 to January 2023. Thirty-two patients had duplicate entries due to multiple cancer locations or occurrences. Of the 2242 patients, 1541 (68.7%) were aged > 50 years, 975 patients (43.5%) had cancers that were stage III or IV, and 1267 (56.5%) had cancers that were stage 0, I, II, or not applicable/unknown. There were 51 different types of cancer: breast, lung, testicular, endometrial, and ovarian were most common (n ≥ 100 patients). Forty-two cancer types were documented among 750 patients prescribed antidepressants (Table 2).

The CAPER database recorded 8882 unique diagnoses for 2104 patients, while PDTS noted 1089 unique prescriptions within 273 therapeutic codes for 2113 patients. Nine therapeutic codes (opiate agonists, adrenals, cathartics-laxatives, nonsteroidal anti-inflammatory agents, antihistamines for GI conditions, 5-HT3 receptor antagonists, analgesics and antipyretic miscellanea, antineoplastic agents, and proton-pump inhibitors) and 8 drugs (dexamethasone, prochlorperazine, ondansetron, docusate, acetaminophen, ibuprofen, oxycodone, and polyethylene glycol 3350) were associated with > 1000 patients (≥ 50%). Patients had between 1 and 275 unique health conditions and filled 1 to 108 prescriptions. The mean (SD) number of diagnoses and prescriptions was 50 (28) and 29 (12), respectively. Of the 273 therapeutic codes, 30 groups were analyzed, with others categorized into miscellaneous groups such as lotions, vaccines, and devices. Significant differences in mean number of prescriptions were found for patients taking antidepressants compared to those not (P < .05), except for anticonvulsants and antipsychotics (P = .12 and .09, respectively) (Table 3).

Antidepressants
Of the 2113 patients with recorded prescriptions, 750 (35.5%) were dispensed 17 different antidepressants. Among these 17 antidepressants, 183 (8.7%) patients received duloxetine, 158 (7.5%) received venlafaxine, 118 (5.6%) received trazodone, and 107 (5.1%) received sertraline (Figure 1, Table 4). Of the 750 patients, 509 (67.9%) received 1 antidepressant, 168 (22.4%) received 2, 60 (8.0%) received 3, and 13 (1.7%) received > 3. Combinations varied, but only duloxetine and trazodone were prescribed to > 10 patients.



Antidepressants were prescribed annually at an overall mean (SD) rate of 23% (5%) from 2003 to 2022 (Figure 2). Patients on antidepressants during systemic therapy had a greater number of diagnosed medical conditions and received more prescription medications compared to those not taking antidepressants (P < .001) (Figure 3). The 745 patients taking antidepressants in CAPER data had between 1 and 275 diagnosed medical issues, with a mean (SD) of 55 (31) vs a range of 1 to 209 and a mean (SD) of 46 (26) for the 1359 patients not taking antidepressants. The 750 patients on antidepressants in PDTS data had between 8 and 108 prescriptions dispensed, with a mean (SD) of 32 (12), vs a range of 1 to 65 prescriptions and a mean (SD) of 29 (12) for 1363 patients not taking antidepressants.


Discussion
The JPC DoD Cancer Registry includes information on cancer types, stages, treatment regimens, and physicians’ notes, while noncancer drugs are sourced from the PDTS database. The pharmacy uses a different documentation system, leading to varied classifications.
Database reliance has its drawbacks. For example, megestrol is coded as a cancer drug, although it’s primarily used for endometrial or gynecologic cancers. Many drugs have multiple therapeutic codes assigned to them, including 10 antineoplastic agents: diclofenac, Bacillus Calmette-Guérin (BCG), megestrol acetate, tamoxifen, anastrozole, letrozole, leuprolide, goserelin, degarelix, and fluorouracil. Diclofenac, BCG, and mitomycin have been repurposed for cancer treatment.84-87 From 2003 to 2023, diclofenac was prescribed to 350 patients for mild-to-moderate pain, with only 2 patients receiving it for cancer in 2018. FDA-approved for bladder cancer in 1990, BCG was prescribed for cancer treatment for 1 patient in 2021 after being used for vaccines between 2003 and 2018. Tamoxifen, used for hormone receptor-positive breast cancer from 2004 to 2017 with 53 patients, switched to estrogen agonist-antagonists from 2017 to 2023 with 123 patients. Only a few of the 168 patients were prescribed tamoxifen using both codes.88-91 Anastrozole and letrozole were coded as antiestrogens for 7 and 18 patients, respectively, while leuprolide and goserelin were coded as gonadotropins for 59 and 18 patients. Degarelix was coded as antigonadotropins, fluorouracil as skin and mucous membrane agents miscellaneous, and megestrol acetate as progestins for 7, 6, and 3 patients, respectively. Duloxetine was given to 186 patients, primarily for depression from 2005 to 2023, with 7 patients treated for fibromyalgia from 2022 to 2023.
Antidepressants Observed
Tables 1 and 5 provide insight into the FDA approval of 14 antineoplastics and antidepressants and their CYP metabolic pathways.92-122 In Table 4, the most prescribed antidepressant classes are SNRIs, SRMs, SSRIs, TeCAs, NDRIs, and TCAs. This trend highlights a preference for newer medications with weak CYP inhibition. A total of 349 patients were prescribed SSRIs, 343 SNRIs, 119 SRMs, 109 TCAs, 83 TeCAs, and 79 NDRIs. MAOIs, SMRAs, and NMDARAs were not observed in this dataset. While there are instances of dextromethorphan-bupropion and sertraline-escitalopram being dispensed together, it remains unclear whether these were NMDARA combinations.
Among the 14 specific antineoplastic agents, 10 are metabolized by CYP isoenzymes, primarily CYP3A4. Duloxetine neither inhibits nor is metabolized by CYP3A4, a reason it is often recommended, following venlafaxine.
Both duloxetine and venlafaxine are used off-label for chemotherapy-induced peripheral neuropathy related to paclitaxel and docetaxel. According to the CYP metabolized pathway, duloxetine tends to have more favorable DDIs than venlafaxine. In PDTS data, 371 patients were treated with paclitaxel and 180 with docetaxel, with respective antidepressant prescriptions of 156 and 70. Of the 156 patients dispensed paclitaxel, 62 (40%) were dispensed with duloxetine compared to 43 (28%) with venlafaxine. Of the 70 patients dispensed docetaxel, 23 (33%) received duloxetine vs 24 (34%) with venlafaxine.
Of 85 patients prescribed duloxetine, 75 received it with either paclitaxel or docetaxel (5 received both). Five patients had documented AEs (1 neuropathy related). Of 67 patients prescribed venlafaxine, 66 received it with either paclitaxel or docetaxel. Two patients had documented AEs (1 was neuropathy related, the same patient who received duloxetine). Of the 687 patients treated with paclitaxel and 337 with docetaxel in all databases, 4 experienced neuropathic AEs from both medications.79
Antidepressants can increase the risk of bleeding, especially when combined with blood thinners, and may elevate blood pressure, particularly alongside stimulants. Of the 554 patients prescribed 9 different anticoagulants, enoxaparin, apixaban, and rivaroxaban were the most common (each > 100 patients). Among these, 201 patients (36%) received both anticoagulants and antidepressants: duloxetine for 64 patients, venlafaxine for 30, trazodone for 35, and sertraline for 26. There were no data available to assess bleeding rates related to the evaluation of DDIs between these medication classes.
Antidepressants can be prescribed for erectile dysfunction. Of the 148 patients prescribed an antidepressant for erectile dysfunction, duloxetine, trazodone, and mirtazapine were the most common. Antidepressant preferences varied by cancer type. Duloxetine was the only antidepressant used for all types of cancer. Venlafaxine, duloxetine, trazodone, sertraline, and escitalopram were the most prescribed antidepressants for breast cancer, while duloxetine, mirtazapine, citalopram, sertraline, and trazodone were the most prescribed for lung cancer. Sertraline, duloxetine, trazodone, amitriptyline, and escitalopram were most common for testicular cancer. Duloxetine, venlafaxine, trazodone, amitriptyline, and sertraline were the most prescribed for endometrial cancer, while duloxetine, venlafaxine, amitriptyline, citalopram, and sertraline were most prescribed for ovarian cancer.
The broadness of International Statistical Classification of Diseases, Tenth Revision codes made it challenging to identify nondepression diagnoses in the analyzed population. However, if all antidepressants were prescribed to treat depression, service members with cancer exhibited a higher depression rate (35%) than the general population (25%). Of 2104 patients, 191 (9.1%) had mood disorders, and 706 (33.6%) had mental disorders: 346 (49.0%) had 1 diagnosis, and 360 (51.0%) had multiple diagnoses. The percentage of diagnoses varied yearly, with notable drops in 2003, 2007, 2011, 2014, and 2018, and peaks in 2006, 2008, 2013, 2017, and 2022. This fluctuation was influenced by events like the establishment of PDTS in 2002, the 2008 economic recession, a hospital relocation in 2011, the 2014 Ebola outbreak, and the COVID-19 pandemic. Although the number of patients receiving antidepressants increased from 2019 to 2022, the overall percentage of patients receiving them did not significantly change from 2003 to 2022, aligning with previous research.5,125
Many medications have potential uses beyond what is detailed in the prescribing information. Antidepressants can relieve pain, while pain medications may help with depression. Opioids were once thought to effectively treat depression, but this perspective has changed with a greater understanding of their risks, including misuse.126-131 Pain is a severe and often unbearable AE of cancer. Of 2113 patients, 92% received opioids; 34% received both opioids and antidepressants; 2% received only antidepressants; and 7% received neither. This study didn’t clarify whether those on opioids alone recognized their depression or if those on both were aware of their dependence. While SSRIs are generally not addictive, they can lead to physical dependence, and any medication can be abused if not managed properly.132-134
Conclusions
This retrospective study analyzes data from antineoplastic agents used in systemic cancer treatment between 1988 and 2023, with a particular focus on the use of antidepressants. Data on antidepressant prescriptions are incomplete and specific to these agents, which means the findings cannot be generalized to all antidepressants. Hence, the results indicate that patients taking antidepressants had more diagnosed health issues and received more medications compared to patients who were not on these drugs.
This study underscores the need for further research into the effects of antidepressants on cancer treatment, utilizing all data from the DoD Cancer Registry. Future research should explore DDIs between antidepressants and other cancer and noncancer medications, as this study did not assess AE documentation, unlike in studies involving erlotinib, gefitinib, and paclitaxel.78,79 Further investigation is needed to evaluate the impact of discontinuing antidepressant use during cancer treatment. This comprehensive overview provides insights for clinicians to help them make informed decisions regarding the prescription of antidepressants in the context of cancer treatment.
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- Paxil (paroxetine). Prescribing Information. Apotex Inc; 2021. Accessed April 4, 2025. https://www.accessdata.fda.gov/drugsatfda_docs/label/2021/020031s077lbl.pdf
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Assessing the Impact of Antidepressants on Cancer Treatment: A Retrospective Analysis of 14 Antineoplastic Agents
Assessing the Impact of Antidepressants on Cancer Treatment: A Retrospective Analysis of 14 Antineoplastic Agents
Safety and Efficacy of Ezetimibe in Patients With and Without Chronic Kidney Disease at a Pharmacist-Managed Clinic
Statins are widely used to reduce low-density lipoprotein (LDL) and non-high-density lipoprotein (HDL) levels for the prevention of atherosclerotic cardiovascular disease (ASCVD).1 However, despite maximally tolerated statin therapy, many patients may not reach their LDL and non-HDL goals. Some patients may experience adverse events (AEs), particularly muscle-related AEs, which can limit the use of these medications.
The 2022 American College of Cardiology (ACC) expert consensus pathway recommends a goal LDL of < 55 mg/dL in very high-risk patients, defined as those with a history of multiple major ASCVD events or 1 major ASCVD event and multiple high-risk conditions.2 Major ASCVD events include acute coronary syndrome within 12 months, history of myocardial infarction (MI) or ischemic stroke, and symptomatic peripheral arterial disease (ie, claudication with ankle-brachial index < 0.85 or previous revascularization or amputation). Factors for being considered high risk include age > 65 years, heterozygous familial hypercholesterolemia, history of prior coronary artery bypass surgery or percutaneous coronary intervention outside the major ASCVD events, diabetes, hypertension, chronic kidney disease (CKD) (estimated glomerular filtration rate [eGFR] 15-59 mL/min/1.73 m2), current smoking, persistently elevated LDL cholesterol (LDL-C) levels despite maximally tolerated statin therapy and ezetimibe, and history of congestive heart failure.2 For these patients, statin therapy alone may not achieve LDL goal.
The ACC recommends ezetimibe as the initial nonstatin therapy in patients who are not at their goal LDL.2 Ezetimibe works by inhibiting Niemann-Pick C1-Like 1 protein, which causes reduced cholesterol absorption in the small intestine.2,3 Previous studies have shown the benefit of ezetimibe for LDL reduction and ASCVD prevention.4-7 The 2015 IMPROVE-IT study found the combination of simvastatin and ezetimibe resulted in a significantly lower risk of cardiovascular events than simvastatin monotherapy. IMPROVE-IT also reported a further clinical benefit when lower LDL targets (ie, < 55 mg/dL) are achieved, which aligns with the expert consensus pathway recommendations for a lower LDL goal for very high-risk patients.2,5
The RACING trial found that treatment with a moderate-intensity statin and ezetimibe was noninferior to treatment with a high-intensity statin for the primary outcome of occurrence of cardiovascular death, major cardiovascular events, or nonfatal stroke within 3 years. The combination of moderate-intensity statin and ezetimibe achieved lower LDL-C levels and lower incidence of drug intolerance compared to high intensity statin monotherapy.6 The SHARP-CKD study assessed major atherosclerotic events in patients with CKD who had no history of MI or coronary revascularization. The study found that lowering LDL-C with the combination of simvastatin plus ezetimibe safely reduces the risk of major atherosclerotic events in a wide range of patients with CKD.7
Lastly, the 2019 EWTOPIA 75 study found that ezetimibe noted a statistically significant reduction in the incidence of the composite of sudden cardiac death, MI, coronary revascularization, or stroke compared to placebo. Ezetimibe showed benefits in preventing ASCVD events independently of statin therapy.8 These clinical trials provided evidence for the efficacy of ezetimibe for secondary or primary prevention of ASCVD, patients with CKD, and patients who are not at their LDL goal despite maximally tolerated statin therapy.
Reductions in LDL levels with ezetimibe are reported to be 15% to 19% for monotherapy and 13% to 25% when used in combination with a statin.4 Given that the ACC now recommends lower LDL goals, patients may need additional lowering despite taking maximally tolerated statin therapy.2 Additionally, the package insert for ezetimibe reports increased area under the curve (AUC) values of ezetimibe and its metabolites in patients with severe renal disease. It is anticipated that ezetimibe may show an increased reduction of LDL and non-HDL, but there may also be an increased risk for muscle-related AEs.3
This quality-assurance quality improvement project investigated the use of ezetimibe in patients with CKD to determine whether there is further LDL and non-HDL reduction in this patient population. It sought to determine the LDL and non-HDL percentage reduction in patients with and without CKD at the Wilkes-Barre Veterans Affairs Medical Center (WBVAMC) and whether there is an increased risk for muscle-related AEs. Determining the percentage reduction of LDL and non-HDL within this population can help increase use of ezetimibe in patients not at their LDL or non-HDL goal or for those patients unable to tolerate statin therapy.
Methods
This single-center retrospective chart review investigated patients prescribed ezetimibe by a patient aligned care team (PACT) pharmacist at WBVAMC between September 1, 2021, and September 1, 2023. This project was determined to be nonresearch by the Veterans Integrated Service Network 4 multisite institutional review board. Patients were excluded from the review if they started taking ezetimibe outside of the prespecified time frame, if ezetimibe was initiated by a non-WBVAMC PACT pharmacist, or if there was no follow-up lipid panel obtained within 6 months of initiation of ezetimibe.
The primary outcomes were to determine the percentage mean change in LDL and non-HDL reduction and the incidence of muscle-related AEs after initiation of ezetimibe in patients without CKD. The secondary outcomes were to determine the percentage mean change in LDL and non-HDL levels and the incidence of muscle-related AEs after initiation of ezetimibe in patients with CKD. For this study, CKD was defined as a patient having an eGFR 15 to 60 ml/min/1.73 m2. Non-HDL is the combination of LDL-C and very LDL-C and represents all potentially atherogenic particles. The 2022 Expert Consensus Pathway included non-HDL goals in addition to LDL goals.2 Non-HDL cholesterol levels can be used for patients with elevated triglycerides where LDL levels may not be as accurate. To account for instances of elevated triglycerides, this study assessed changes in both LDL and non-HDL levels.
Data were collected from the US Department of Veterans Affairs (VA) Computerized Patient Record System (CPRS) and recorded in a spreadsheet. Collected data included age, sex, race, concomitant cholesterol-lowering medications (statin, proprotein convertase subtilisin/kexin type 9 [PCSK9] inhibitor, bempedoic acid, fish oil, niacin, bile acid sequestrants, and fibrates), baseline lipid panel, lipid panel within 6 months of ezetimibe initiation, and eGFR level. If the patient’s LDL or non-HDL levels worsened on the follow-up lipid panel, their baseline LDL and non-HDL levels were used to calculate the percentage reduction; thus, the percentage reduction would be 0%. This strategy was used in prior research, notably the IMPROVE-IT and SHARP-CKD trials.
Ezetimibe 5 mg once daily was used in this study based on a 2008 VA study that evaluated the use of ezetimibe 5 mg vs ezetimibe 10 mg and the percentage reduction of LDL with each dose. The study found no significant difference between the 5 mg and 10 mg dose.9 Most patients included in this study received the 5 mg dose.
Results
This retrospective chart review consisted of 173 patients, 137 (79.2%) without CKD and 36 (20.8%) with CKD at baseline. The mean age was 69.6 years, 155 (89.6%) patients were male, and 18 (10.4%) were female. There were 164 concomitant medications, including 115 patients prescribed a statin and 38 patients prescribed fish oil (Table 1).
Patients without CKD had mean reductions in LDL levels of 23.5% and non-HDL levels of 21.7% (Figure). Patients who had an increase in LDL and non-HDL levels were excluded to control for potential confounding factors such as dietary changes, discontinuation of ezetimibe therapy, nonadherence to ezetimibe, and medication changes that impacted follow-up laboratory tests such as discontinuation of a statin. Fifteen patients experienced an increase in LDL or non-HDL levels. After excluding these patients, those without CKD had a mean reduction in LDL levels of 28.0% and non-HDL levels of 25.5%. Nineteen (13.9%) patients without CKD experienced a muscle-related AE (Table 2). One patient discontinued ezetimibe and statin use following a Lyme disease diagnosis due to concerns over potential muscle-related AEs.
Patients with CKD had a mean reduction in LDL and non-HDL levels of 27.0% and 24.8%, respectively. Patients with an increase in LDL or non-HDL levels were also excluded to help control for potential confounding factors. After excluding 4 patients with increased LDL and non-HDL levels, the mean reduction in LDL and non-HDL levels was 30.5% and 27.5%, respectively. Five (13.9%) patients with CKD experienced muscle-related AEs thought to be due to ezetimibe. Other AEs (eg, urticaria, diarrhea, reflux, dizziness, headache, upset stomach) were reported that led to discontinuation of ezetimibe, but only muscle-related AEs were analyzed.
Discussion
This retrospective chart review found larger reductions in LDL and non-HDL levels for patients with CKD than reported in the literature.4 Based on the findings that indicate a greater cholesterol reduction with ezetimibe, the results suggest an underutilization of ezetimibe in clinical practice, which may be due to clinicians favoring statin therapy and overlooking ezetimibe as a viable option based on recommendation in earlier guidelines. The 2022 guidelines transitioned from a statin focus to a focus on LDL targets and goals.2
According to the ACC, there is evidence to support a direct relationship between LDL-C levels, atherosclerosis progression, and ASCVD event risk.2 Absolute LDL-C level reduction is directly associated with ASCVD risk reduction which supports the LDL hypothesis. There appears to be no specific LDL-C level below which benefit ceases.2 This suggests that lower LDL-C targets (< 55 mg/dL) should be used when clinically indicated. Many patients are either unable to reach their goal LDL levels with statin monotherapy or are unable to tolerate statin therapy at higher doses, which may require additional pharmacotherapy to reach goal LDL-C. The ACC expert consensus pathway recommends ezetimibe as the initial add-on treatment to statins.2 The RACING trial showed the benefit of adding ezetimibe to a moderate-intensity statin vs increasing to a high-intensity statin dose. This trial found patients had lower LDL levels and lower rates of intolerances, which further supports ezetimibe use.6
This quality improvement project assessed LDL and non-HDL level reduction in patients with CKD. As anticipated, there was greater reduction in LDL and non-HDL levels seen in patients with CKD. The SHARP-CKD trial also found reductions in LDL levels with ezetimibe in patients with CKD.7 Given the reduction in LDL and non-HDL levels with ezetimibe in patients with or without CKD, add-on therapy of ezetimibe should be recommended for patients who do not achieve their LDL goals with statin therapy or for patients who intolerant to statin therapy.
The ezetimibe package insert reports myalgias incidence to be < 5% in patients and research has shown up to a 20% incidence of muscle-related AEs with statin therapy.3,10 Based on the package information reporting increased AUC values of ezetimibe and its metabolites in patients with severe renal disease, it was anticipated there may be an increased risk of muscle-related AEs in patients with CKD.3 However, this study found the same incidence of muscle-related AEs in patients with and without CKD. Previous research on statin-intolerant patients found the incidence of muscle-related AEs with ezetimibe to be 23.0% and 28.8%.11,12 This increased incidence of muscle-related AEs may be the result of including patients with a history of statin intolerance. Collectively, data from clinical trials and this study indicate that patients with prior intolerances to statins appear to have a higher likelihood of developing a muscle-related AEs with ezetimibe.11,12 Clinicians and patients should be educated on the potential for these AEs and be aware that the likelihood may be greater if there is a history of statin intolerance. To our knowledge, this was the first study to evaluate muscle-related AEs with ezetimibe in patients with and without CKD.
Limitations
This retrospective chart review was performed over a prespecified period and only patients initiated on ezetimibe by a PACT pharmacist were included. This study did not assess the percentage of LDL reduction in patients on concomitant statins vs those who were not on concomitant statins. The study only included 173 patients. Additionally, the study was primarily composed of White men and may not be representative of other populations. In addition, veterans may not be representative of the general population given their high comorbidity burden and other exposures. Some reported muscle-related AEs associated with ezetimibe may be attributed to the nocebo effect.
Conclusions
The results of this retrospective chart review suggest there may be a larger mean reduction in LDL and non-HDL levels seen with ezetimibe therapy than reported within the literature. There was a larger mean reduction in LDL and non-HDL levels in patients with CKD than in patients without CKD. Additionally, there were the same rates of muscle-related AEs with ezetimibe therapy in patients with and without CKD. The rates of muscle-related AEs with ezetimibe therapy were higher than reported in the medication’s package insert, but lower than reported in literature that included statin-intolerant patients. These results indicate there may be a benefit to an increase in use of ezetimibe in clinical practice due to its increased effectiveness and safety in patients with and without CKD. Ultimately, this can help patients achieve their LDL goals as recommended by ACC clinical practice guidelines.
Grundy SM, Stone NJ, Bailey AL, et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol. 2019;73(24) e285-e350. doi:10.1016/j.jacc.2018.11.003
Writing Committee, Lloyd-Jones DM, Morris PB, et al. 2022 ACC expert consensus decision pathway on the role of nonstatin therapies for LDL-cholesterol lowering in the management of atherosclerotic cardiovascular disease risk: a report of the American College of Cardiology Solution Set Oversight Committee. J Am Coll Cardiol. 2022;80(14):1366-1418. doi:10.1016/j.jacc.2022.07.006
US Food and Drug Administration. Ezetimibe. 2007. Accessed April 1, 2025. https://www.accessdata.fda.gov/drugsatfda_docs/label/2008/021445s019lbl.pdf
Singh A, Cho LS. Nonstatin therapy to reduce low-density lipoprotein cholesterol and improve cardiovascular outcomes. Cleve Clin J Med. 2024;91(1):53-63. doi:10.3949/ccjm.91a.23058
Cannon CP, Blazing MA, Giugliano RP, et al. Ezetimibe added to statin therapy after acute coronary syndromes. N Engl J Med. 2015;372(25):2387-2397. doi:10.1056/NEJMoa1410489
Kim B, Hong S, Lee Y, et al. Long-term efficacy and safety of moderate-intensity statin with ezetimibe combination therapy versus high-intensity statin monotherapy in patients with atherosclerotic cardiovascular disease (RACING): a randomised, open-label, non-inferiority trial. Lancet. 2022;400(10349):380-390. doi:10.1016/S0140-6736(22)00916-3
Baigent C, Landray MJ, Reith C, et al. The effects of lowering LDL cholesterol with simvastatin plus ezetimibe in patients with chronic kidney disease (Study of Heart and Renal Protection): a randomised placebo-controlled trial. Lancet. 2011;377(9784):2181-2192. doi:10.1016/S0140-6736(11)60739-3
Ouchi Y, Sasaki J, Arai H, et al. Ezetimibe lipid-lowering trial on prevention of atherosclerotic cardiovascular disease in 75 or older (EWTOPIA 75): a randomized, controlled trial. Circulation. 2019;140:992-1003. doi:10.1161/CIRCULATIONAHA.118.039415
Baruch L, Gupta B, Lieberman-Blum SS, Agarwal S, Eng C. Ezetimibe 5 and 10 mg for lowering LDL-C: potential billion-dollar savings with improved tolerability. Am J Manag Care. 2008;14(10):637-641. https://www.ajmc.com/view/oct08-3644p637-641
Stroes ES, Thompson PD, Corsini A, et al. Statin-associated muscle symptoms: impact on statin therapy-European Atherosclerosis Society Consensus Panel Statement on Assessment, Aetiology and Management. Eur Heart J. 2015;36(17):1012-1022. doi:10.1093/eurheartj/ehv043
Stroes E, Colquhoun D, Sullivan D, et al. Anti-PCSK9 antibody effectively lowers cholesterol in patients with statin intolerance: the GAUSS-2 randomized, placebo-controlled phase 3 clinical trial of evolocumab. J Am Coll Cardiol. 2014;63(23):2541-2548. doi:10.1016/j.jacc.2014.03.019
Nissen SE, Stroes E, Dent-Acosta RE, et al. Efficacy and tolerability of evolocumab vs ezetimibe in patients with muscle-related statin intolerance: the GAUSS-3 randomized clinical trial. JAMA. 2016;315(15):1580-1590. doi:10.1001/jama.2016.3608
Statins are widely used to reduce low-density lipoprotein (LDL) and non-high-density lipoprotein (HDL) levels for the prevention of atherosclerotic cardiovascular disease (ASCVD).1 However, despite maximally tolerated statin therapy, many patients may not reach their LDL and non-HDL goals. Some patients may experience adverse events (AEs), particularly muscle-related AEs, which can limit the use of these medications.
The 2022 American College of Cardiology (ACC) expert consensus pathway recommends a goal LDL of < 55 mg/dL in very high-risk patients, defined as those with a history of multiple major ASCVD events or 1 major ASCVD event and multiple high-risk conditions.2 Major ASCVD events include acute coronary syndrome within 12 months, history of myocardial infarction (MI) or ischemic stroke, and symptomatic peripheral arterial disease (ie, claudication with ankle-brachial index < 0.85 or previous revascularization or amputation). Factors for being considered high risk include age > 65 years, heterozygous familial hypercholesterolemia, history of prior coronary artery bypass surgery or percutaneous coronary intervention outside the major ASCVD events, diabetes, hypertension, chronic kidney disease (CKD) (estimated glomerular filtration rate [eGFR] 15-59 mL/min/1.73 m2), current smoking, persistently elevated LDL cholesterol (LDL-C) levels despite maximally tolerated statin therapy and ezetimibe, and history of congestive heart failure.2 For these patients, statin therapy alone may not achieve LDL goal.
The ACC recommends ezetimibe as the initial nonstatin therapy in patients who are not at their goal LDL.2 Ezetimibe works by inhibiting Niemann-Pick C1-Like 1 protein, which causes reduced cholesterol absorption in the small intestine.2,3 Previous studies have shown the benefit of ezetimibe for LDL reduction and ASCVD prevention.4-7 The 2015 IMPROVE-IT study found the combination of simvastatin and ezetimibe resulted in a significantly lower risk of cardiovascular events than simvastatin monotherapy. IMPROVE-IT also reported a further clinical benefit when lower LDL targets (ie, < 55 mg/dL) are achieved, which aligns with the expert consensus pathway recommendations for a lower LDL goal for very high-risk patients.2,5
The RACING trial found that treatment with a moderate-intensity statin and ezetimibe was noninferior to treatment with a high-intensity statin for the primary outcome of occurrence of cardiovascular death, major cardiovascular events, or nonfatal stroke within 3 years. The combination of moderate-intensity statin and ezetimibe achieved lower LDL-C levels and lower incidence of drug intolerance compared to high intensity statin monotherapy.6 The SHARP-CKD study assessed major atherosclerotic events in patients with CKD who had no history of MI or coronary revascularization. The study found that lowering LDL-C with the combination of simvastatin plus ezetimibe safely reduces the risk of major atherosclerotic events in a wide range of patients with CKD.7
Lastly, the 2019 EWTOPIA 75 study found that ezetimibe noted a statistically significant reduction in the incidence of the composite of sudden cardiac death, MI, coronary revascularization, or stroke compared to placebo. Ezetimibe showed benefits in preventing ASCVD events independently of statin therapy.8 These clinical trials provided evidence for the efficacy of ezetimibe for secondary or primary prevention of ASCVD, patients with CKD, and patients who are not at their LDL goal despite maximally tolerated statin therapy.
Reductions in LDL levels with ezetimibe are reported to be 15% to 19% for monotherapy and 13% to 25% when used in combination with a statin.4 Given that the ACC now recommends lower LDL goals, patients may need additional lowering despite taking maximally tolerated statin therapy.2 Additionally, the package insert for ezetimibe reports increased area under the curve (AUC) values of ezetimibe and its metabolites in patients with severe renal disease. It is anticipated that ezetimibe may show an increased reduction of LDL and non-HDL, but there may also be an increased risk for muscle-related AEs.3
This quality-assurance quality improvement project investigated the use of ezetimibe in patients with CKD to determine whether there is further LDL and non-HDL reduction in this patient population. It sought to determine the LDL and non-HDL percentage reduction in patients with and without CKD at the Wilkes-Barre Veterans Affairs Medical Center (WBVAMC) and whether there is an increased risk for muscle-related AEs. Determining the percentage reduction of LDL and non-HDL within this population can help increase use of ezetimibe in patients not at their LDL or non-HDL goal or for those patients unable to tolerate statin therapy.
Methods
This single-center retrospective chart review investigated patients prescribed ezetimibe by a patient aligned care team (PACT) pharmacist at WBVAMC between September 1, 2021, and September 1, 2023. This project was determined to be nonresearch by the Veterans Integrated Service Network 4 multisite institutional review board. Patients were excluded from the review if they started taking ezetimibe outside of the prespecified time frame, if ezetimibe was initiated by a non-WBVAMC PACT pharmacist, or if there was no follow-up lipid panel obtained within 6 months of initiation of ezetimibe.
The primary outcomes were to determine the percentage mean change in LDL and non-HDL reduction and the incidence of muscle-related AEs after initiation of ezetimibe in patients without CKD. The secondary outcomes were to determine the percentage mean change in LDL and non-HDL levels and the incidence of muscle-related AEs after initiation of ezetimibe in patients with CKD. For this study, CKD was defined as a patient having an eGFR 15 to 60 ml/min/1.73 m2. Non-HDL is the combination of LDL-C and very LDL-C and represents all potentially atherogenic particles. The 2022 Expert Consensus Pathway included non-HDL goals in addition to LDL goals.2 Non-HDL cholesterol levels can be used for patients with elevated triglycerides where LDL levels may not be as accurate. To account for instances of elevated triglycerides, this study assessed changes in both LDL and non-HDL levels.
Data were collected from the US Department of Veterans Affairs (VA) Computerized Patient Record System (CPRS) and recorded in a spreadsheet. Collected data included age, sex, race, concomitant cholesterol-lowering medications (statin, proprotein convertase subtilisin/kexin type 9 [PCSK9] inhibitor, bempedoic acid, fish oil, niacin, bile acid sequestrants, and fibrates), baseline lipid panel, lipid panel within 6 months of ezetimibe initiation, and eGFR level. If the patient’s LDL or non-HDL levels worsened on the follow-up lipid panel, their baseline LDL and non-HDL levels were used to calculate the percentage reduction; thus, the percentage reduction would be 0%. This strategy was used in prior research, notably the IMPROVE-IT and SHARP-CKD trials.
Ezetimibe 5 mg once daily was used in this study based on a 2008 VA study that evaluated the use of ezetimibe 5 mg vs ezetimibe 10 mg and the percentage reduction of LDL with each dose. The study found no significant difference between the 5 mg and 10 mg dose.9 Most patients included in this study received the 5 mg dose.
Results
This retrospective chart review consisted of 173 patients, 137 (79.2%) without CKD and 36 (20.8%) with CKD at baseline. The mean age was 69.6 years, 155 (89.6%) patients were male, and 18 (10.4%) were female. There were 164 concomitant medications, including 115 patients prescribed a statin and 38 patients prescribed fish oil (Table 1).
Patients without CKD had mean reductions in LDL levels of 23.5% and non-HDL levels of 21.7% (Figure). Patients who had an increase in LDL and non-HDL levels were excluded to control for potential confounding factors such as dietary changes, discontinuation of ezetimibe therapy, nonadherence to ezetimibe, and medication changes that impacted follow-up laboratory tests such as discontinuation of a statin. Fifteen patients experienced an increase in LDL or non-HDL levels. After excluding these patients, those without CKD had a mean reduction in LDL levels of 28.0% and non-HDL levels of 25.5%. Nineteen (13.9%) patients without CKD experienced a muscle-related AE (Table 2). One patient discontinued ezetimibe and statin use following a Lyme disease diagnosis due to concerns over potential muscle-related AEs.
Patients with CKD had a mean reduction in LDL and non-HDL levels of 27.0% and 24.8%, respectively. Patients with an increase in LDL or non-HDL levels were also excluded to help control for potential confounding factors. After excluding 4 patients with increased LDL and non-HDL levels, the mean reduction in LDL and non-HDL levels was 30.5% and 27.5%, respectively. Five (13.9%) patients with CKD experienced muscle-related AEs thought to be due to ezetimibe. Other AEs (eg, urticaria, diarrhea, reflux, dizziness, headache, upset stomach) were reported that led to discontinuation of ezetimibe, but only muscle-related AEs were analyzed.
Discussion
This retrospective chart review found larger reductions in LDL and non-HDL levels for patients with CKD than reported in the literature.4 Based on the findings that indicate a greater cholesterol reduction with ezetimibe, the results suggest an underutilization of ezetimibe in clinical practice, which may be due to clinicians favoring statin therapy and overlooking ezetimibe as a viable option based on recommendation in earlier guidelines. The 2022 guidelines transitioned from a statin focus to a focus on LDL targets and goals.2
According to the ACC, there is evidence to support a direct relationship between LDL-C levels, atherosclerosis progression, and ASCVD event risk.2 Absolute LDL-C level reduction is directly associated with ASCVD risk reduction which supports the LDL hypothesis. There appears to be no specific LDL-C level below which benefit ceases.2 This suggests that lower LDL-C targets (< 55 mg/dL) should be used when clinically indicated. Many patients are either unable to reach their goal LDL levels with statin monotherapy or are unable to tolerate statin therapy at higher doses, which may require additional pharmacotherapy to reach goal LDL-C. The ACC expert consensus pathway recommends ezetimibe as the initial add-on treatment to statins.2 The RACING trial showed the benefit of adding ezetimibe to a moderate-intensity statin vs increasing to a high-intensity statin dose. This trial found patients had lower LDL levels and lower rates of intolerances, which further supports ezetimibe use.6
This quality improvement project assessed LDL and non-HDL level reduction in patients with CKD. As anticipated, there was greater reduction in LDL and non-HDL levels seen in patients with CKD. The SHARP-CKD trial also found reductions in LDL levels with ezetimibe in patients with CKD.7 Given the reduction in LDL and non-HDL levels with ezetimibe in patients with or without CKD, add-on therapy of ezetimibe should be recommended for patients who do not achieve their LDL goals with statin therapy or for patients who intolerant to statin therapy.
The ezetimibe package insert reports myalgias incidence to be < 5% in patients and research has shown up to a 20% incidence of muscle-related AEs with statin therapy.3,10 Based on the package information reporting increased AUC values of ezetimibe and its metabolites in patients with severe renal disease, it was anticipated there may be an increased risk of muscle-related AEs in patients with CKD.3 However, this study found the same incidence of muscle-related AEs in patients with and without CKD. Previous research on statin-intolerant patients found the incidence of muscle-related AEs with ezetimibe to be 23.0% and 28.8%.11,12 This increased incidence of muscle-related AEs may be the result of including patients with a history of statin intolerance. Collectively, data from clinical trials and this study indicate that patients with prior intolerances to statins appear to have a higher likelihood of developing a muscle-related AEs with ezetimibe.11,12 Clinicians and patients should be educated on the potential for these AEs and be aware that the likelihood may be greater if there is a history of statin intolerance. To our knowledge, this was the first study to evaluate muscle-related AEs with ezetimibe in patients with and without CKD.
Limitations
This retrospective chart review was performed over a prespecified period and only patients initiated on ezetimibe by a PACT pharmacist were included. This study did not assess the percentage of LDL reduction in patients on concomitant statins vs those who were not on concomitant statins. The study only included 173 patients. Additionally, the study was primarily composed of White men and may not be representative of other populations. In addition, veterans may not be representative of the general population given their high comorbidity burden and other exposures. Some reported muscle-related AEs associated with ezetimibe may be attributed to the nocebo effect.
Conclusions
The results of this retrospective chart review suggest there may be a larger mean reduction in LDL and non-HDL levels seen with ezetimibe therapy than reported within the literature. There was a larger mean reduction in LDL and non-HDL levels in patients with CKD than in patients without CKD. Additionally, there were the same rates of muscle-related AEs with ezetimibe therapy in patients with and without CKD. The rates of muscle-related AEs with ezetimibe therapy were higher than reported in the medication’s package insert, but lower than reported in literature that included statin-intolerant patients. These results indicate there may be a benefit to an increase in use of ezetimibe in clinical practice due to its increased effectiveness and safety in patients with and without CKD. Ultimately, this can help patients achieve their LDL goals as recommended by ACC clinical practice guidelines.
Statins are widely used to reduce low-density lipoprotein (LDL) and non-high-density lipoprotein (HDL) levels for the prevention of atherosclerotic cardiovascular disease (ASCVD).1 However, despite maximally tolerated statin therapy, many patients may not reach their LDL and non-HDL goals. Some patients may experience adverse events (AEs), particularly muscle-related AEs, which can limit the use of these medications.
The 2022 American College of Cardiology (ACC) expert consensus pathway recommends a goal LDL of < 55 mg/dL in very high-risk patients, defined as those with a history of multiple major ASCVD events or 1 major ASCVD event and multiple high-risk conditions.2 Major ASCVD events include acute coronary syndrome within 12 months, history of myocardial infarction (MI) or ischemic stroke, and symptomatic peripheral arterial disease (ie, claudication with ankle-brachial index < 0.85 or previous revascularization or amputation). Factors for being considered high risk include age > 65 years, heterozygous familial hypercholesterolemia, history of prior coronary artery bypass surgery or percutaneous coronary intervention outside the major ASCVD events, diabetes, hypertension, chronic kidney disease (CKD) (estimated glomerular filtration rate [eGFR] 15-59 mL/min/1.73 m2), current smoking, persistently elevated LDL cholesterol (LDL-C) levels despite maximally tolerated statin therapy and ezetimibe, and history of congestive heart failure.2 For these patients, statin therapy alone may not achieve LDL goal.
The ACC recommends ezetimibe as the initial nonstatin therapy in patients who are not at their goal LDL.2 Ezetimibe works by inhibiting Niemann-Pick C1-Like 1 protein, which causes reduced cholesterol absorption in the small intestine.2,3 Previous studies have shown the benefit of ezetimibe for LDL reduction and ASCVD prevention.4-7 The 2015 IMPROVE-IT study found the combination of simvastatin and ezetimibe resulted in a significantly lower risk of cardiovascular events than simvastatin monotherapy. IMPROVE-IT also reported a further clinical benefit when lower LDL targets (ie, < 55 mg/dL) are achieved, which aligns with the expert consensus pathway recommendations for a lower LDL goal for very high-risk patients.2,5
The RACING trial found that treatment with a moderate-intensity statin and ezetimibe was noninferior to treatment with a high-intensity statin for the primary outcome of occurrence of cardiovascular death, major cardiovascular events, or nonfatal stroke within 3 years. The combination of moderate-intensity statin and ezetimibe achieved lower LDL-C levels and lower incidence of drug intolerance compared to high intensity statin monotherapy.6 The SHARP-CKD study assessed major atherosclerotic events in patients with CKD who had no history of MI or coronary revascularization. The study found that lowering LDL-C with the combination of simvastatin plus ezetimibe safely reduces the risk of major atherosclerotic events in a wide range of patients with CKD.7
Lastly, the 2019 EWTOPIA 75 study found that ezetimibe noted a statistically significant reduction in the incidence of the composite of sudden cardiac death, MI, coronary revascularization, or stroke compared to placebo. Ezetimibe showed benefits in preventing ASCVD events independently of statin therapy.8 These clinical trials provided evidence for the efficacy of ezetimibe for secondary or primary prevention of ASCVD, patients with CKD, and patients who are not at their LDL goal despite maximally tolerated statin therapy.
Reductions in LDL levels with ezetimibe are reported to be 15% to 19% for monotherapy and 13% to 25% when used in combination with a statin.4 Given that the ACC now recommends lower LDL goals, patients may need additional lowering despite taking maximally tolerated statin therapy.2 Additionally, the package insert for ezetimibe reports increased area under the curve (AUC) values of ezetimibe and its metabolites in patients with severe renal disease. It is anticipated that ezetimibe may show an increased reduction of LDL and non-HDL, but there may also be an increased risk for muscle-related AEs.3
This quality-assurance quality improvement project investigated the use of ezetimibe in patients with CKD to determine whether there is further LDL and non-HDL reduction in this patient population. It sought to determine the LDL and non-HDL percentage reduction in patients with and without CKD at the Wilkes-Barre Veterans Affairs Medical Center (WBVAMC) and whether there is an increased risk for muscle-related AEs. Determining the percentage reduction of LDL and non-HDL within this population can help increase use of ezetimibe in patients not at their LDL or non-HDL goal or for those patients unable to tolerate statin therapy.
Methods
This single-center retrospective chart review investigated patients prescribed ezetimibe by a patient aligned care team (PACT) pharmacist at WBVAMC between September 1, 2021, and September 1, 2023. This project was determined to be nonresearch by the Veterans Integrated Service Network 4 multisite institutional review board. Patients were excluded from the review if they started taking ezetimibe outside of the prespecified time frame, if ezetimibe was initiated by a non-WBVAMC PACT pharmacist, or if there was no follow-up lipid panel obtained within 6 months of initiation of ezetimibe.
The primary outcomes were to determine the percentage mean change in LDL and non-HDL reduction and the incidence of muscle-related AEs after initiation of ezetimibe in patients without CKD. The secondary outcomes were to determine the percentage mean change in LDL and non-HDL levels and the incidence of muscle-related AEs after initiation of ezetimibe in patients with CKD. For this study, CKD was defined as a patient having an eGFR 15 to 60 ml/min/1.73 m2. Non-HDL is the combination of LDL-C and very LDL-C and represents all potentially atherogenic particles. The 2022 Expert Consensus Pathway included non-HDL goals in addition to LDL goals.2 Non-HDL cholesterol levels can be used for patients with elevated triglycerides where LDL levels may not be as accurate. To account for instances of elevated triglycerides, this study assessed changes in both LDL and non-HDL levels.
Data were collected from the US Department of Veterans Affairs (VA) Computerized Patient Record System (CPRS) and recorded in a spreadsheet. Collected data included age, sex, race, concomitant cholesterol-lowering medications (statin, proprotein convertase subtilisin/kexin type 9 [PCSK9] inhibitor, bempedoic acid, fish oil, niacin, bile acid sequestrants, and fibrates), baseline lipid panel, lipid panel within 6 months of ezetimibe initiation, and eGFR level. If the patient’s LDL or non-HDL levels worsened on the follow-up lipid panel, their baseline LDL and non-HDL levels were used to calculate the percentage reduction; thus, the percentage reduction would be 0%. This strategy was used in prior research, notably the IMPROVE-IT and SHARP-CKD trials.
Ezetimibe 5 mg once daily was used in this study based on a 2008 VA study that evaluated the use of ezetimibe 5 mg vs ezetimibe 10 mg and the percentage reduction of LDL with each dose. The study found no significant difference between the 5 mg and 10 mg dose.9 Most patients included in this study received the 5 mg dose.
Results
This retrospective chart review consisted of 173 patients, 137 (79.2%) without CKD and 36 (20.8%) with CKD at baseline. The mean age was 69.6 years, 155 (89.6%) patients were male, and 18 (10.4%) were female. There were 164 concomitant medications, including 115 patients prescribed a statin and 38 patients prescribed fish oil (Table 1).
Patients without CKD had mean reductions in LDL levels of 23.5% and non-HDL levels of 21.7% (Figure). Patients who had an increase in LDL and non-HDL levels were excluded to control for potential confounding factors such as dietary changes, discontinuation of ezetimibe therapy, nonadherence to ezetimibe, and medication changes that impacted follow-up laboratory tests such as discontinuation of a statin. Fifteen patients experienced an increase in LDL or non-HDL levels. After excluding these patients, those without CKD had a mean reduction in LDL levels of 28.0% and non-HDL levels of 25.5%. Nineteen (13.9%) patients without CKD experienced a muscle-related AE (Table 2). One patient discontinued ezetimibe and statin use following a Lyme disease diagnosis due to concerns over potential muscle-related AEs.
Patients with CKD had a mean reduction in LDL and non-HDL levels of 27.0% and 24.8%, respectively. Patients with an increase in LDL or non-HDL levels were also excluded to help control for potential confounding factors. After excluding 4 patients with increased LDL and non-HDL levels, the mean reduction in LDL and non-HDL levels was 30.5% and 27.5%, respectively. Five (13.9%) patients with CKD experienced muscle-related AEs thought to be due to ezetimibe. Other AEs (eg, urticaria, diarrhea, reflux, dizziness, headache, upset stomach) were reported that led to discontinuation of ezetimibe, but only muscle-related AEs were analyzed.
Discussion
This retrospective chart review found larger reductions in LDL and non-HDL levels for patients with CKD than reported in the literature.4 Based on the findings that indicate a greater cholesterol reduction with ezetimibe, the results suggest an underutilization of ezetimibe in clinical practice, which may be due to clinicians favoring statin therapy and overlooking ezetimibe as a viable option based on recommendation in earlier guidelines. The 2022 guidelines transitioned from a statin focus to a focus on LDL targets and goals.2
According to the ACC, there is evidence to support a direct relationship between LDL-C levels, atherosclerosis progression, and ASCVD event risk.2 Absolute LDL-C level reduction is directly associated with ASCVD risk reduction which supports the LDL hypothesis. There appears to be no specific LDL-C level below which benefit ceases.2 This suggests that lower LDL-C targets (< 55 mg/dL) should be used when clinically indicated. Many patients are either unable to reach their goal LDL levels with statin monotherapy or are unable to tolerate statin therapy at higher doses, which may require additional pharmacotherapy to reach goal LDL-C. The ACC expert consensus pathway recommends ezetimibe as the initial add-on treatment to statins.2 The RACING trial showed the benefit of adding ezetimibe to a moderate-intensity statin vs increasing to a high-intensity statin dose. This trial found patients had lower LDL levels and lower rates of intolerances, which further supports ezetimibe use.6
This quality improvement project assessed LDL and non-HDL level reduction in patients with CKD. As anticipated, there was greater reduction in LDL and non-HDL levels seen in patients with CKD. The SHARP-CKD trial also found reductions in LDL levels with ezetimibe in patients with CKD.7 Given the reduction in LDL and non-HDL levels with ezetimibe in patients with or without CKD, add-on therapy of ezetimibe should be recommended for patients who do not achieve their LDL goals with statin therapy or for patients who intolerant to statin therapy.
The ezetimibe package insert reports myalgias incidence to be < 5% in patients and research has shown up to a 20% incidence of muscle-related AEs with statin therapy.3,10 Based on the package information reporting increased AUC values of ezetimibe and its metabolites in patients with severe renal disease, it was anticipated there may be an increased risk of muscle-related AEs in patients with CKD.3 However, this study found the same incidence of muscle-related AEs in patients with and without CKD. Previous research on statin-intolerant patients found the incidence of muscle-related AEs with ezetimibe to be 23.0% and 28.8%.11,12 This increased incidence of muscle-related AEs may be the result of including patients with a history of statin intolerance. Collectively, data from clinical trials and this study indicate that patients with prior intolerances to statins appear to have a higher likelihood of developing a muscle-related AEs with ezetimibe.11,12 Clinicians and patients should be educated on the potential for these AEs and be aware that the likelihood may be greater if there is a history of statin intolerance. To our knowledge, this was the first study to evaluate muscle-related AEs with ezetimibe in patients with and without CKD.
Limitations
This retrospective chart review was performed over a prespecified period and only patients initiated on ezetimibe by a PACT pharmacist were included. This study did not assess the percentage of LDL reduction in patients on concomitant statins vs those who were not on concomitant statins. The study only included 173 patients. Additionally, the study was primarily composed of White men and may not be representative of other populations. In addition, veterans may not be representative of the general population given their high comorbidity burden and other exposures. Some reported muscle-related AEs associated with ezetimibe may be attributed to the nocebo effect.
Conclusions
The results of this retrospective chart review suggest there may be a larger mean reduction in LDL and non-HDL levels seen with ezetimibe therapy than reported within the literature. There was a larger mean reduction in LDL and non-HDL levels in patients with CKD than in patients without CKD. Additionally, there were the same rates of muscle-related AEs with ezetimibe therapy in patients with and without CKD. The rates of muscle-related AEs with ezetimibe therapy were higher than reported in the medication’s package insert, but lower than reported in literature that included statin-intolerant patients. These results indicate there may be a benefit to an increase in use of ezetimibe in clinical practice due to its increased effectiveness and safety in patients with and without CKD. Ultimately, this can help patients achieve their LDL goals as recommended by ACC clinical practice guidelines.
Grundy SM, Stone NJ, Bailey AL, et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol. 2019;73(24) e285-e350. doi:10.1016/j.jacc.2018.11.003
Writing Committee, Lloyd-Jones DM, Morris PB, et al. 2022 ACC expert consensus decision pathway on the role of nonstatin therapies for LDL-cholesterol lowering in the management of atherosclerotic cardiovascular disease risk: a report of the American College of Cardiology Solution Set Oversight Committee. J Am Coll Cardiol. 2022;80(14):1366-1418. doi:10.1016/j.jacc.2022.07.006
US Food and Drug Administration. Ezetimibe. 2007. Accessed April 1, 2025. https://www.accessdata.fda.gov/drugsatfda_docs/label/2008/021445s019lbl.pdf
Singh A, Cho LS. Nonstatin therapy to reduce low-density lipoprotein cholesterol and improve cardiovascular outcomes. Cleve Clin J Med. 2024;91(1):53-63. doi:10.3949/ccjm.91a.23058
Cannon CP, Blazing MA, Giugliano RP, et al. Ezetimibe added to statin therapy after acute coronary syndromes. N Engl J Med. 2015;372(25):2387-2397. doi:10.1056/NEJMoa1410489
Kim B, Hong S, Lee Y, et al. Long-term efficacy and safety of moderate-intensity statin with ezetimibe combination therapy versus high-intensity statin monotherapy in patients with atherosclerotic cardiovascular disease (RACING): a randomised, open-label, non-inferiority trial. Lancet. 2022;400(10349):380-390. doi:10.1016/S0140-6736(22)00916-3
Baigent C, Landray MJ, Reith C, et al. The effects of lowering LDL cholesterol with simvastatin plus ezetimibe in patients with chronic kidney disease (Study of Heart and Renal Protection): a randomised placebo-controlled trial. Lancet. 2011;377(9784):2181-2192. doi:10.1016/S0140-6736(11)60739-3
Ouchi Y, Sasaki J, Arai H, et al. Ezetimibe lipid-lowering trial on prevention of atherosclerotic cardiovascular disease in 75 or older (EWTOPIA 75): a randomized, controlled trial. Circulation. 2019;140:992-1003. doi:10.1161/CIRCULATIONAHA.118.039415
Baruch L, Gupta B, Lieberman-Blum SS, Agarwal S, Eng C. Ezetimibe 5 and 10 mg for lowering LDL-C: potential billion-dollar savings with improved tolerability. Am J Manag Care. 2008;14(10):637-641. https://www.ajmc.com/view/oct08-3644p637-641
Stroes ES, Thompson PD, Corsini A, et al. Statin-associated muscle symptoms: impact on statin therapy-European Atherosclerosis Society Consensus Panel Statement on Assessment, Aetiology and Management. Eur Heart J. 2015;36(17):1012-1022. doi:10.1093/eurheartj/ehv043
Stroes E, Colquhoun D, Sullivan D, et al. Anti-PCSK9 antibody effectively lowers cholesterol in patients with statin intolerance: the GAUSS-2 randomized, placebo-controlled phase 3 clinical trial of evolocumab. J Am Coll Cardiol. 2014;63(23):2541-2548. doi:10.1016/j.jacc.2014.03.019
Nissen SE, Stroes E, Dent-Acosta RE, et al. Efficacy and tolerability of evolocumab vs ezetimibe in patients with muscle-related statin intolerance: the GAUSS-3 randomized clinical trial. JAMA. 2016;315(15):1580-1590. doi:10.1001/jama.2016.3608
Grundy SM, Stone NJ, Bailey AL, et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol. 2019;73(24) e285-e350. doi:10.1016/j.jacc.2018.11.003
Writing Committee, Lloyd-Jones DM, Morris PB, et al. 2022 ACC expert consensus decision pathway on the role of nonstatin therapies for LDL-cholesterol lowering in the management of atherosclerotic cardiovascular disease risk: a report of the American College of Cardiology Solution Set Oversight Committee. J Am Coll Cardiol. 2022;80(14):1366-1418. doi:10.1016/j.jacc.2022.07.006
US Food and Drug Administration. Ezetimibe. 2007. Accessed April 1, 2025. https://www.accessdata.fda.gov/drugsatfda_docs/label/2008/021445s019lbl.pdf
Singh A, Cho LS. Nonstatin therapy to reduce low-density lipoprotein cholesterol and improve cardiovascular outcomes. Cleve Clin J Med. 2024;91(1):53-63. doi:10.3949/ccjm.91a.23058
Cannon CP, Blazing MA, Giugliano RP, et al. Ezetimibe added to statin therapy after acute coronary syndromes. N Engl J Med. 2015;372(25):2387-2397. doi:10.1056/NEJMoa1410489
Kim B, Hong S, Lee Y, et al. Long-term efficacy and safety of moderate-intensity statin with ezetimibe combination therapy versus high-intensity statin monotherapy in patients with atherosclerotic cardiovascular disease (RACING): a randomised, open-label, non-inferiority trial. Lancet. 2022;400(10349):380-390. doi:10.1016/S0140-6736(22)00916-3
Baigent C, Landray MJ, Reith C, et al. The effects of lowering LDL cholesterol with simvastatin plus ezetimibe in patients with chronic kidney disease (Study of Heart and Renal Protection): a randomised placebo-controlled trial. Lancet. 2011;377(9784):2181-2192. doi:10.1016/S0140-6736(11)60739-3
Ouchi Y, Sasaki J, Arai H, et al. Ezetimibe lipid-lowering trial on prevention of atherosclerotic cardiovascular disease in 75 or older (EWTOPIA 75): a randomized, controlled trial. Circulation. 2019;140:992-1003. doi:10.1161/CIRCULATIONAHA.118.039415
Baruch L, Gupta B, Lieberman-Blum SS, Agarwal S, Eng C. Ezetimibe 5 and 10 mg for lowering LDL-C: potential billion-dollar savings with improved tolerability. Am J Manag Care. 2008;14(10):637-641. https://www.ajmc.com/view/oct08-3644p637-641
Stroes ES, Thompson PD, Corsini A, et al. Statin-associated muscle symptoms: impact on statin therapy-European Atherosclerosis Society Consensus Panel Statement on Assessment, Aetiology and Management. Eur Heart J. 2015;36(17):1012-1022. doi:10.1093/eurheartj/ehv043
Stroes E, Colquhoun D, Sullivan D, et al. Anti-PCSK9 antibody effectively lowers cholesterol in patients with statin intolerance: the GAUSS-2 randomized, placebo-controlled phase 3 clinical trial of evolocumab. J Am Coll Cardiol. 2014;63(23):2541-2548. doi:10.1016/j.jacc.2014.03.019
Nissen SE, Stroes E, Dent-Acosta RE, et al. Efficacy and tolerability of evolocumab vs ezetimibe in patients with muscle-related statin intolerance: the GAUSS-3 randomized clinical trial. JAMA. 2016;315(15):1580-1590. doi:10.1001/jama.2016.3608
Efficacy of Anti-Obesity Medications in Adult and Older Adult Veteran Populations
Efficacy of Anti-Obesity Medications in Adult and Older Adult Veteran Populations
The impact of obesity in the United States is significant. Between August 2021 and August 2023, the prevalence of obesity (body mass index ≥ 30) in US adults was 40.3%.1 The prevalence of obesity in adults aged 40 to 59 years was 46.4%, higher than the prevalence in adults aged 20 to 39 years (35.5%) and those aged ≥ 60 years (38.9%).1 The excess annual medical costs associated with obesity in the US are estimated at nearly $173 billion.2
The first-line treatment for obesity is lifestyle modifications, including a healthy diet and exercise. When lifestyle modifications are not enough to achieve weight-loss goals, bariatric surgery and anti-obesity medications (AOMs) are often considered. Five medications were approved for the long-term tretament of obesity by the US Food and Drug Administration (FDA) between 2021 and 2023, when this study was conducted: semaglutide (Wegovy), liraglutide (Saxenda), phentermine and topiramate, naltrexone and bupropion, and orlistat. The clinically meaningful (and commonly accepted) weight-loss target for these medications is ≥ 5% from baseline by week 12 of the maximally tolerated dose of therapy. A 5% weight loss has been shown to be clinically significant in improving cardiometabolic risk factors.3,4 These medications are intended to be used as an adjunct to healthy diet and exercise. Of note, semaglutide and liraglutide carry brand names, which are associated with different dosing for the treatment of type 2 diabetes mellitus (T2DM).
All 5 FDA-approved AOMs were available at the Veterans Affairs Sioux Falls Health Care System (VASFHCS) for the treatment of obesity at the time of the study. To qualify for an AOM, a veteran at VASFHCS must first work with a dietitian or be enrolled in the MOVE! clinic to participate in the weight management program, which focuses on dietary, exercise, and behavioral changes. At VASFHCS, AOMs are prescribed by primary care practitioners, clinical pharmacy providers, and advanced practitioners within the MOVE! program.
Ample data exist for the efficacy of AOMs. However, no published research has reported on AOM efficacy by age group (Appendix).5-11 While most of the AOM clinical trials included older adults, the average age of participants was typically between 40 and 50 years. It is well-known that pharmacokinetic and pharmacodynamic changes occur as age increases. Renal and hepatic clearance is reduced while the volume distribution and sensitivities to some medications may increase. 12 Although this study did not focus on specific pharmacokinetic and pharmacodynamic changes with respect to AOM, it is important to recognize that this may play a role in the efficacy and safety of AOMs in older adults.

Methods
This retrospective single-center chart review was performed using the VASFHCS Computerized Patient Record System to compare the efficacy of AOMs in older adults (aged ≥ 65 years) vs adults (aged < 65 years). The primary endpoint was the percent change in body weight from baseline to 6 and 12 months after initiation of AOM therapy in the older adult vs adult population. Secondary endpoints included changes in low-density lipoprotein (LDL), hemoglobin A1c (HbA1c), and blood pressure (BP) from baseline compared to 12 months on AOM therapy. HbA1c was assessed in patients with T2DM or prediabetes at the time of AOM initiation. Two safety endpoints were also explored to determine the incidence of medication adverse events (AEs) and subsequent discontinuation of AOM. A subset analysis was performed to determine whether there was a difference in percent change in body weight between patients in 3 age groups: 18 to 40 years, 41 to 64 years, and ≥ 65 years.
The study population included patients who were prescribed an AOM between January 1, 2021, and June 30, 2023. Patients were excluded if they did not continue AOM therapy for ≥ 6 months after initiation or if they underwent gastric bypass surgery while undergoing AOM therapy. Patients taking semaglutide (Ozempic) or liraglutide (Victoza) for both T2DM and weight loss who were eventually switched to the weight loss formulations (Wegovy or Saxenda) were included. Patients who switched between semaglutide and liraglutide for weight loss were also included. Those taking semaglutide or liraglutide solely for T2DM treatment were excluded because they are dosed differently.
Collected data included age, gender, race, weight (baseline, 6 and 12 months after initiation of AOM), metabolic laboratory values/vital signs (HbA1c, LDL, and BP at baseline and 12 months after initiation of AOM), diagnosis of T2DM or prediabetes, reported AEs associated with AOM therapy, and date of AOM initiation and discontinuation (if applicable). Baseline values were defined at the time of medication initiation or values documented within 6 months prior to medication initiation if true baseline data were not reported. If values were not recorded at months 6 and 12 after AOM initiation, values documented closest to those targets were used. Weights were used for baseline, 6-, and 12-month data unless they were unavailable due to use of virtual care modalities. In these cases, patient-reported weights were used. Patients were included in the 6-month data, but not the 12-month data, if they were taking AOMs for > 6 months but not for 12 months. If patients had been on multiple AOMs, baseline data were recorded at the start of the first medication that was used for 6 months or longer. Twelve-month data were recorded after subsequent medication change. Twelve-month metabolic laboratory values/vital signs were recorded for patients included in the study even if they did not complete ≥ 12 months of AOM therapy.
Statistical Analysis
Data from patients who were prescribed an AOM from January 2021 to June 2023 and who remained on the medication for ≥ 6 months were analyzed. Baseline characteristics were analyzed using descriptive statistics. The primary and secondary endpoints were evaluated using the t test. The safety endpoints were analyzed using descriptive statistics. An analysis of variance test was used for the subset analysis. Results with P < .05 were statistically significant.
Results
A total of 144 participants were included in this study, 116 in the adult group (aged < 65 years) and 28 in the older adult group (aged ≥ 65 years). Sixty-seven patients were excluded due to prespecified inclusion and exclusion criteria.
Other than the predetermined mean age differences (48 years vs 71 years), there were multiple differences in patient baseline characteristics. When comparing older adults and adults, average weight (283 lb vs 269 lb) and White race (89% vs 87%) were slightly higher in the older adult group. Also, a higher prevalence of T2DM (54% and 18%) and a lower prevalence of prediabetes (21% and 33%) was noted in the older adult group. HbA1c and BP were similar between both groups at baseline, while LDL was slightly lower in the older adult group (Table 1).

Patients in the adult group lost a mean 7.0% and 8.7% of body weight at 6 and 12 months, respectively, while the older adult group lost 5.0% and 6.6% body weight at 6 and 12 months, respectively. The difference in percent change in body weight was not statistically different at 6 (P = .08) or 12 (P = .26) months between patients in the adult group vs the older adult group or in the specific age groups (18-40 years, 41-64 years, ≥ 65 years) at 6 months (P = .24) or 12 months (P = .53) (Figure).

At 12 months, the difference between the adult group vs the older adult group was not statistically significant for HbA1c in patients with T2DM or prediabetes (P = .73), LDL (P = .95), systolic BP (P = .58), or diastolic BP (P = .51) (Table 2).

For the safety endpoint, the incidence of AEs was found to be different between groups. There were more reported AEs (61.2% vs 39.3%) and a greater increase in therapy discontinuation due to AEs (6.0% vs 0%) in the adult group compared to the older adult group (Table 3).

Discussion
Patients taking AOMs revealed no statistically significant difference in percent change in body weight at 6 or 12 months between adults aged < 65 years and older adults aged ≥ 65 years. The subset analysis also showed no statistically significant difference in change in percent body weight between more narrowly defined age groups of 18 to 40 years, 41 to 64 years, and ≥ 65 years. This suggests that AOM may have similar efficacy for weight loss in all ages of adults.
Secondary endpoint findings showed no statistically significant difference in HbA1c (in patients with T2DM or prediabetes), LDL, or BP at 12 months between the 2 groups. Although this study did not differentiate secondary outcomes based on the individual AOM, the change in HbA1c in both groups was expected, given that 70% of the patients included in this study were taking a glucagon-like peptide-1 agonist (liraglutide and semaglutide) at some point during the study. It’s also worth noting that secondary endpoints were collected for patients who discontinued the AOM between 6 and 12 months. Therefore, the patients’ HbA1c, LDL, and BP may not have accurately reflected the change that could have been expected if they had continued AOM therapy beyond the 12-month period.
Due to the different mechanisms and range in efficacy that AOMs have in regard to weight loss, changes in all outcomes, including weight, HbA1c, LDL, and BP were expected to vary as patients were included even after switching AOM (collection of data started after ≥ 6 months on a single AOM). Switching of AOM after the first 6 months of therapy was recorded in 25% of the patients in the ≥ 65 years group and 330% of the patients in the < 65 years group.
The incidence of AEs and subsequent discontinuation of AOMs in this study was higher in the adult group. This study excluded patients who did not continue taking an AOM for at least 6 months. As a result, the incidence of AEs between the 2 groups within the first 6 months of AOM therapy remains unknown. It is possible that during the first 6 months of therapy, patients aged < 65 years were more willing to tolerate or had fewer severe AEs compared with the older adult group. It’s also possible that the smaller number of patients in the older adult group was due to increased AEs that led them to discontinue early (before completion of 6 months of therapy) and/or prescriber discomfort in using AOMs in the older adult population. In addition, because the specific medication(s) taken by patients in each group were not detailed, it is unknown whether the adult group was taking AOMs associated with a greater number of AEs.
Limitations
This was a retrospective study with a relatively small sample size. A larger sample size may have shown more precise differences between age groups and may be more representative of the general population. Additionally, data were reliant on appropriate documentation, and adherence to AOM therapy was not assessed due to the retrospective nature of this study. At times, the study relied on patient reported data points, such as weight, if a clinic weight was not available. Also, this study did not account for many potential confounding factors such as other medications taken by the patient, which can affect outcomes including weight, HbA1c, LDL, blood pressure, and AEs.
Conclusions
This retrospective study of patients taking AOMs showed no statistically significant difference in weight loss at 6 or 12 months between adults aged < 65 years and older adults aged ≥ 65 years. A subset analysis found no statistically significant difference in change in body weight between specific age groups (18-40 years, 41-64 years, and ≥ 65 years). There was also no statistically significant difference in secondary outcomes, including change in HbA1c (in patients with T2DM or prediabetes), LDL or BP between age groups. The safety endpoints showed a higher incidence of medication AEs in the adult group, with more of these adults discontinuing therapy due to AEs. This study indicates that AOM may have similar outcomes for weight loss and metabolic laboratory values/vital sign changes between adults and older adults. Also, our findings suggest that patients aged < 65 years may experience more AEs than patients aged ≥ 65 years after ≥ 6 months of AOM therapy. Larger studies are needed to further evaluate these age-specific findings.
- Emmerich SD, Fryar CD, Stierman B, Ogden CL. Obesity and severe obesity prevalence in adults: United States, August 2021-August 2023. NCHS Data Brief No. 508. National Center for Health Statistics; 2024. Accessed December 11, 2024. https://www.cdc.gov/nchs/products/databriefs/db508.htm
- Ward ZJ, Bleich SN, Long MW, Gortmaker SL. Association of body mass index with health care expenditures in the United States by age and sex. PLoS One. 2021;16(3):e0247307. doi:10.1371/journal.pone.0247307
- Horn DB, Almandoz JP, Look M. What is clinically relevant weight loss for your patients and how can it be achieved? A narrative review. Postgrad Med. 2022;134(4):359-375. doi:10.1080/00325481.2022.2051366
- American Diabetes Association (ADA). Standards of care in diabetes–2023. Diabetes Care. 2023;46(suppl 1):S128- S2139. doi:10.2337/dc23-S008
- Wilding JPH, Batterham RL, Calanna S, et al. Onceweekly semaglutide in adults with overweight or obesity. N Engl J Med. 2021;384(11):989-1002. doi:10.1056/NEJMoa2032183
- Pi-Sunyer X, Astrup A, Fujioka K, et al. A randomized, controlled trial of 3.0 mg of liraglutide in weight management. N Engl J Med. 2015;373(1):11-22. doi:10.1056/NEJMoa1411892
- Allison DB, Gadde KM, Garvey WT, et al. Controlled-release phentermine/topiramate in severely obese adults: a randomized controlled trial (EQUIP). Obesity (Silver Spring). 2012;20(2):330-342. doi:10.1038/oby.2011.330
- Gadde KM, Allison DB, Ryan DH, et al. Effects of low-dose, controlled-release, phentermine plus topiramate combination on weight and associated comorbidities in overweight and obese adults (CONQUER): a randomised, placebo-controlled, phase 3 trial. Lancet. 2011;377(9774):1341-1352. doi:10.1016/S0140-6736(11)60205-5
- Garvey WT, Ryan DH, Look M, et al. Two-year sustained weight loss and metabolic benefits with controlled-release phentermine/topiramate in obese and overweight adults (SEQUEL): a randomized, placebo-controlled, phase 3 extension study. Am J Clin Nutr. 2012;95(2):297-308. doi:10.3945/ajcn.111.024927
- Greenway FL, Fujioka K, Plodkowski RA, et al. Effect of naltrexone plus bupropion on weight loss in overweight and obese adults (COR-I): a multicentre, randomised, double-blind, placebo-controlled, phase 3 trial. Lancet. 2010;376(9741):595-605. doi:10.1016/S0140-6736(10)60888-4
- Sjöström L, Rissanen A, Andersen T, et al. Randomised placebo-controlled trial of orlistat for weight loss and prevention of weight regain in obese patients. European Multicentre Orlistat Study Group. Lancet. 1998;352(9123):167-172. doi:10.1016s0140-6736(97)11509-4
- Mangoni AA, Jackson SHD. Age-related changes in pharmacokinetics and pharmacodynamics: basic principles and practical applications. Br J Clin Pharmacol. 2004;57(1):6-14. doi:10.1046/j.1365-2125.2003.02007.x
The impact of obesity in the United States is significant. Between August 2021 and August 2023, the prevalence of obesity (body mass index ≥ 30) in US adults was 40.3%.1 The prevalence of obesity in adults aged 40 to 59 years was 46.4%, higher than the prevalence in adults aged 20 to 39 years (35.5%) and those aged ≥ 60 years (38.9%).1 The excess annual medical costs associated with obesity in the US are estimated at nearly $173 billion.2
The first-line treatment for obesity is lifestyle modifications, including a healthy diet and exercise. When lifestyle modifications are not enough to achieve weight-loss goals, bariatric surgery and anti-obesity medications (AOMs) are often considered. Five medications were approved for the long-term tretament of obesity by the US Food and Drug Administration (FDA) between 2021 and 2023, when this study was conducted: semaglutide (Wegovy), liraglutide (Saxenda), phentermine and topiramate, naltrexone and bupropion, and orlistat. The clinically meaningful (and commonly accepted) weight-loss target for these medications is ≥ 5% from baseline by week 12 of the maximally tolerated dose of therapy. A 5% weight loss has been shown to be clinically significant in improving cardiometabolic risk factors.3,4 These medications are intended to be used as an adjunct to healthy diet and exercise. Of note, semaglutide and liraglutide carry brand names, which are associated with different dosing for the treatment of type 2 diabetes mellitus (T2DM).
All 5 FDA-approved AOMs were available at the Veterans Affairs Sioux Falls Health Care System (VASFHCS) for the treatment of obesity at the time of the study. To qualify for an AOM, a veteran at VASFHCS must first work with a dietitian or be enrolled in the MOVE! clinic to participate in the weight management program, which focuses on dietary, exercise, and behavioral changes. At VASFHCS, AOMs are prescribed by primary care practitioners, clinical pharmacy providers, and advanced practitioners within the MOVE! program.
Ample data exist for the efficacy of AOMs. However, no published research has reported on AOM efficacy by age group (Appendix).5-11 While most of the AOM clinical trials included older adults, the average age of participants was typically between 40 and 50 years. It is well-known that pharmacokinetic and pharmacodynamic changes occur as age increases. Renal and hepatic clearance is reduced while the volume distribution and sensitivities to some medications may increase. 12 Although this study did not focus on specific pharmacokinetic and pharmacodynamic changes with respect to AOM, it is important to recognize that this may play a role in the efficacy and safety of AOMs in older adults.

Methods
This retrospective single-center chart review was performed using the VASFHCS Computerized Patient Record System to compare the efficacy of AOMs in older adults (aged ≥ 65 years) vs adults (aged < 65 years). The primary endpoint was the percent change in body weight from baseline to 6 and 12 months after initiation of AOM therapy in the older adult vs adult population. Secondary endpoints included changes in low-density lipoprotein (LDL), hemoglobin A1c (HbA1c), and blood pressure (BP) from baseline compared to 12 months on AOM therapy. HbA1c was assessed in patients with T2DM or prediabetes at the time of AOM initiation. Two safety endpoints were also explored to determine the incidence of medication adverse events (AEs) and subsequent discontinuation of AOM. A subset analysis was performed to determine whether there was a difference in percent change in body weight between patients in 3 age groups: 18 to 40 years, 41 to 64 years, and ≥ 65 years.
The study population included patients who were prescribed an AOM between January 1, 2021, and June 30, 2023. Patients were excluded if they did not continue AOM therapy for ≥ 6 months after initiation or if they underwent gastric bypass surgery while undergoing AOM therapy. Patients taking semaglutide (Ozempic) or liraglutide (Victoza) for both T2DM and weight loss who were eventually switched to the weight loss formulations (Wegovy or Saxenda) were included. Patients who switched between semaglutide and liraglutide for weight loss were also included. Those taking semaglutide or liraglutide solely for T2DM treatment were excluded because they are dosed differently.
Collected data included age, gender, race, weight (baseline, 6 and 12 months after initiation of AOM), metabolic laboratory values/vital signs (HbA1c, LDL, and BP at baseline and 12 months after initiation of AOM), diagnosis of T2DM or prediabetes, reported AEs associated with AOM therapy, and date of AOM initiation and discontinuation (if applicable). Baseline values were defined at the time of medication initiation or values documented within 6 months prior to medication initiation if true baseline data were not reported. If values were not recorded at months 6 and 12 after AOM initiation, values documented closest to those targets were used. Weights were used for baseline, 6-, and 12-month data unless they were unavailable due to use of virtual care modalities. In these cases, patient-reported weights were used. Patients were included in the 6-month data, but not the 12-month data, if they were taking AOMs for > 6 months but not for 12 months. If patients had been on multiple AOMs, baseline data were recorded at the start of the first medication that was used for 6 months or longer. Twelve-month data were recorded after subsequent medication change. Twelve-month metabolic laboratory values/vital signs were recorded for patients included in the study even if they did not complete ≥ 12 months of AOM therapy.
Statistical Analysis
Data from patients who were prescribed an AOM from January 2021 to June 2023 and who remained on the medication for ≥ 6 months were analyzed. Baseline characteristics were analyzed using descriptive statistics. The primary and secondary endpoints were evaluated using the t test. The safety endpoints were analyzed using descriptive statistics. An analysis of variance test was used for the subset analysis. Results with P < .05 were statistically significant.
Results
A total of 144 participants were included in this study, 116 in the adult group (aged < 65 years) and 28 in the older adult group (aged ≥ 65 years). Sixty-seven patients were excluded due to prespecified inclusion and exclusion criteria.
Other than the predetermined mean age differences (48 years vs 71 years), there were multiple differences in patient baseline characteristics. When comparing older adults and adults, average weight (283 lb vs 269 lb) and White race (89% vs 87%) were slightly higher in the older adult group. Also, a higher prevalence of T2DM (54% and 18%) and a lower prevalence of prediabetes (21% and 33%) was noted in the older adult group. HbA1c and BP were similar between both groups at baseline, while LDL was slightly lower in the older adult group (Table 1).

Patients in the adult group lost a mean 7.0% and 8.7% of body weight at 6 and 12 months, respectively, while the older adult group lost 5.0% and 6.6% body weight at 6 and 12 months, respectively. The difference in percent change in body weight was not statistically different at 6 (P = .08) or 12 (P = .26) months between patients in the adult group vs the older adult group or in the specific age groups (18-40 years, 41-64 years, ≥ 65 years) at 6 months (P = .24) or 12 months (P = .53) (Figure).

At 12 months, the difference between the adult group vs the older adult group was not statistically significant for HbA1c in patients with T2DM or prediabetes (P = .73), LDL (P = .95), systolic BP (P = .58), or diastolic BP (P = .51) (Table 2).

For the safety endpoint, the incidence of AEs was found to be different between groups. There were more reported AEs (61.2% vs 39.3%) and a greater increase in therapy discontinuation due to AEs (6.0% vs 0%) in the adult group compared to the older adult group (Table 3).

Discussion
Patients taking AOMs revealed no statistically significant difference in percent change in body weight at 6 or 12 months between adults aged < 65 years and older adults aged ≥ 65 years. The subset analysis also showed no statistically significant difference in change in percent body weight between more narrowly defined age groups of 18 to 40 years, 41 to 64 years, and ≥ 65 years. This suggests that AOM may have similar efficacy for weight loss in all ages of adults.
Secondary endpoint findings showed no statistically significant difference in HbA1c (in patients with T2DM or prediabetes), LDL, or BP at 12 months between the 2 groups. Although this study did not differentiate secondary outcomes based on the individual AOM, the change in HbA1c in both groups was expected, given that 70% of the patients included in this study were taking a glucagon-like peptide-1 agonist (liraglutide and semaglutide) at some point during the study. It’s also worth noting that secondary endpoints were collected for patients who discontinued the AOM between 6 and 12 months. Therefore, the patients’ HbA1c, LDL, and BP may not have accurately reflected the change that could have been expected if they had continued AOM therapy beyond the 12-month period.
Due to the different mechanisms and range in efficacy that AOMs have in regard to weight loss, changes in all outcomes, including weight, HbA1c, LDL, and BP were expected to vary as patients were included even after switching AOM (collection of data started after ≥ 6 months on a single AOM). Switching of AOM after the first 6 months of therapy was recorded in 25% of the patients in the ≥ 65 years group and 330% of the patients in the < 65 years group.
The incidence of AEs and subsequent discontinuation of AOMs in this study was higher in the adult group. This study excluded patients who did not continue taking an AOM for at least 6 months. As a result, the incidence of AEs between the 2 groups within the first 6 months of AOM therapy remains unknown. It is possible that during the first 6 months of therapy, patients aged < 65 years were more willing to tolerate or had fewer severe AEs compared with the older adult group. It’s also possible that the smaller number of patients in the older adult group was due to increased AEs that led them to discontinue early (before completion of 6 months of therapy) and/or prescriber discomfort in using AOMs in the older adult population. In addition, because the specific medication(s) taken by patients in each group were not detailed, it is unknown whether the adult group was taking AOMs associated with a greater number of AEs.
Limitations
This was a retrospective study with a relatively small sample size. A larger sample size may have shown more precise differences between age groups and may be more representative of the general population. Additionally, data were reliant on appropriate documentation, and adherence to AOM therapy was not assessed due to the retrospective nature of this study. At times, the study relied on patient reported data points, such as weight, if a clinic weight was not available. Also, this study did not account for many potential confounding factors such as other medications taken by the patient, which can affect outcomes including weight, HbA1c, LDL, blood pressure, and AEs.
Conclusions
This retrospective study of patients taking AOMs showed no statistically significant difference in weight loss at 6 or 12 months between adults aged < 65 years and older adults aged ≥ 65 years. A subset analysis found no statistically significant difference in change in body weight between specific age groups (18-40 years, 41-64 years, and ≥ 65 years). There was also no statistically significant difference in secondary outcomes, including change in HbA1c (in patients with T2DM or prediabetes), LDL or BP between age groups. The safety endpoints showed a higher incidence of medication AEs in the adult group, with more of these adults discontinuing therapy due to AEs. This study indicates that AOM may have similar outcomes for weight loss and metabolic laboratory values/vital sign changes between adults and older adults. Also, our findings suggest that patients aged < 65 years may experience more AEs than patients aged ≥ 65 years after ≥ 6 months of AOM therapy. Larger studies are needed to further evaluate these age-specific findings.
The impact of obesity in the United States is significant. Between August 2021 and August 2023, the prevalence of obesity (body mass index ≥ 30) in US adults was 40.3%.1 The prevalence of obesity in adults aged 40 to 59 years was 46.4%, higher than the prevalence in adults aged 20 to 39 years (35.5%) and those aged ≥ 60 years (38.9%).1 The excess annual medical costs associated with obesity in the US are estimated at nearly $173 billion.2
The first-line treatment for obesity is lifestyle modifications, including a healthy diet and exercise. When lifestyle modifications are not enough to achieve weight-loss goals, bariatric surgery and anti-obesity medications (AOMs) are often considered. Five medications were approved for the long-term tretament of obesity by the US Food and Drug Administration (FDA) between 2021 and 2023, when this study was conducted: semaglutide (Wegovy), liraglutide (Saxenda), phentermine and topiramate, naltrexone and bupropion, and orlistat. The clinically meaningful (and commonly accepted) weight-loss target for these medications is ≥ 5% from baseline by week 12 of the maximally tolerated dose of therapy. A 5% weight loss has been shown to be clinically significant in improving cardiometabolic risk factors.3,4 These medications are intended to be used as an adjunct to healthy diet and exercise. Of note, semaglutide and liraglutide carry brand names, which are associated with different dosing for the treatment of type 2 diabetes mellitus (T2DM).
All 5 FDA-approved AOMs were available at the Veterans Affairs Sioux Falls Health Care System (VASFHCS) for the treatment of obesity at the time of the study. To qualify for an AOM, a veteran at VASFHCS must first work with a dietitian or be enrolled in the MOVE! clinic to participate in the weight management program, which focuses on dietary, exercise, and behavioral changes. At VASFHCS, AOMs are prescribed by primary care practitioners, clinical pharmacy providers, and advanced practitioners within the MOVE! program.
Ample data exist for the efficacy of AOMs. However, no published research has reported on AOM efficacy by age group (Appendix).5-11 While most of the AOM clinical trials included older adults, the average age of participants was typically between 40 and 50 years. It is well-known that pharmacokinetic and pharmacodynamic changes occur as age increases. Renal and hepatic clearance is reduced while the volume distribution and sensitivities to some medications may increase. 12 Although this study did not focus on specific pharmacokinetic and pharmacodynamic changes with respect to AOM, it is important to recognize that this may play a role in the efficacy and safety of AOMs in older adults.

Methods
This retrospective single-center chart review was performed using the VASFHCS Computerized Patient Record System to compare the efficacy of AOMs in older adults (aged ≥ 65 years) vs adults (aged < 65 years). The primary endpoint was the percent change in body weight from baseline to 6 and 12 months after initiation of AOM therapy in the older adult vs adult population. Secondary endpoints included changes in low-density lipoprotein (LDL), hemoglobin A1c (HbA1c), and blood pressure (BP) from baseline compared to 12 months on AOM therapy. HbA1c was assessed in patients with T2DM or prediabetes at the time of AOM initiation. Two safety endpoints were also explored to determine the incidence of medication adverse events (AEs) and subsequent discontinuation of AOM. A subset analysis was performed to determine whether there was a difference in percent change in body weight between patients in 3 age groups: 18 to 40 years, 41 to 64 years, and ≥ 65 years.
The study population included patients who were prescribed an AOM between January 1, 2021, and June 30, 2023. Patients were excluded if they did not continue AOM therapy for ≥ 6 months after initiation or if they underwent gastric bypass surgery while undergoing AOM therapy. Patients taking semaglutide (Ozempic) or liraglutide (Victoza) for both T2DM and weight loss who were eventually switched to the weight loss formulations (Wegovy or Saxenda) were included. Patients who switched between semaglutide and liraglutide for weight loss were also included. Those taking semaglutide or liraglutide solely for T2DM treatment were excluded because they are dosed differently.
Collected data included age, gender, race, weight (baseline, 6 and 12 months after initiation of AOM), metabolic laboratory values/vital signs (HbA1c, LDL, and BP at baseline and 12 months after initiation of AOM), diagnosis of T2DM or prediabetes, reported AEs associated with AOM therapy, and date of AOM initiation and discontinuation (if applicable). Baseline values were defined at the time of medication initiation or values documented within 6 months prior to medication initiation if true baseline data were not reported. If values were not recorded at months 6 and 12 after AOM initiation, values documented closest to those targets were used. Weights were used for baseline, 6-, and 12-month data unless they were unavailable due to use of virtual care modalities. In these cases, patient-reported weights were used. Patients were included in the 6-month data, but not the 12-month data, if they were taking AOMs for > 6 months but not for 12 months. If patients had been on multiple AOMs, baseline data were recorded at the start of the first medication that was used for 6 months or longer. Twelve-month data were recorded after subsequent medication change. Twelve-month metabolic laboratory values/vital signs were recorded for patients included in the study even if they did not complete ≥ 12 months of AOM therapy.
Statistical Analysis
Data from patients who were prescribed an AOM from January 2021 to June 2023 and who remained on the medication for ≥ 6 months were analyzed. Baseline characteristics were analyzed using descriptive statistics. The primary and secondary endpoints were evaluated using the t test. The safety endpoints were analyzed using descriptive statistics. An analysis of variance test was used for the subset analysis. Results with P < .05 were statistically significant.
Results
A total of 144 participants were included in this study, 116 in the adult group (aged < 65 years) and 28 in the older adult group (aged ≥ 65 years). Sixty-seven patients were excluded due to prespecified inclusion and exclusion criteria.
Other than the predetermined mean age differences (48 years vs 71 years), there were multiple differences in patient baseline characteristics. When comparing older adults and adults, average weight (283 lb vs 269 lb) and White race (89% vs 87%) were slightly higher in the older adult group. Also, a higher prevalence of T2DM (54% and 18%) and a lower prevalence of prediabetes (21% and 33%) was noted in the older adult group. HbA1c and BP were similar between both groups at baseline, while LDL was slightly lower in the older adult group (Table 1).

Patients in the adult group lost a mean 7.0% and 8.7% of body weight at 6 and 12 months, respectively, while the older adult group lost 5.0% and 6.6% body weight at 6 and 12 months, respectively. The difference in percent change in body weight was not statistically different at 6 (P = .08) or 12 (P = .26) months between patients in the adult group vs the older adult group or in the specific age groups (18-40 years, 41-64 years, ≥ 65 years) at 6 months (P = .24) or 12 months (P = .53) (Figure).

At 12 months, the difference between the adult group vs the older adult group was not statistically significant for HbA1c in patients with T2DM or prediabetes (P = .73), LDL (P = .95), systolic BP (P = .58), or diastolic BP (P = .51) (Table 2).

For the safety endpoint, the incidence of AEs was found to be different between groups. There were more reported AEs (61.2% vs 39.3%) and a greater increase in therapy discontinuation due to AEs (6.0% vs 0%) in the adult group compared to the older adult group (Table 3).

Discussion
Patients taking AOMs revealed no statistically significant difference in percent change in body weight at 6 or 12 months between adults aged < 65 years and older adults aged ≥ 65 years. The subset analysis also showed no statistically significant difference in change in percent body weight between more narrowly defined age groups of 18 to 40 years, 41 to 64 years, and ≥ 65 years. This suggests that AOM may have similar efficacy for weight loss in all ages of adults.
Secondary endpoint findings showed no statistically significant difference in HbA1c (in patients with T2DM or prediabetes), LDL, or BP at 12 months between the 2 groups. Although this study did not differentiate secondary outcomes based on the individual AOM, the change in HbA1c in both groups was expected, given that 70% of the patients included in this study were taking a glucagon-like peptide-1 agonist (liraglutide and semaglutide) at some point during the study. It’s also worth noting that secondary endpoints were collected for patients who discontinued the AOM between 6 and 12 months. Therefore, the patients’ HbA1c, LDL, and BP may not have accurately reflected the change that could have been expected if they had continued AOM therapy beyond the 12-month period.
Due to the different mechanisms and range in efficacy that AOMs have in regard to weight loss, changes in all outcomes, including weight, HbA1c, LDL, and BP were expected to vary as patients were included even after switching AOM (collection of data started after ≥ 6 months on a single AOM). Switching of AOM after the first 6 months of therapy was recorded in 25% of the patients in the ≥ 65 years group and 330% of the patients in the < 65 years group.
The incidence of AEs and subsequent discontinuation of AOMs in this study was higher in the adult group. This study excluded patients who did not continue taking an AOM for at least 6 months. As a result, the incidence of AEs between the 2 groups within the first 6 months of AOM therapy remains unknown. It is possible that during the first 6 months of therapy, patients aged < 65 years were more willing to tolerate or had fewer severe AEs compared with the older adult group. It’s also possible that the smaller number of patients in the older adult group was due to increased AEs that led them to discontinue early (before completion of 6 months of therapy) and/or prescriber discomfort in using AOMs in the older adult population. In addition, because the specific medication(s) taken by patients in each group were not detailed, it is unknown whether the adult group was taking AOMs associated with a greater number of AEs.
Limitations
This was a retrospective study with a relatively small sample size. A larger sample size may have shown more precise differences between age groups and may be more representative of the general population. Additionally, data were reliant on appropriate documentation, and adherence to AOM therapy was not assessed due to the retrospective nature of this study. At times, the study relied on patient reported data points, such as weight, if a clinic weight was not available. Also, this study did not account for many potential confounding factors such as other medications taken by the patient, which can affect outcomes including weight, HbA1c, LDL, blood pressure, and AEs.
Conclusions
This retrospective study of patients taking AOMs showed no statistically significant difference in weight loss at 6 or 12 months between adults aged < 65 years and older adults aged ≥ 65 years. A subset analysis found no statistically significant difference in change in body weight between specific age groups (18-40 years, 41-64 years, and ≥ 65 years). There was also no statistically significant difference in secondary outcomes, including change in HbA1c (in patients with T2DM or prediabetes), LDL or BP between age groups. The safety endpoints showed a higher incidence of medication AEs in the adult group, with more of these adults discontinuing therapy due to AEs. This study indicates that AOM may have similar outcomes for weight loss and metabolic laboratory values/vital sign changes between adults and older adults. Also, our findings suggest that patients aged < 65 years may experience more AEs than patients aged ≥ 65 years after ≥ 6 months of AOM therapy. Larger studies are needed to further evaluate these age-specific findings.
- Emmerich SD, Fryar CD, Stierman B, Ogden CL. Obesity and severe obesity prevalence in adults: United States, August 2021-August 2023. NCHS Data Brief No. 508. National Center for Health Statistics; 2024. Accessed December 11, 2024. https://www.cdc.gov/nchs/products/databriefs/db508.htm
- Ward ZJ, Bleich SN, Long MW, Gortmaker SL. Association of body mass index with health care expenditures in the United States by age and sex. PLoS One. 2021;16(3):e0247307. doi:10.1371/journal.pone.0247307
- Horn DB, Almandoz JP, Look M. What is clinically relevant weight loss for your patients and how can it be achieved? A narrative review. Postgrad Med. 2022;134(4):359-375. doi:10.1080/00325481.2022.2051366
- American Diabetes Association (ADA). Standards of care in diabetes–2023. Diabetes Care. 2023;46(suppl 1):S128- S2139. doi:10.2337/dc23-S008
- Wilding JPH, Batterham RL, Calanna S, et al. Onceweekly semaglutide in adults with overweight or obesity. N Engl J Med. 2021;384(11):989-1002. doi:10.1056/NEJMoa2032183
- Pi-Sunyer X, Astrup A, Fujioka K, et al. A randomized, controlled trial of 3.0 mg of liraglutide in weight management. N Engl J Med. 2015;373(1):11-22. doi:10.1056/NEJMoa1411892
- Allison DB, Gadde KM, Garvey WT, et al. Controlled-release phentermine/topiramate in severely obese adults: a randomized controlled trial (EQUIP). Obesity (Silver Spring). 2012;20(2):330-342. doi:10.1038/oby.2011.330
- Gadde KM, Allison DB, Ryan DH, et al. Effects of low-dose, controlled-release, phentermine plus topiramate combination on weight and associated comorbidities in overweight and obese adults (CONQUER): a randomised, placebo-controlled, phase 3 trial. Lancet. 2011;377(9774):1341-1352. doi:10.1016/S0140-6736(11)60205-5
- Garvey WT, Ryan DH, Look M, et al. Two-year sustained weight loss and metabolic benefits with controlled-release phentermine/topiramate in obese and overweight adults (SEQUEL): a randomized, placebo-controlled, phase 3 extension study. Am J Clin Nutr. 2012;95(2):297-308. doi:10.3945/ajcn.111.024927
- Greenway FL, Fujioka K, Plodkowski RA, et al. Effect of naltrexone plus bupropion on weight loss in overweight and obese adults (COR-I): a multicentre, randomised, double-blind, placebo-controlled, phase 3 trial. Lancet. 2010;376(9741):595-605. doi:10.1016/S0140-6736(10)60888-4
- Sjöström L, Rissanen A, Andersen T, et al. Randomised placebo-controlled trial of orlistat for weight loss and prevention of weight regain in obese patients. European Multicentre Orlistat Study Group. Lancet. 1998;352(9123):167-172. doi:10.1016s0140-6736(97)11509-4
- Mangoni AA, Jackson SHD. Age-related changes in pharmacokinetics and pharmacodynamics: basic principles and practical applications. Br J Clin Pharmacol. 2004;57(1):6-14. doi:10.1046/j.1365-2125.2003.02007.x
- Emmerich SD, Fryar CD, Stierman B, Ogden CL. Obesity and severe obesity prevalence in adults: United States, August 2021-August 2023. NCHS Data Brief No. 508. National Center for Health Statistics; 2024. Accessed December 11, 2024. https://www.cdc.gov/nchs/products/databriefs/db508.htm
- Ward ZJ, Bleich SN, Long MW, Gortmaker SL. Association of body mass index with health care expenditures in the United States by age and sex. PLoS One. 2021;16(3):e0247307. doi:10.1371/journal.pone.0247307
- Horn DB, Almandoz JP, Look M. What is clinically relevant weight loss for your patients and how can it be achieved? A narrative review. Postgrad Med. 2022;134(4):359-375. doi:10.1080/00325481.2022.2051366
- American Diabetes Association (ADA). Standards of care in diabetes–2023. Diabetes Care. 2023;46(suppl 1):S128- S2139. doi:10.2337/dc23-S008
- Wilding JPH, Batterham RL, Calanna S, et al. Onceweekly semaglutide in adults with overweight or obesity. N Engl J Med. 2021;384(11):989-1002. doi:10.1056/NEJMoa2032183
- Pi-Sunyer X, Astrup A, Fujioka K, et al. A randomized, controlled trial of 3.0 mg of liraglutide in weight management. N Engl J Med. 2015;373(1):11-22. doi:10.1056/NEJMoa1411892
- Allison DB, Gadde KM, Garvey WT, et al. Controlled-release phentermine/topiramate in severely obese adults: a randomized controlled trial (EQUIP). Obesity (Silver Spring). 2012;20(2):330-342. doi:10.1038/oby.2011.330
- Gadde KM, Allison DB, Ryan DH, et al. Effects of low-dose, controlled-release, phentermine plus topiramate combination on weight and associated comorbidities in overweight and obese adults (CONQUER): a randomised, placebo-controlled, phase 3 trial. Lancet. 2011;377(9774):1341-1352. doi:10.1016/S0140-6736(11)60205-5
- Garvey WT, Ryan DH, Look M, et al. Two-year sustained weight loss and metabolic benefits with controlled-release phentermine/topiramate in obese and overweight adults (SEQUEL): a randomized, placebo-controlled, phase 3 extension study. Am J Clin Nutr. 2012;95(2):297-308. doi:10.3945/ajcn.111.024927
- Greenway FL, Fujioka K, Plodkowski RA, et al. Effect of naltrexone plus bupropion on weight loss in overweight and obese adults (COR-I): a multicentre, randomised, double-blind, placebo-controlled, phase 3 trial. Lancet. 2010;376(9741):595-605. doi:10.1016/S0140-6736(10)60888-4
- Sjöström L, Rissanen A, Andersen T, et al. Randomised placebo-controlled trial of orlistat for weight loss and prevention of weight regain in obese patients. European Multicentre Orlistat Study Group. Lancet. 1998;352(9123):167-172. doi:10.1016s0140-6736(97)11509-4
- Mangoni AA, Jackson SHD. Age-related changes in pharmacokinetics and pharmacodynamics: basic principles and practical applications. Br J Clin Pharmacol. 2004;57(1):6-14. doi:10.1046/j.1365-2125.2003.02007.x
Efficacy of Anti-Obesity Medications in Adult and Older Adult Veteran Populations
Efficacy of Anti-Obesity Medications in Adult and Older Adult Veteran Populations
FDA Approves Sotorasib + Panitumumab for mCRC
The US Food and Drug Administration (FDA) has approved sotorasib (Lumakras, Amgen Inc.) with panitumumab (Vectibix, Amgen Inc.) for the treatment of certain adult patients with metastatic colorectal cancer (mCRC).
Specifically, the combination therapy is indicated for those with KRAS G12C-mutated mCRC, as determined using an FDA-approved test, who have received prior treatment with fluoropyrimidine-, oxaliplatin-, and irinotecan-based chemotherapy, according to the FDA notice. The FDA also approved the therascreen KRAS RGQ PCR Kit (QIAGEN GmbH) as a companion diagnostic device for identifying eligible patients.
Approval of sotorasib with panitumumab was based on findings from the randomized, open-label, controlled CodeBreaK 300 trial showing improved overall response rates (ORR) and progression-free survival (PFS) with sotorasib and panitumumab vs investigator’s choice of trifluridine/tipiracil or regorafenib, which are current standard-of-care options.
Median PFS was 5.6 months in 53 patients randomized to receive 960 mg of oral sotorasib once daily plus 6 mg/kg of intravenous (IV) panitumumab every 2 weeks, and 2 months in 54 patients randomized to receive standard-of-care therapy (hazard ratio, 0.48). The ORR was 26% vs 0% in the arms, respectively, and the duration of response in the sotorasib/panitumumab arm was 4.4 months. No significant difference in PFS was observed between the standard-of-care arm and a third arm with 53 patients who received 240 mg of oral sotorasib daily plus 6 mg/kg of IV panitumumab every 2 weeks.
Overall survival (OS) did not differ significantly between the treatment arms in the final analysis, but the study was not statistically powered for OS.
Adverse reactions occurring in at least 20% of patients receiving sotorasib/panitumumab were rash, dry skin, diarrhea, stomatitis, fatigue, and musculoskeletal pain. Common grade 3-4 laboratory abnormalities, which occurred in two or more patients, included decreased magnesium, decreased potassium, decreased corrected calcium, and increased potassium.
The recommended dose of sotorasib is 960 mg given orally once daily and administered before the first panitumumab infusion. The recommended panitumumab dose is 6 mg/kg as an IV infusion every 14 days until disease progression, unacceptable toxicity, or until sotorasib is withheld or discontinued, according to the full prescribing information.
A version of this article first appeared on Medscape.com.
The US Food and Drug Administration (FDA) has approved sotorasib (Lumakras, Amgen Inc.) with panitumumab (Vectibix, Amgen Inc.) for the treatment of certain adult patients with metastatic colorectal cancer (mCRC).
Specifically, the combination therapy is indicated for those with KRAS G12C-mutated mCRC, as determined using an FDA-approved test, who have received prior treatment with fluoropyrimidine-, oxaliplatin-, and irinotecan-based chemotherapy, according to the FDA notice. The FDA also approved the therascreen KRAS RGQ PCR Kit (QIAGEN GmbH) as a companion diagnostic device for identifying eligible patients.
Approval of sotorasib with panitumumab was based on findings from the randomized, open-label, controlled CodeBreaK 300 trial showing improved overall response rates (ORR) and progression-free survival (PFS) with sotorasib and panitumumab vs investigator’s choice of trifluridine/tipiracil or regorafenib, which are current standard-of-care options.
Median PFS was 5.6 months in 53 patients randomized to receive 960 mg of oral sotorasib once daily plus 6 mg/kg of intravenous (IV) panitumumab every 2 weeks, and 2 months in 54 patients randomized to receive standard-of-care therapy (hazard ratio, 0.48). The ORR was 26% vs 0% in the arms, respectively, and the duration of response in the sotorasib/panitumumab arm was 4.4 months. No significant difference in PFS was observed between the standard-of-care arm and a third arm with 53 patients who received 240 mg of oral sotorasib daily plus 6 mg/kg of IV panitumumab every 2 weeks.
Overall survival (OS) did not differ significantly between the treatment arms in the final analysis, but the study was not statistically powered for OS.
Adverse reactions occurring in at least 20% of patients receiving sotorasib/panitumumab were rash, dry skin, diarrhea, stomatitis, fatigue, and musculoskeletal pain. Common grade 3-4 laboratory abnormalities, which occurred in two or more patients, included decreased magnesium, decreased potassium, decreased corrected calcium, and increased potassium.
The recommended dose of sotorasib is 960 mg given orally once daily and administered before the first panitumumab infusion. The recommended panitumumab dose is 6 mg/kg as an IV infusion every 14 days until disease progression, unacceptable toxicity, or until sotorasib is withheld or discontinued, according to the full prescribing information.
A version of this article first appeared on Medscape.com.
The US Food and Drug Administration (FDA) has approved sotorasib (Lumakras, Amgen Inc.) with panitumumab (Vectibix, Amgen Inc.) for the treatment of certain adult patients with metastatic colorectal cancer (mCRC).
Specifically, the combination therapy is indicated for those with KRAS G12C-mutated mCRC, as determined using an FDA-approved test, who have received prior treatment with fluoropyrimidine-, oxaliplatin-, and irinotecan-based chemotherapy, according to the FDA notice. The FDA also approved the therascreen KRAS RGQ PCR Kit (QIAGEN GmbH) as a companion diagnostic device for identifying eligible patients.
Approval of sotorasib with panitumumab was based on findings from the randomized, open-label, controlled CodeBreaK 300 trial showing improved overall response rates (ORR) and progression-free survival (PFS) with sotorasib and panitumumab vs investigator’s choice of trifluridine/tipiracil or regorafenib, which are current standard-of-care options.
Median PFS was 5.6 months in 53 patients randomized to receive 960 mg of oral sotorasib once daily plus 6 mg/kg of intravenous (IV) panitumumab every 2 weeks, and 2 months in 54 patients randomized to receive standard-of-care therapy (hazard ratio, 0.48). The ORR was 26% vs 0% in the arms, respectively, and the duration of response in the sotorasib/panitumumab arm was 4.4 months. No significant difference in PFS was observed between the standard-of-care arm and a third arm with 53 patients who received 240 mg of oral sotorasib daily plus 6 mg/kg of IV panitumumab every 2 weeks.
Overall survival (OS) did not differ significantly between the treatment arms in the final analysis, but the study was not statistically powered for OS.
Adverse reactions occurring in at least 20% of patients receiving sotorasib/panitumumab were rash, dry skin, diarrhea, stomatitis, fatigue, and musculoskeletal pain. Common grade 3-4 laboratory abnormalities, which occurred in two or more patients, included decreased magnesium, decreased potassium, decreased corrected calcium, and increased potassium.
The recommended dose of sotorasib is 960 mg given orally once daily and administered before the first panitumumab infusion. The recommended panitumumab dose is 6 mg/kg as an IV infusion every 14 days until disease progression, unacceptable toxicity, or until sotorasib is withheld or discontinued, according to the full prescribing information.
A version of this article first appeared on Medscape.com.
Pharmacist-Led Deprescribing of Aspirin for Primary Prevention of Cardiovascular Disease Among Geriatric Veterans
Pharmacist-Led Deprescribing of Aspirin for Primary Prevention of Cardiovascular Disease Among Geriatric Veterans
Low-dose aspirin commonly is used for the prevention of cardiovascular disease (CVD) but is associated with an increased risk of major bleeding.1 The use of aspirin for primary prevention is largely extrapolated from clinical trials showing benefit in the secondary prevention of myocardial infarction and ischemic stroke. However, results from the Aspirin in Reducing Events in the Elderly (ASPREE) trial challenged this practice.2 The ASPREE trial, conducted in the United States and Australia from 2010 to 2014, sought to determine whether daily 100 mg aspirin, was superior to placebo in promoting disability-free survival among older adults. Participants were aged ≥ 70 years (≥ 65 years for Hispanic and Black US participants), living in the community, and were free from preexisting CVD, cerebrovascular disease, or any chronic condition likely to limit survival to < 5 years. The study found no significant difference in the primary endpoints of death, dementia, or persistent physical disability, but there was a significantly higher risk of major hemorrhage in the aspirin group (3.8% vs 2.8%; hazard ratio, 1.38; 95% CI, 1.18-1.62; P < .001).
Several medical societies have updated their guideline recommendations for aspirin for primary prevention of CVD. The 2022 United States Public Service Task Force (USPSTF) provides a grade C recommendation (at least moderate certainty that the net benefit is small) to consider low-dose aspirin for the primary prevention of CVD on an individual patient basis for adults aged 40 to 59 years who have a ≥ 10% 10-year CVD risk. For adults aged ≥ 60 years, the USPSTF recommendation is grade D (moderate or high certainty that the practice has no net benefit or that harms outweigh the benefits) for low-dose aspirin use.1,3 The American College of Cardiology and American Heart Association (ACC/AHA) recommend considering low-dose aspirin for primary prevention of atherosclerotic cardiovascular disease (ASCVD) among select adults aged 40 to 70 years at higher CVD risk but not at increased risk of bleeding.4 The American Diabetes Association (ADA) recommends low-dose aspirin for primary prevention of CVD in patients with diabetes and additional risk factors such as family history of premature ASCVD, hypertension, dyslipidemia, smoking, or chronic kidney disease, and who are not at higher risk of bleeding.5 The ADA standards also caution against the use of aspirin as primary prevention in patients aged > 70 years. Low-dose aspirin use is not recommended for the primary prevention of CVD in older adults or adults of any age who are at increased risk of bleeding.
Recent literature using the US Department of Veterans Affairs (VA) Corporate Data Warehouse database confirms 86,555 of 1.8 million veterans aged > 70 years (5%) were taking low-dose aspirin for primary prevention of ASCVD despite guideline recommendations.6 Higher risk of gastrointestinal and other major bleeding from low-dose aspirin has been reported in the literature.1 Major bleeds represent a significant burden to the health care system with an estimated mean $13,093 cost for gastrointestinal bleed hospitalization.7
Considering the large scale aspirin use without appropriate indication within the veteran population, the risk of adverse effects, and the significant cost to patients and the health care system, it is imperative to determine the best approach to efficiently deprescribe aspirin for primary prevention among geriatric patients. Deprescribing refers to the systematic and supervised process of dose reduction or drug discontinuation with the goal of improving health and/or reducing the risk of adverse effects.8 During patient visits, primary care practitioners (PCPs) have opportunities to discontinue aspirin, but these encounters are time-limited and deprescribing might be secondary to more acute primary care needs. The shortage of PCPs is expected to worsen in coming years, which could further reduce their availability to assess inappropriate aspirin use.9
VA clinical pharmacist practitioners (CPPs) serve as medication experts and work autonomously under a broad scope of practice as part of the patient aligned care team.10-12 CPPs can free up time for PCPs and facilitate deprescribing efforts, especially for older adults. One retrospective cohort study conducted at a VA medical center found that CPPs deprescribed more potentially inappropriate medications among individuals aged ≥ 80 years compared with usual care with PCPs (26.8% vs 16.1%; P < .001).12,13 An aspirin deprescribing protocol conducted in 2022 resulted in nearly half of veterans aged ≥ 70 years contacted by phone agreeing to stop aspirin. Although this study supports the role pharmacists can play in reducing aspirin use in accordance with guidelines, the authors acknowledge that their interventions had a mean time of 12 minutes per patient and would require workflow changes.14 The purpose of this study is to evaluate the efficiency of aspirin deprescribing through 2 approaches: direct deprescribing by pharmacists using populationlevel review compared with clinicians following a pharmacist-led education.
Methods
This was a single-center quality improvement cohort study at the Durham VA Health Care System (DVAHCS) in North Carolina. Patients included were aged ≥ 70 years without known ASCVD who received care at any of 3 DVAHCS community-based outpatient clinics and prescribed aspirin. Patient data was obtained using the VIONE (Deprescribing Dashboard called Vital, Important, Optional, Not indicated, and Every medication has a specific indication or diagnosis) dashboard.15 VIONE was developed to identify potentially inappropriate medications (PIMs) that are eligible to deprescribe based on Beers Criteria, Screening Tool of Older Personsf Prescriptions criteria, and common clinical scenarios when clinicians determine the risk outweighs the benefit to continue a specific medication. 16,17 VIONE is used to reduce polypharmacy and improve patient safety, comfort, and medication adherence. Aspirin for patients aged ≥ 70 years without a history of ASCVD is a PIM identified by VIONE. Patients aged ≥ 70 years were chosen as an inclusion criteria in this study to match the ASPREE trial inclusion criteria and age inclusion criteria in the VIONE dashboard for aspirin deprescribing.2 Patient lists were generated for these potentially inappropriate aspirin prescriptions for 3 months before clinician staff education presentations, the day of the presentations, and 3 months after.
The primary endpoint was the number of veterans with aspirin deprescribed directly by 2 pharmacists over 12 weeks, divided by total patient care time spent, compared with the change in number of veterans with aspirin deprescribed by any DVAHCS physician, nurse practitioner, physician assistant, or CPP over 12 weeks, divided by the total pharmacist time spent on PCP education. Secondary endpoints were the number of aspirin orders discontinued by pharmacists and CPPs, the number of aspirin orders discontinued 12 weeks before pharmacist-led education compared with the number of aspirin orders discontinued 12 weeks after CPP-led education, average and median pharmacist time spent per patient encounter, and time of direct patient encounters vs time spent on PCP education.
Pharmacists reviewed each patient who met the inclusion criteria from the list generated by VIONE on December 1, 2022, for aspirin appropriateness according to the ACC/AHA and USPSTF guidelines, with the goal to discontinue aspirin for primary prevention of ASCVD and no other indications.1,4 Pharmacists documented their visits using VIONE methodology in the Computerized Patient Record System (CPRS) using a polypharmacy review note. CPPs contacted patients who were taking aspirin for primary prevention by unscheduled telephone call to assess for aspirin adherence, undocumented history of ASCVD, cardiovascular risk factors, and history of bleeding. Aspirin was discontinued if patients met guideline criteria recommendations and agreed to discontinuation. Risk-benefit discussions were completed when patients without known ASCVD were considered high risk because the ACC/AHA guidelines mention there is insufficient evidence of safety and efficacy of aspirin for primary prevention for patients with other known ASCVD risk factors (eg, strong family history of premature myocardial infarction, inability to achieve lipid, blood pressure, or glucose targets, or significant elevation in coronary artery calcium score).
High risk was defined as family history of premature ASCVD (in a male first-degree relative aged < 55 years or a female first-degree relative aged < 65 years), most recent blood pressure or 2 blood pressure results in the last 12 months > 160/100 mm Hg, recent hemoglobin A1c > 9%, and/or low-density lipoprotein > 190 mg/dL or not prescribed an indicated statin.3 Aspirin was continued or discontinued according to patient preference after the personalized risk-benefit discussion.
For patients with a clinical indication for aspirin use other than ASCVD (eg, atrial fibrillation not on anticoagulation, venous thromboembolism prophylaxis, carotid artery disease), CPPs documented their assessment and when appropriate deferred to the PCP for consideration of stopping aspirin. For patients with undocumented ASCVD, CPPs added their ASCVD history to their problem list and aspirin was continued. PCPs were notified by alert when aspirin was discontinued and when patients could not be reached by telephone.
presented a review of recent guideline updates and supporting literature at 2 online staff meetings. The education sessions lasted about 10 minutes and were presented to PCPs across 3 community-based outpatient clinics. An estimated 40 minutes were spent creating the PowerPoint education materials, seeking feedback, making edits, and answering questions or emails from PCPs after the presentation. During the presentation, pharmacists encouraged PCPs to discontinue aspirin (active VA prescriptions and reported over-the-counter use) for primary prevention of ASCVD in patients aged ≥ 70 years during their upcoming appointments and consider risk factors recommended by the ACC/AHA guidelines when applicable. PCPs were notified that CPPs planned to start a population review for discontinuing active VA aspirin prescriptions on December 1, 2022. The primary endpoint and secondary endpoints were analyzed using descriptive statistics. All data were analyzed using Microsoft Excel.

Results
A total of 868 patients aged ≥ 70 years with active prescriptions for aspirin were identified on December 1, 2022. After applying inclusion and exclusion criteria for the pharmacist population review, 224 patients were included for cohort final analysis (Figure). All 868 patients were eligible for the CPP intervention. Primary reasons for exclusion from the CPP population included over-thecounter aspirin and a history of ASCVD in the patient’s problem list. All patients were male, with a mean (SD) age of 75 (4.4) years (Table 1). Most patients were prescribed aspirin, 81 mg daily (n = 220; 98%).

The direct CPP deprescribing intervention resulted in 2 aspirin prescriptions discontinued per hour of pharmacist time and 67 aspirin prescriptions discontinued per hour of pharmacist time via the PCP education intervention. CPPs discontinued 66 aspirin orders in the 12 weeks before the PCP education sessions. A total of 230 aspirin prescriptions were discontinued in the 12 weeks following the PCP education sessions, with 97 discontinued directly by CPPs and 133 discontinued by PCPs. The PCP education session yielded an additional 67 discontinued aspirin orders compared with the 12 weeks before the education sessions (Table 2).

The CPP direct deprescribing intervention took about 48.3 hours, accounting for health record review and time interacting with patients. The PCP education intervention took about 60 minutes, which included time for preparing and delivering education materials (Table 3). CPP deprescribing encounter types, interventions, and related subcategories, and other identified indications to continue aspirin are listed in Table 4.


Discussion
Compared with direct deprescribing by pharmacists, the PCP education intervention was more efficient based on number of aspirin orders discontinued by pharmacist time. PCPs discontinued twice as many aspirin prescriptions in the 12 weeks after pharmacist-led education compared with the 12 weeks before.
Patients were primarily contacted by telephone (73%) for deprescribing. Among the 163 patients reached by phone and encouraged to discontinue aspirin, 97 patients (60%) accepted the recommendation, which was similar to the acceptance rates found in the literature (48% to 55%).14,18 Although many veterans continued taking aspirin (78%), most had indications for its continued use, such as a history of ASCVD, atrial fibrillation without anticoagulation, and carotid artery stenosis, and complex comorbidities that required further discussion with their PCP. Less common uses for aspirin were identified through CPRS review or patient reports included cerebral small vessel disease without history of ASCVD, subclavian artery stenosis, thrombocytosis, bioprosthetic valve replacement, giant cell arteritis, rheumatoid arthritis, and prevention of second eye involvement of ischemic optic neuropathy.
to describe the benefit of clinical pharmacy services for deprescribing aspirin for primary prevention of ASCVD through PCP education. Previously published literature has assessed alternative ways to identify or discontinue PIMs—including aspirin—among geriatric patients. One study evaluated the use of marking inappropriate aspirin prescriptions in the electronic health database, leading to a significant reduction in incidence of inappropriate aspirin prescribing; however, it did not assess changes in discontinuation rates of existing aspirin prescriptions.19 The previous VA pharmacist aspirin deprescribing protocol demonstrated pharmacists’ aptitude at discontinuing aspirin for primary prevention but only used direct patient contact and did not compare efficiency with other methods, including PCP education.14
This quality improvement project contributes new data to the existing literature to support the use of clinical pharmacists to discontinue aspirin for primary prevention and suggests a strong role for pharmacists as educators on clinical guidelines, in addition to their roles directly deprescribing PIMs in clinical practice. This study is further strengthened by its use of VIONE, which previously has demonstrated effectiveness in deprescribing a variety of PIMs in primary care settings.20
Despite using VIONE for generating a list of patients eligible for deprescription, our CPRS review found that this list was frequently inaccurate. For example, a small portion of patients were on the VIONE generated list indicating they had no ASCVD history, but had transient ischemic attack listed in their problem lists. Patient problem lists often were missing documented ASCVD history that was revealed by patient interview or CPRS review. It is possible that patients interviewed might have omitted relevant ASCVD history because of low health literacy, conditions affecting memory, or use of health care services outside the VA system.
There were several instances of aspirin used for other non-ASCVD indications, such as primary stroke prevention in atrial fibrillation. The ACC/AHA atrial fibrillation guidelines previously provided a Class IIb recommendation (benefit is greater than risk but additional studies are needed) for considering no antithrombic therapy or treatment with oral anticoagulant or aspirin for nonvalvular atrial fibrillation with CHA2DS2-VASc (Congestive heart failure, Hypertension, Age [> 65 y, 1 point; > 75 y, 2 points], Diabetes, previous Stroke/transient ischemic attack [2 points]) score of 1.21 The ACC/ AHA guidelines were updated in 2023 to recommend against antiplatelet therapy as an alternative to anticoagulation for reducing cardioembolic stroke risk among patients with atrial fibrillation with no indication for antiplatelet therapy because of risk of harm.22 If a patient has no risk factors for stroke, aspirin is not recommended to prevent thromboembolic events because of a lack of benefit. Interventions from this quality improvement study were completed before the 2023 atrial fibrillation guideline was published and therefore in this study aspirin was not discontinued when used for atrial fibrillation. Aspirin use for atrial fibrillation might benefit from similar discontinuation efforts analyzed within this study. Beyond atrial fibrillation, major guidelines do not comment on the use of aspirin for any other indications in the absence of clinical ASCVD.
Limitations
This study is limited by the lack of clinical consensus for complex patients and demonstrates the importance of individualized patient assessment when considering discontinuing aspirin. Because of the project’s relatively short intervention period, aspirin deprescribing rates could decrease over time and repeated education efforts might be necessary to see lasting impact. Health care professionals from services outside of primary care also might have discontinued aspirin during the study period unrelated to the education and these discontinued aspirin prescriptions could contribute to the higher rate observed among PCPs. This study included a specific population cohort of male, US veterans and might not reflect other populations where these interventions could be implemented.
The measurement of time spent by pharmacists and PCPs is an additional limitation. Although it is expected that PCPs attempt to discontinue aspirin during their existing patient care appointments, the time spent during visits was not measured or documented. Direct deprescribing by pharmacist CPRS review required a significant amount of time and could be a barrier to successful intervention by CPPs in patient aligned care teams.
To reduce the time pharmacists spent completing CPRS reviews, an aspirin deprescribing clinical reminder tool could be used to assess use and appropriate indication quickly during any primary care visit led by a PCP or CPP. In addition, it is recommended that pharmacists regularly educate health care professionals on guideline recommendations for aspirin use among geriatric patients. Future studies of the incidence of major cardiovascular events after aspirin deprescribing among geriatric patients and a longitudinal cost/benefit analysis could support these initiatives.
Conclusions
In this study, pharmacists successfully deprescribed inappropriate medications, such as aspirin. However, pharmacist-led PCP education is more efficient compared with direct deprescribing using a population-level review. PCP education requires less time and could allow ambulatory care pharmacists to spend more time on other direct patient care interventions to improve quality and access to care in primary care clinics. This study’s results further support the role of pharmacists in deprescribing PIMs for older adults and the use of a deprescribing tool, such as VIONE, in a primary care setting.
- US Preventive Services Task Force; Davidson KW, Barry MJ, et al. Aspirin use to prevent cardiovascular disease: US Preventive Services Task Force recommendation statement. JAMA. 2022;327(16):1577-1584. doi:10.1001/jama.2022.4983
- McNeil JJ, Nelson MR, Woods RL, et al. Effect of aspirin on all-cause mortality in the healthy elderly. N Engl J Med. 2018;379(16):1519-1528. doi:10.1056/NEJMoa1803955
- Barry MJ, Wolff TA, Pbert L, et al. Putting evidence into practice: an update on the US Preventive Services Task Force methods for developing recommendations for preventive services. Ann Fam Med. 2023;21(2):165-171. doi:10.1370/afm.2946
- Arnett DK, Blumenthal RS, Albert MA, et al. 2019 ACC/ AHA Guideline on the Primary Prevention of Cardiovascular Disease: A report of the American College of Cardiology/ American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019;140(11):e596-e646. doi:10.1161/CIR.0000000000000678
- American Diabetes Association Professional Practice Committee. 10. Cardiovascular disease and risk management: Standards of care in diabetes-2024. Diabetes Care. 2024;47(Suppl 1):S179-S218. doi:10.2337/dc24-S010
- Ong SY, Chui P, Bhargava A, Justice A, Hauser RG. Estimating aspirin overuse for primary prevention of atherosclerotic cardiovascular disease (from a nationwide healthcare system). Am J Cardiol. 2020;137:25-30. doi:10.1016/j.amjcard.2020.09.042
- Weiss AJ, Jiang HJ. Overview of clinical conditions with frequent and costly hospital readmissions by payer, 2018. In: Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. Agency for Healthcare Research and Quality (US); July 20, 2021.
- Krishnaswami A, Steinman MA, Goyal P, et al. Deprescribing in older adults with cardiovascular disease. J Am Coll Cardiol. 2019;73(20):2584-2595. doi:10.1016/j.jacc.2019.03.467
- Association of American Medical Colleges. The complexities of physician supply and demand: projections from 2019 to 2034. Accessed March 17, 2024. https://www.aamc.org/media/54681/download
- US Department of Veterans Affairs, Veterans Health Administration. VHA Directive 1108.07(1): General pharmacy service requirements. November 28, 2022. Accessed March 17, 2024. https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=10045
- US Department of Veterans Affairs, Veterans Health Administration. VHA Handbook 1108.11(3): Clinical pharmacy services. July 1, 2015. Accessed March 17, 2024. https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=3120
- US Department of Veterans Affairs. Clinical pharmacist practitioner (CPP) to improve access to and quality of care August 2021. August 2021. Accessed May 19, 2023. https://www.pbm.va.gov/PBM/CPPO/Documents/ExternalFactSheet_OptimizingtheCPPToImproveAccess_508.pdf
- Ammerman CA, Simpkins BA, Warman N, Downs TN. Potentially inappropriate medications in older adults: Deprescribing with a clinical pharmacist. J Am Geriatr Soc. 2019;67(1):115-118. doi:10.1111/jgs.15623
- Rothbauer K, Siodlak M, Dreischmeier E, Ranola TS, Welch L. Evaluation of a pharmacist-driven ambulatory aspirin deprescribing protocol. Fed Pract. 2022;39(suppl 5):S37- S41a. doi:10.12788/fp.0294
- US Department of Veterans Affairs. VIONE changes the way VA handles prescriptions. January 25, 2020. Accessed May 21, 2023. https://news.va.gov/70709/vione-changes-way-va-handles-prescriptions/
- 2023 American Geriatrics Society Beers Criteria Update Expert Panel. American Geriatrics Society 2023 updated AGS Beers Criteria for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2023;71(7):2052- 2081. doi:10.1111/jgs.18372
- O’Mahony D, Cherubini A, Guiteras AR, et al. STOPP/ START criteria for potentially inappropriate prescribing in older people: version 3. Eur Geriatr Med. 2023;14(4):625- 632. doi:10.1007/s41999-023-00777-y
- Draeger C, Lodhi F, Geissinger N, Larson T, Griesbach S. Interdisciplinary deprescribing of aspirin through prescriber education and provision of patient-specific recommendations. WMJ. 2022;121(3):220-225
- de Lusignan S, Hinton W, Seidu S, et al. Dashboards to reduce inappropriate prescribing of metformin and aspirin: A quality assurance programme in a primary care sentinel network. Prim Care Diabetes. 2021;15(6):1075-1079. doi:10.1016/j.pcd.2021.06.003
- Nelson MW, Downs TN, Puglisi GM, Simpkins BA, Collier AS. Use of a deprescribing tool in an interdisciplinary primary-care patient-aligned care team. Sr Care Pharm. 2022;37(1):34-43. doi:10.4140/TCP.n.2022.34
- January CT, Wann LS, Alpert JS, et al. 2014 AHA/ ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines and the Heart Rhythm Society. Circulation. 2014;130(23):e199-e267. doi:10.1161/CIR.0000000000000041
- Joglar JA, Chung MK, Armbruster AL, et al. 2023 ACC/ AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines Circulation. 2024;149(1):e1- e156. doi:10.1161/CIR.0000000000001193
Low-dose aspirin commonly is used for the prevention of cardiovascular disease (CVD) but is associated with an increased risk of major bleeding.1 The use of aspirin for primary prevention is largely extrapolated from clinical trials showing benefit in the secondary prevention of myocardial infarction and ischemic stroke. However, results from the Aspirin in Reducing Events in the Elderly (ASPREE) trial challenged this practice.2 The ASPREE trial, conducted in the United States and Australia from 2010 to 2014, sought to determine whether daily 100 mg aspirin, was superior to placebo in promoting disability-free survival among older adults. Participants were aged ≥ 70 years (≥ 65 years for Hispanic and Black US participants), living in the community, and were free from preexisting CVD, cerebrovascular disease, or any chronic condition likely to limit survival to < 5 years. The study found no significant difference in the primary endpoints of death, dementia, or persistent physical disability, but there was a significantly higher risk of major hemorrhage in the aspirin group (3.8% vs 2.8%; hazard ratio, 1.38; 95% CI, 1.18-1.62; P < .001).
Several medical societies have updated their guideline recommendations for aspirin for primary prevention of CVD. The 2022 United States Public Service Task Force (USPSTF) provides a grade C recommendation (at least moderate certainty that the net benefit is small) to consider low-dose aspirin for the primary prevention of CVD on an individual patient basis for adults aged 40 to 59 years who have a ≥ 10% 10-year CVD risk. For adults aged ≥ 60 years, the USPSTF recommendation is grade D (moderate or high certainty that the practice has no net benefit or that harms outweigh the benefits) for low-dose aspirin use.1,3 The American College of Cardiology and American Heart Association (ACC/AHA) recommend considering low-dose aspirin for primary prevention of atherosclerotic cardiovascular disease (ASCVD) among select adults aged 40 to 70 years at higher CVD risk but not at increased risk of bleeding.4 The American Diabetes Association (ADA) recommends low-dose aspirin for primary prevention of CVD in patients with diabetes and additional risk factors such as family history of premature ASCVD, hypertension, dyslipidemia, smoking, or chronic kidney disease, and who are not at higher risk of bleeding.5 The ADA standards also caution against the use of aspirin as primary prevention in patients aged > 70 years. Low-dose aspirin use is not recommended for the primary prevention of CVD in older adults or adults of any age who are at increased risk of bleeding.
Recent literature using the US Department of Veterans Affairs (VA) Corporate Data Warehouse database confirms 86,555 of 1.8 million veterans aged > 70 years (5%) were taking low-dose aspirin for primary prevention of ASCVD despite guideline recommendations.6 Higher risk of gastrointestinal and other major bleeding from low-dose aspirin has been reported in the literature.1 Major bleeds represent a significant burden to the health care system with an estimated mean $13,093 cost for gastrointestinal bleed hospitalization.7
Considering the large scale aspirin use without appropriate indication within the veteran population, the risk of adverse effects, and the significant cost to patients and the health care system, it is imperative to determine the best approach to efficiently deprescribe aspirin for primary prevention among geriatric patients. Deprescribing refers to the systematic and supervised process of dose reduction or drug discontinuation with the goal of improving health and/or reducing the risk of adverse effects.8 During patient visits, primary care practitioners (PCPs) have opportunities to discontinue aspirin, but these encounters are time-limited and deprescribing might be secondary to more acute primary care needs. The shortage of PCPs is expected to worsen in coming years, which could further reduce their availability to assess inappropriate aspirin use.9
VA clinical pharmacist practitioners (CPPs) serve as medication experts and work autonomously under a broad scope of practice as part of the patient aligned care team.10-12 CPPs can free up time for PCPs and facilitate deprescribing efforts, especially for older adults. One retrospective cohort study conducted at a VA medical center found that CPPs deprescribed more potentially inappropriate medications among individuals aged ≥ 80 years compared with usual care with PCPs (26.8% vs 16.1%; P < .001).12,13 An aspirin deprescribing protocol conducted in 2022 resulted in nearly half of veterans aged ≥ 70 years contacted by phone agreeing to stop aspirin. Although this study supports the role pharmacists can play in reducing aspirin use in accordance with guidelines, the authors acknowledge that their interventions had a mean time of 12 minutes per patient and would require workflow changes.14 The purpose of this study is to evaluate the efficiency of aspirin deprescribing through 2 approaches: direct deprescribing by pharmacists using populationlevel review compared with clinicians following a pharmacist-led education.
Methods
This was a single-center quality improvement cohort study at the Durham VA Health Care System (DVAHCS) in North Carolina. Patients included were aged ≥ 70 years without known ASCVD who received care at any of 3 DVAHCS community-based outpatient clinics and prescribed aspirin. Patient data was obtained using the VIONE (Deprescribing Dashboard called Vital, Important, Optional, Not indicated, and Every medication has a specific indication or diagnosis) dashboard.15 VIONE was developed to identify potentially inappropriate medications (PIMs) that are eligible to deprescribe based on Beers Criteria, Screening Tool of Older Personsf Prescriptions criteria, and common clinical scenarios when clinicians determine the risk outweighs the benefit to continue a specific medication. 16,17 VIONE is used to reduce polypharmacy and improve patient safety, comfort, and medication adherence. Aspirin for patients aged ≥ 70 years without a history of ASCVD is a PIM identified by VIONE. Patients aged ≥ 70 years were chosen as an inclusion criteria in this study to match the ASPREE trial inclusion criteria and age inclusion criteria in the VIONE dashboard for aspirin deprescribing.2 Patient lists were generated for these potentially inappropriate aspirin prescriptions for 3 months before clinician staff education presentations, the day of the presentations, and 3 months after.
The primary endpoint was the number of veterans with aspirin deprescribed directly by 2 pharmacists over 12 weeks, divided by total patient care time spent, compared with the change in number of veterans with aspirin deprescribed by any DVAHCS physician, nurse practitioner, physician assistant, or CPP over 12 weeks, divided by the total pharmacist time spent on PCP education. Secondary endpoints were the number of aspirin orders discontinued by pharmacists and CPPs, the number of aspirin orders discontinued 12 weeks before pharmacist-led education compared with the number of aspirin orders discontinued 12 weeks after CPP-led education, average and median pharmacist time spent per patient encounter, and time of direct patient encounters vs time spent on PCP education.
Pharmacists reviewed each patient who met the inclusion criteria from the list generated by VIONE on December 1, 2022, for aspirin appropriateness according to the ACC/AHA and USPSTF guidelines, with the goal to discontinue aspirin for primary prevention of ASCVD and no other indications.1,4 Pharmacists documented their visits using VIONE methodology in the Computerized Patient Record System (CPRS) using a polypharmacy review note. CPPs contacted patients who were taking aspirin for primary prevention by unscheduled telephone call to assess for aspirin adherence, undocumented history of ASCVD, cardiovascular risk factors, and history of bleeding. Aspirin was discontinued if patients met guideline criteria recommendations and agreed to discontinuation. Risk-benefit discussions were completed when patients without known ASCVD were considered high risk because the ACC/AHA guidelines mention there is insufficient evidence of safety and efficacy of aspirin for primary prevention for patients with other known ASCVD risk factors (eg, strong family history of premature myocardial infarction, inability to achieve lipid, blood pressure, or glucose targets, or significant elevation in coronary artery calcium score).
High risk was defined as family history of premature ASCVD (in a male first-degree relative aged < 55 years or a female first-degree relative aged < 65 years), most recent blood pressure or 2 blood pressure results in the last 12 months > 160/100 mm Hg, recent hemoglobin A1c > 9%, and/or low-density lipoprotein > 190 mg/dL or not prescribed an indicated statin.3 Aspirin was continued or discontinued according to patient preference after the personalized risk-benefit discussion.
For patients with a clinical indication for aspirin use other than ASCVD (eg, atrial fibrillation not on anticoagulation, venous thromboembolism prophylaxis, carotid artery disease), CPPs documented their assessment and when appropriate deferred to the PCP for consideration of stopping aspirin. For patients with undocumented ASCVD, CPPs added their ASCVD history to their problem list and aspirin was continued. PCPs were notified by alert when aspirin was discontinued and when patients could not be reached by telephone.
presented a review of recent guideline updates and supporting literature at 2 online staff meetings. The education sessions lasted about 10 minutes and were presented to PCPs across 3 community-based outpatient clinics. An estimated 40 minutes were spent creating the PowerPoint education materials, seeking feedback, making edits, and answering questions or emails from PCPs after the presentation. During the presentation, pharmacists encouraged PCPs to discontinue aspirin (active VA prescriptions and reported over-the-counter use) for primary prevention of ASCVD in patients aged ≥ 70 years during their upcoming appointments and consider risk factors recommended by the ACC/AHA guidelines when applicable. PCPs were notified that CPPs planned to start a population review for discontinuing active VA aspirin prescriptions on December 1, 2022. The primary endpoint and secondary endpoints were analyzed using descriptive statistics. All data were analyzed using Microsoft Excel.

Results
A total of 868 patients aged ≥ 70 years with active prescriptions for aspirin were identified on December 1, 2022. After applying inclusion and exclusion criteria for the pharmacist population review, 224 patients were included for cohort final analysis (Figure). All 868 patients were eligible for the CPP intervention. Primary reasons for exclusion from the CPP population included over-thecounter aspirin and a history of ASCVD in the patient’s problem list. All patients were male, with a mean (SD) age of 75 (4.4) years (Table 1). Most patients were prescribed aspirin, 81 mg daily (n = 220; 98%).

The direct CPP deprescribing intervention resulted in 2 aspirin prescriptions discontinued per hour of pharmacist time and 67 aspirin prescriptions discontinued per hour of pharmacist time via the PCP education intervention. CPPs discontinued 66 aspirin orders in the 12 weeks before the PCP education sessions. A total of 230 aspirin prescriptions were discontinued in the 12 weeks following the PCP education sessions, with 97 discontinued directly by CPPs and 133 discontinued by PCPs. The PCP education session yielded an additional 67 discontinued aspirin orders compared with the 12 weeks before the education sessions (Table 2).

The CPP direct deprescribing intervention took about 48.3 hours, accounting for health record review and time interacting with patients. The PCP education intervention took about 60 minutes, which included time for preparing and delivering education materials (Table 3). CPP deprescribing encounter types, interventions, and related subcategories, and other identified indications to continue aspirin are listed in Table 4.


Discussion
Compared with direct deprescribing by pharmacists, the PCP education intervention was more efficient based on number of aspirin orders discontinued by pharmacist time. PCPs discontinued twice as many aspirin prescriptions in the 12 weeks after pharmacist-led education compared with the 12 weeks before.
Patients were primarily contacted by telephone (73%) for deprescribing. Among the 163 patients reached by phone and encouraged to discontinue aspirin, 97 patients (60%) accepted the recommendation, which was similar to the acceptance rates found in the literature (48% to 55%).14,18 Although many veterans continued taking aspirin (78%), most had indications for its continued use, such as a history of ASCVD, atrial fibrillation without anticoagulation, and carotid artery stenosis, and complex comorbidities that required further discussion with their PCP. Less common uses for aspirin were identified through CPRS review or patient reports included cerebral small vessel disease without history of ASCVD, subclavian artery stenosis, thrombocytosis, bioprosthetic valve replacement, giant cell arteritis, rheumatoid arthritis, and prevention of second eye involvement of ischemic optic neuropathy.
to describe the benefit of clinical pharmacy services for deprescribing aspirin for primary prevention of ASCVD through PCP education. Previously published literature has assessed alternative ways to identify or discontinue PIMs—including aspirin—among geriatric patients. One study evaluated the use of marking inappropriate aspirin prescriptions in the electronic health database, leading to a significant reduction in incidence of inappropriate aspirin prescribing; however, it did not assess changes in discontinuation rates of existing aspirin prescriptions.19 The previous VA pharmacist aspirin deprescribing protocol demonstrated pharmacists’ aptitude at discontinuing aspirin for primary prevention but only used direct patient contact and did not compare efficiency with other methods, including PCP education.14
This quality improvement project contributes new data to the existing literature to support the use of clinical pharmacists to discontinue aspirin for primary prevention and suggests a strong role for pharmacists as educators on clinical guidelines, in addition to their roles directly deprescribing PIMs in clinical practice. This study is further strengthened by its use of VIONE, which previously has demonstrated effectiveness in deprescribing a variety of PIMs in primary care settings.20
Despite using VIONE for generating a list of patients eligible for deprescription, our CPRS review found that this list was frequently inaccurate. For example, a small portion of patients were on the VIONE generated list indicating they had no ASCVD history, but had transient ischemic attack listed in their problem lists. Patient problem lists often were missing documented ASCVD history that was revealed by patient interview or CPRS review. It is possible that patients interviewed might have omitted relevant ASCVD history because of low health literacy, conditions affecting memory, or use of health care services outside the VA system.
There were several instances of aspirin used for other non-ASCVD indications, such as primary stroke prevention in atrial fibrillation. The ACC/AHA atrial fibrillation guidelines previously provided a Class IIb recommendation (benefit is greater than risk but additional studies are needed) for considering no antithrombic therapy or treatment with oral anticoagulant or aspirin for nonvalvular atrial fibrillation with CHA2DS2-VASc (Congestive heart failure, Hypertension, Age [> 65 y, 1 point; > 75 y, 2 points], Diabetes, previous Stroke/transient ischemic attack [2 points]) score of 1.21 The ACC/ AHA guidelines were updated in 2023 to recommend against antiplatelet therapy as an alternative to anticoagulation for reducing cardioembolic stroke risk among patients with atrial fibrillation with no indication for antiplatelet therapy because of risk of harm.22 If a patient has no risk factors for stroke, aspirin is not recommended to prevent thromboembolic events because of a lack of benefit. Interventions from this quality improvement study were completed before the 2023 atrial fibrillation guideline was published and therefore in this study aspirin was not discontinued when used for atrial fibrillation. Aspirin use for atrial fibrillation might benefit from similar discontinuation efforts analyzed within this study. Beyond atrial fibrillation, major guidelines do not comment on the use of aspirin for any other indications in the absence of clinical ASCVD.
Limitations
This study is limited by the lack of clinical consensus for complex patients and demonstrates the importance of individualized patient assessment when considering discontinuing aspirin. Because of the project’s relatively short intervention period, aspirin deprescribing rates could decrease over time and repeated education efforts might be necessary to see lasting impact. Health care professionals from services outside of primary care also might have discontinued aspirin during the study period unrelated to the education and these discontinued aspirin prescriptions could contribute to the higher rate observed among PCPs. This study included a specific population cohort of male, US veterans and might not reflect other populations where these interventions could be implemented.
The measurement of time spent by pharmacists and PCPs is an additional limitation. Although it is expected that PCPs attempt to discontinue aspirin during their existing patient care appointments, the time spent during visits was not measured or documented. Direct deprescribing by pharmacist CPRS review required a significant amount of time and could be a barrier to successful intervention by CPPs in patient aligned care teams.
To reduce the time pharmacists spent completing CPRS reviews, an aspirin deprescribing clinical reminder tool could be used to assess use and appropriate indication quickly during any primary care visit led by a PCP or CPP. In addition, it is recommended that pharmacists regularly educate health care professionals on guideline recommendations for aspirin use among geriatric patients. Future studies of the incidence of major cardiovascular events after aspirin deprescribing among geriatric patients and a longitudinal cost/benefit analysis could support these initiatives.
Conclusions
In this study, pharmacists successfully deprescribed inappropriate medications, such as aspirin. However, pharmacist-led PCP education is more efficient compared with direct deprescribing using a population-level review. PCP education requires less time and could allow ambulatory care pharmacists to spend more time on other direct patient care interventions to improve quality and access to care in primary care clinics. This study’s results further support the role of pharmacists in deprescribing PIMs for older adults and the use of a deprescribing tool, such as VIONE, in a primary care setting.
Low-dose aspirin commonly is used for the prevention of cardiovascular disease (CVD) but is associated with an increased risk of major bleeding.1 The use of aspirin for primary prevention is largely extrapolated from clinical trials showing benefit in the secondary prevention of myocardial infarction and ischemic stroke. However, results from the Aspirin in Reducing Events in the Elderly (ASPREE) trial challenged this practice.2 The ASPREE trial, conducted in the United States and Australia from 2010 to 2014, sought to determine whether daily 100 mg aspirin, was superior to placebo in promoting disability-free survival among older adults. Participants were aged ≥ 70 years (≥ 65 years for Hispanic and Black US participants), living in the community, and were free from preexisting CVD, cerebrovascular disease, or any chronic condition likely to limit survival to < 5 years. The study found no significant difference in the primary endpoints of death, dementia, or persistent physical disability, but there was a significantly higher risk of major hemorrhage in the aspirin group (3.8% vs 2.8%; hazard ratio, 1.38; 95% CI, 1.18-1.62; P < .001).
Several medical societies have updated their guideline recommendations for aspirin for primary prevention of CVD. The 2022 United States Public Service Task Force (USPSTF) provides a grade C recommendation (at least moderate certainty that the net benefit is small) to consider low-dose aspirin for the primary prevention of CVD on an individual patient basis for adults aged 40 to 59 years who have a ≥ 10% 10-year CVD risk. For adults aged ≥ 60 years, the USPSTF recommendation is grade D (moderate or high certainty that the practice has no net benefit or that harms outweigh the benefits) for low-dose aspirin use.1,3 The American College of Cardiology and American Heart Association (ACC/AHA) recommend considering low-dose aspirin for primary prevention of atherosclerotic cardiovascular disease (ASCVD) among select adults aged 40 to 70 years at higher CVD risk but not at increased risk of bleeding.4 The American Diabetes Association (ADA) recommends low-dose aspirin for primary prevention of CVD in patients with diabetes and additional risk factors such as family history of premature ASCVD, hypertension, dyslipidemia, smoking, or chronic kidney disease, and who are not at higher risk of bleeding.5 The ADA standards also caution against the use of aspirin as primary prevention in patients aged > 70 years. Low-dose aspirin use is not recommended for the primary prevention of CVD in older adults or adults of any age who are at increased risk of bleeding.
Recent literature using the US Department of Veterans Affairs (VA) Corporate Data Warehouse database confirms 86,555 of 1.8 million veterans aged > 70 years (5%) were taking low-dose aspirin for primary prevention of ASCVD despite guideline recommendations.6 Higher risk of gastrointestinal and other major bleeding from low-dose aspirin has been reported in the literature.1 Major bleeds represent a significant burden to the health care system with an estimated mean $13,093 cost for gastrointestinal bleed hospitalization.7
Considering the large scale aspirin use without appropriate indication within the veteran population, the risk of adverse effects, and the significant cost to patients and the health care system, it is imperative to determine the best approach to efficiently deprescribe aspirin for primary prevention among geriatric patients. Deprescribing refers to the systematic and supervised process of dose reduction or drug discontinuation with the goal of improving health and/or reducing the risk of adverse effects.8 During patient visits, primary care practitioners (PCPs) have opportunities to discontinue aspirin, but these encounters are time-limited and deprescribing might be secondary to more acute primary care needs. The shortage of PCPs is expected to worsen in coming years, which could further reduce their availability to assess inappropriate aspirin use.9
VA clinical pharmacist practitioners (CPPs) serve as medication experts and work autonomously under a broad scope of practice as part of the patient aligned care team.10-12 CPPs can free up time for PCPs and facilitate deprescribing efforts, especially for older adults. One retrospective cohort study conducted at a VA medical center found that CPPs deprescribed more potentially inappropriate medications among individuals aged ≥ 80 years compared with usual care with PCPs (26.8% vs 16.1%; P < .001).12,13 An aspirin deprescribing protocol conducted in 2022 resulted in nearly half of veterans aged ≥ 70 years contacted by phone agreeing to stop aspirin. Although this study supports the role pharmacists can play in reducing aspirin use in accordance with guidelines, the authors acknowledge that their interventions had a mean time of 12 minutes per patient and would require workflow changes.14 The purpose of this study is to evaluate the efficiency of aspirin deprescribing through 2 approaches: direct deprescribing by pharmacists using populationlevel review compared with clinicians following a pharmacist-led education.
Methods
This was a single-center quality improvement cohort study at the Durham VA Health Care System (DVAHCS) in North Carolina. Patients included were aged ≥ 70 years without known ASCVD who received care at any of 3 DVAHCS community-based outpatient clinics and prescribed aspirin. Patient data was obtained using the VIONE (Deprescribing Dashboard called Vital, Important, Optional, Not indicated, and Every medication has a specific indication or diagnosis) dashboard.15 VIONE was developed to identify potentially inappropriate medications (PIMs) that are eligible to deprescribe based on Beers Criteria, Screening Tool of Older Personsf Prescriptions criteria, and common clinical scenarios when clinicians determine the risk outweighs the benefit to continue a specific medication. 16,17 VIONE is used to reduce polypharmacy and improve patient safety, comfort, and medication adherence. Aspirin for patients aged ≥ 70 years without a history of ASCVD is a PIM identified by VIONE. Patients aged ≥ 70 years were chosen as an inclusion criteria in this study to match the ASPREE trial inclusion criteria and age inclusion criteria in the VIONE dashboard for aspirin deprescribing.2 Patient lists were generated for these potentially inappropriate aspirin prescriptions for 3 months before clinician staff education presentations, the day of the presentations, and 3 months after.
The primary endpoint was the number of veterans with aspirin deprescribed directly by 2 pharmacists over 12 weeks, divided by total patient care time spent, compared with the change in number of veterans with aspirin deprescribed by any DVAHCS physician, nurse practitioner, physician assistant, or CPP over 12 weeks, divided by the total pharmacist time spent on PCP education. Secondary endpoints were the number of aspirin orders discontinued by pharmacists and CPPs, the number of aspirin orders discontinued 12 weeks before pharmacist-led education compared with the number of aspirin orders discontinued 12 weeks after CPP-led education, average and median pharmacist time spent per patient encounter, and time of direct patient encounters vs time spent on PCP education.
Pharmacists reviewed each patient who met the inclusion criteria from the list generated by VIONE on December 1, 2022, for aspirin appropriateness according to the ACC/AHA and USPSTF guidelines, with the goal to discontinue aspirin for primary prevention of ASCVD and no other indications.1,4 Pharmacists documented their visits using VIONE methodology in the Computerized Patient Record System (CPRS) using a polypharmacy review note. CPPs contacted patients who were taking aspirin for primary prevention by unscheduled telephone call to assess for aspirin adherence, undocumented history of ASCVD, cardiovascular risk factors, and history of bleeding. Aspirin was discontinued if patients met guideline criteria recommendations and agreed to discontinuation. Risk-benefit discussions were completed when patients without known ASCVD were considered high risk because the ACC/AHA guidelines mention there is insufficient evidence of safety and efficacy of aspirin for primary prevention for patients with other known ASCVD risk factors (eg, strong family history of premature myocardial infarction, inability to achieve lipid, blood pressure, or glucose targets, or significant elevation in coronary artery calcium score).
High risk was defined as family history of premature ASCVD (in a male first-degree relative aged < 55 years or a female first-degree relative aged < 65 years), most recent blood pressure or 2 blood pressure results in the last 12 months > 160/100 mm Hg, recent hemoglobin A1c > 9%, and/or low-density lipoprotein > 190 mg/dL or not prescribed an indicated statin.3 Aspirin was continued or discontinued according to patient preference after the personalized risk-benefit discussion.
For patients with a clinical indication for aspirin use other than ASCVD (eg, atrial fibrillation not on anticoagulation, venous thromboembolism prophylaxis, carotid artery disease), CPPs documented their assessment and when appropriate deferred to the PCP for consideration of stopping aspirin. For patients with undocumented ASCVD, CPPs added their ASCVD history to their problem list and aspirin was continued. PCPs were notified by alert when aspirin was discontinued and when patients could not be reached by telephone.
presented a review of recent guideline updates and supporting literature at 2 online staff meetings. The education sessions lasted about 10 minutes and were presented to PCPs across 3 community-based outpatient clinics. An estimated 40 minutes were spent creating the PowerPoint education materials, seeking feedback, making edits, and answering questions or emails from PCPs after the presentation. During the presentation, pharmacists encouraged PCPs to discontinue aspirin (active VA prescriptions and reported over-the-counter use) for primary prevention of ASCVD in patients aged ≥ 70 years during their upcoming appointments and consider risk factors recommended by the ACC/AHA guidelines when applicable. PCPs were notified that CPPs planned to start a population review for discontinuing active VA aspirin prescriptions on December 1, 2022. The primary endpoint and secondary endpoints were analyzed using descriptive statistics. All data were analyzed using Microsoft Excel.

Results
A total of 868 patients aged ≥ 70 years with active prescriptions for aspirin were identified on December 1, 2022. After applying inclusion and exclusion criteria for the pharmacist population review, 224 patients were included for cohort final analysis (Figure). All 868 patients were eligible for the CPP intervention. Primary reasons for exclusion from the CPP population included over-thecounter aspirin and a history of ASCVD in the patient’s problem list. All patients were male, with a mean (SD) age of 75 (4.4) years (Table 1). Most patients were prescribed aspirin, 81 mg daily (n = 220; 98%).

The direct CPP deprescribing intervention resulted in 2 aspirin prescriptions discontinued per hour of pharmacist time and 67 aspirin prescriptions discontinued per hour of pharmacist time via the PCP education intervention. CPPs discontinued 66 aspirin orders in the 12 weeks before the PCP education sessions. A total of 230 aspirin prescriptions were discontinued in the 12 weeks following the PCP education sessions, with 97 discontinued directly by CPPs and 133 discontinued by PCPs. The PCP education session yielded an additional 67 discontinued aspirin orders compared with the 12 weeks before the education sessions (Table 2).

The CPP direct deprescribing intervention took about 48.3 hours, accounting for health record review and time interacting with patients. The PCP education intervention took about 60 minutes, which included time for preparing and delivering education materials (Table 3). CPP deprescribing encounter types, interventions, and related subcategories, and other identified indications to continue aspirin are listed in Table 4.


Discussion
Compared with direct deprescribing by pharmacists, the PCP education intervention was more efficient based on number of aspirin orders discontinued by pharmacist time. PCPs discontinued twice as many aspirin prescriptions in the 12 weeks after pharmacist-led education compared with the 12 weeks before.
Patients were primarily contacted by telephone (73%) for deprescribing. Among the 163 patients reached by phone and encouraged to discontinue aspirin, 97 patients (60%) accepted the recommendation, which was similar to the acceptance rates found in the literature (48% to 55%).14,18 Although many veterans continued taking aspirin (78%), most had indications for its continued use, such as a history of ASCVD, atrial fibrillation without anticoagulation, and carotid artery stenosis, and complex comorbidities that required further discussion with their PCP. Less common uses for aspirin were identified through CPRS review or patient reports included cerebral small vessel disease without history of ASCVD, subclavian artery stenosis, thrombocytosis, bioprosthetic valve replacement, giant cell arteritis, rheumatoid arthritis, and prevention of second eye involvement of ischemic optic neuropathy.
to describe the benefit of clinical pharmacy services for deprescribing aspirin for primary prevention of ASCVD through PCP education. Previously published literature has assessed alternative ways to identify or discontinue PIMs—including aspirin—among geriatric patients. One study evaluated the use of marking inappropriate aspirin prescriptions in the electronic health database, leading to a significant reduction in incidence of inappropriate aspirin prescribing; however, it did not assess changes in discontinuation rates of existing aspirin prescriptions.19 The previous VA pharmacist aspirin deprescribing protocol demonstrated pharmacists’ aptitude at discontinuing aspirin for primary prevention but only used direct patient contact and did not compare efficiency with other methods, including PCP education.14
This quality improvement project contributes new data to the existing literature to support the use of clinical pharmacists to discontinue aspirin for primary prevention and suggests a strong role for pharmacists as educators on clinical guidelines, in addition to their roles directly deprescribing PIMs in clinical practice. This study is further strengthened by its use of VIONE, which previously has demonstrated effectiveness in deprescribing a variety of PIMs in primary care settings.20
Despite using VIONE for generating a list of patients eligible for deprescription, our CPRS review found that this list was frequently inaccurate. For example, a small portion of patients were on the VIONE generated list indicating they had no ASCVD history, but had transient ischemic attack listed in their problem lists. Patient problem lists often were missing documented ASCVD history that was revealed by patient interview or CPRS review. It is possible that patients interviewed might have omitted relevant ASCVD history because of low health literacy, conditions affecting memory, or use of health care services outside the VA system.
There were several instances of aspirin used for other non-ASCVD indications, such as primary stroke prevention in atrial fibrillation. The ACC/AHA atrial fibrillation guidelines previously provided a Class IIb recommendation (benefit is greater than risk but additional studies are needed) for considering no antithrombic therapy or treatment with oral anticoagulant or aspirin for nonvalvular atrial fibrillation with CHA2DS2-VASc (Congestive heart failure, Hypertension, Age [> 65 y, 1 point; > 75 y, 2 points], Diabetes, previous Stroke/transient ischemic attack [2 points]) score of 1.21 The ACC/ AHA guidelines were updated in 2023 to recommend against antiplatelet therapy as an alternative to anticoagulation for reducing cardioembolic stroke risk among patients with atrial fibrillation with no indication for antiplatelet therapy because of risk of harm.22 If a patient has no risk factors for stroke, aspirin is not recommended to prevent thromboembolic events because of a lack of benefit. Interventions from this quality improvement study were completed before the 2023 atrial fibrillation guideline was published and therefore in this study aspirin was not discontinued when used for atrial fibrillation. Aspirin use for atrial fibrillation might benefit from similar discontinuation efforts analyzed within this study. Beyond atrial fibrillation, major guidelines do not comment on the use of aspirin for any other indications in the absence of clinical ASCVD.
Limitations
This study is limited by the lack of clinical consensus for complex patients and demonstrates the importance of individualized patient assessment when considering discontinuing aspirin. Because of the project’s relatively short intervention period, aspirin deprescribing rates could decrease over time and repeated education efforts might be necessary to see lasting impact. Health care professionals from services outside of primary care also might have discontinued aspirin during the study period unrelated to the education and these discontinued aspirin prescriptions could contribute to the higher rate observed among PCPs. This study included a specific population cohort of male, US veterans and might not reflect other populations where these interventions could be implemented.
The measurement of time spent by pharmacists and PCPs is an additional limitation. Although it is expected that PCPs attempt to discontinue aspirin during their existing patient care appointments, the time spent during visits was not measured or documented. Direct deprescribing by pharmacist CPRS review required a significant amount of time and could be a barrier to successful intervention by CPPs in patient aligned care teams.
To reduce the time pharmacists spent completing CPRS reviews, an aspirin deprescribing clinical reminder tool could be used to assess use and appropriate indication quickly during any primary care visit led by a PCP or CPP. In addition, it is recommended that pharmacists regularly educate health care professionals on guideline recommendations for aspirin use among geriatric patients. Future studies of the incidence of major cardiovascular events after aspirin deprescribing among geriatric patients and a longitudinal cost/benefit analysis could support these initiatives.
Conclusions
In this study, pharmacists successfully deprescribed inappropriate medications, such as aspirin. However, pharmacist-led PCP education is more efficient compared with direct deprescribing using a population-level review. PCP education requires less time and could allow ambulatory care pharmacists to spend more time on other direct patient care interventions to improve quality and access to care in primary care clinics. This study’s results further support the role of pharmacists in deprescribing PIMs for older adults and the use of a deprescribing tool, such as VIONE, in a primary care setting.
- US Preventive Services Task Force; Davidson KW, Barry MJ, et al. Aspirin use to prevent cardiovascular disease: US Preventive Services Task Force recommendation statement. JAMA. 2022;327(16):1577-1584. doi:10.1001/jama.2022.4983
- McNeil JJ, Nelson MR, Woods RL, et al. Effect of aspirin on all-cause mortality in the healthy elderly. N Engl J Med. 2018;379(16):1519-1528. doi:10.1056/NEJMoa1803955
- Barry MJ, Wolff TA, Pbert L, et al. Putting evidence into practice: an update on the US Preventive Services Task Force methods for developing recommendations for preventive services. Ann Fam Med. 2023;21(2):165-171. doi:10.1370/afm.2946
- Arnett DK, Blumenthal RS, Albert MA, et al. 2019 ACC/ AHA Guideline on the Primary Prevention of Cardiovascular Disease: A report of the American College of Cardiology/ American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019;140(11):e596-e646. doi:10.1161/CIR.0000000000000678
- American Diabetes Association Professional Practice Committee. 10. Cardiovascular disease and risk management: Standards of care in diabetes-2024. Diabetes Care. 2024;47(Suppl 1):S179-S218. doi:10.2337/dc24-S010
- Ong SY, Chui P, Bhargava A, Justice A, Hauser RG. Estimating aspirin overuse for primary prevention of atherosclerotic cardiovascular disease (from a nationwide healthcare system). Am J Cardiol. 2020;137:25-30. doi:10.1016/j.amjcard.2020.09.042
- Weiss AJ, Jiang HJ. Overview of clinical conditions with frequent and costly hospital readmissions by payer, 2018. In: Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. Agency for Healthcare Research and Quality (US); July 20, 2021.
- Krishnaswami A, Steinman MA, Goyal P, et al. Deprescribing in older adults with cardiovascular disease. J Am Coll Cardiol. 2019;73(20):2584-2595. doi:10.1016/j.jacc.2019.03.467
- Association of American Medical Colleges. The complexities of physician supply and demand: projections from 2019 to 2034. Accessed March 17, 2024. https://www.aamc.org/media/54681/download
- US Department of Veterans Affairs, Veterans Health Administration. VHA Directive 1108.07(1): General pharmacy service requirements. November 28, 2022. Accessed March 17, 2024. https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=10045
- US Department of Veterans Affairs, Veterans Health Administration. VHA Handbook 1108.11(3): Clinical pharmacy services. July 1, 2015. Accessed March 17, 2024. https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=3120
- US Department of Veterans Affairs. Clinical pharmacist practitioner (CPP) to improve access to and quality of care August 2021. August 2021. Accessed May 19, 2023. https://www.pbm.va.gov/PBM/CPPO/Documents/ExternalFactSheet_OptimizingtheCPPToImproveAccess_508.pdf
- Ammerman CA, Simpkins BA, Warman N, Downs TN. Potentially inappropriate medications in older adults: Deprescribing with a clinical pharmacist. J Am Geriatr Soc. 2019;67(1):115-118. doi:10.1111/jgs.15623
- Rothbauer K, Siodlak M, Dreischmeier E, Ranola TS, Welch L. Evaluation of a pharmacist-driven ambulatory aspirin deprescribing protocol. Fed Pract. 2022;39(suppl 5):S37- S41a. doi:10.12788/fp.0294
- US Department of Veterans Affairs. VIONE changes the way VA handles prescriptions. January 25, 2020. Accessed May 21, 2023. https://news.va.gov/70709/vione-changes-way-va-handles-prescriptions/
- 2023 American Geriatrics Society Beers Criteria Update Expert Panel. American Geriatrics Society 2023 updated AGS Beers Criteria for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2023;71(7):2052- 2081. doi:10.1111/jgs.18372
- O’Mahony D, Cherubini A, Guiteras AR, et al. STOPP/ START criteria for potentially inappropriate prescribing in older people: version 3. Eur Geriatr Med. 2023;14(4):625- 632. doi:10.1007/s41999-023-00777-y
- Draeger C, Lodhi F, Geissinger N, Larson T, Griesbach S. Interdisciplinary deprescribing of aspirin through prescriber education and provision of patient-specific recommendations. WMJ. 2022;121(3):220-225
- de Lusignan S, Hinton W, Seidu S, et al. Dashboards to reduce inappropriate prescribing of metformin and aspirin: A quality assurance programme in a primary care sentinel network. Prim Care Diabetes. 2021;15(6):1075-1079. doi:10.1016/j.pcd.2021.06.003
- Nelson MW, Downs TN, Puglisi GM, Simpkins BA, Collier AS. Use of a deprescribing tool in an interdisciplinary primary-care patient-aligned care team. Sr Care Pharm. 2022;37(1):34-43. doi:10.4140/TCP.n.2022.34
- January CT, Wann LS, Alpert JS, et al. 2014 AHA/ ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines and the Heart Rhythm Society. Circulation. 2014;130(23):e199-e267. doi:10.1161/CIR.0000000000000041
- Joglar JA, Chung MK, Armbruster AL, et al. 2023 ACC/ AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines Circulation. 2024;149(1):e1- e156. doi:10.1161/CIR.0000000000001193
- US Preventive Services Task Force; Davidson KW, Barry MJ, et al. Aspirin use to prevent cardiovascular disease: US Preventive Services Task Force recommendation statement. JAMA. 2022;327(16):1577-1584. doi:10.1001/jama.2022.4983
- McNeil JJ, Nelson MR, Woods RL, et al. Effect of aspirin on all-cause mortality in the healthy elderly. N Engl J Med. 2018;379(16):1519-1528. doi:10.1056/NEJMoa1803955
- Barry MJ, Wolff TA, Pbert L, et al. Putting evidence into practice: an update on the US Preventive Services Task Force methods for developing recommendations for preventive services. Ann Fam Med. 2023;21(2):165-171. doi:10.1370/afm.2946
- Arnett DK, Blumenthal RS, Albert MA, et al. 2019 ACC/ AHA Guideline on the Primary Prevention of Cardiovascular Disease: A report of the American College of Cardiology/ American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019;140(11):e596-e646. doi:10.1161/CIR.0000000000000678
- American Diabetes Association Professional Practice Committee. 10. Cardiovascular disease and risk management: Standards of care in diabetes-2024. Diabetes Care. 2024;47(Suppl 1):S179-S218. doi:10.2337/dc24-S010
- Ong SY, Chui P, Bhargava A, Justice A, Hauser RG. Estimating aspirin overuse for primary prevention of atherosclerotic cardiovascular disease (from a nationwide healthcare system). Am J Cardiol. 2020;137:25-30. doi:10.1016/j.amjcard.2020.09.042
- Weiss AJ, Jiang HJ. Overview of clinical conditions with frequent and costly hospital readmissions by payer, 2018. In: Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. Agency for Healthcare Research and Quality (US); July 20, 2021.
- Krishnaswami A, Steinman MA, Goyal P, et al. Deprescribing in older adults with cardiovascular disease. J Am Coll Cardiol. 2019;73(20):2584-2595. doi:10.1016/j.jacc.2019.03.467
- Association of American Medical Colleges. The complexities of physician supply and demand: projections from 2019 to 2034. Accessed March 17, 2024. https://www.aamc.org/media/54681/download
- US Department of Veterans Affairs, Veterans Health Administration. VHA Directive 1108.07(1): General pharmacy service requirements. November 28, 2022. Accessed March 17, 2024. https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=10045
- US Department of Veterans Affairs, Veterans Health Administration. VHA Handbook 1108.11(3): Clinical pharmacy services. July 1, 2015. Accessed March 17, 2024. https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=3120
- US Department of Veterans Affairs. Clinical pharmacist practitioner (CPP) to improve access to and quality of care August 2021. August 2021. Accessed May 19, 2023. https://www.pbm.va.gov/PBM/CPPO/Documents/ExternalFactSheet_OptimizingtheCPPToImproveAccess_508.pdf
- Ammerman CA, Simpkins BA, Warman N, Downs TN. Potentially inappropriate medications in older adults: Deprescribing with a clinical pharmacist. J Am Geriatr Soc. 2019;67(1):115-118. doi:10.1111/jgs.15623
- Rothbauer K, Siodlak M, Dreischmeier E, Ranola TS, Welch L. Evaluation of a pharmacist-driven ambulatory aspirin deprescribing protocol. Fed Pract. 2022;39(suppl 5):S37- S41a. doi:10.12788/fp.0294
- US Department of Veterans Affairs. VIONE changes the way VA handles prescriptions. January 25, 2020. Accessed May 21, 2023. https://news.va.gov/70709/vione-changes-way-va-handles-prescriptions/
- 2023 American Geriatrics Society Beers Criteria Update Expert Panel. American Geriatrics Society 2023 updated AGS Beers Criteria for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2023;71(7):2052- 2081. doi:10.1111/jgs.18372
- O’Mahony D, Cherubini A, Guiteras AR, et al. STOPP/ START criteria for potentially inappropriate prescribing in older people: version 3. Eur Geriatr Med. 2023;14(4):625- 632. doi:10.1007/s41999-023-00777-y
- Draeger C, Lodhi F, Geissinger N, Larson T, Griesbach S. Interdisciplinary deprescribing of aspirin through prescriber education and provision of patient-specific recommendations. WMJ. 2022;121(3):220-225
- de Lusignan S, Hinton W, Seidu S, et al. Dashboards to reduce inappropriate prescribing of metformin and aspirin: A quality assurance programme in a primary care sentinel network. Prim Care Diabetes. 2021;15(6):1075-1079. doi:10.1016/j.pcd.2021.06.003
- Nelson MW, Downs TN, Puglisi GM, Simpkins BA, Collier AS. Use of a deprescribing tool in an interdisciplinary primary-care patient-aligned care team. Sr Care Pharm. 2022;37(1):34-43. doi:10.4140/TCP.n.2022.34
- January CT, Wann LS, Alpert JS, et al. 2014 AHA/ ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines and the Heart Rhythm Society. Circulation. 2014;130(23):e199-e267. doi:10.1161/CIR.0000000000000041
- Joglar JA, Chung MK, Armbruster AL, et al. 2023 ACC/ AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines Circulation. 2024;149(1):e1- e156. doi:10.1161/CIR.0000000000001193
Pharmacist-Led Deprescribing of Aspirin for Primary Prevention of Cardiovascular Disease Among Geriatric Veterans
Pharmacist-Led Deprescribing of Aspirin for Primary Prevention of Cardiovascular Disease Among Geriatric Veterans
Impact of NSAID Use on Bleeding Rates for Patients Taking Rivaroxaban or Apixaban
Impact of NSAID Use on Bleeding Rates for Patients Taking Rivaroxaban or Apixaban
Clinical practice has shifted from vitamin K antagonists to direct oral anticoagulants (DOACs) for atrial fibrillation treatment due to their more favorable risk-benefit profile and less lifestyle modification required.1,2 However, the advantage of a lower bleeding risk with DOACs could be compromised by potentially problematic pharmacokinetic interactions like those conferred by antiplatelets or nonsteroidal anti-inflammatory drugs (NSAIDs).3,4 Treating a patient needing anticoagulation with a DOAC who has comorbidities may introduce unavoidable drug-drug interactions. This particularly happens with over-the-counter and prescription NSAIDs used for the management of pain and inflammatory conditions.5
NSAIDs primarily affect 2 cyclooxygenase (COX) enzyme isomers, COX-1 and COX-2.6 COX-1 helps maintain gastrointestinal (GI) mucosa integrity and platelet aggregation processes, whereas COX-2 is engaged in pain signaling and inflammation mediation. COX-1 inhibition is associated with more bleeding-related adverse events (AEs), especially in the GI tract. COX-2 inhibition is thought to provide analgesia and anti-inflammatory properties without elevating bleeding risk. This premise is responsible for the preferential use of celecoxib, a COX-2 selective NSAID, which should confer a lower bleeding risk compared to nonselective NSAIDs such as ibuprofen and naproxen.7 NSAIDs have been documented as independent risk factors for bleeding. NSAID users are about 3 times as likely to develop GI AEs compared to nonNSAID users.8
Many clinicians aim to further mitigate NSAID-associated bleeding risk by coprescribing a proton pump inhibitor (PPI). PPIs provide gastroprotection against NSAID-induced mucosal injury and sequential complication of GI bleeding. In a multicenter randomized control trial, patients who received concomitant PPI therapy while undergoing chronic NSAID therapy—including nonselective and COX-2 selective NSAIDs—had a significantly lower risk of GI ulcer development (placebo, 17.0%; 20 mg esomeprazole, 5.2%; 40 mg esomeprazole, 4.6%).9 Current clinical guidelines for preventing NSAIDassociated bleeding complications recommend using a COX-2 selective NSAID in combination with PPI therapy for patients at high risk for GI-related bleeding, including the concomitant use of anticoagulants.10
There is evidence suggesting an increased bleeding risk with NSAIDs when used in combination with vitamin K antagonists such as warfarin.11,12 A systematic review of warfarin and concomitant NSAID use found an increased risk of overall bleeding with NSAID use in combination with warfarin (odds ratio 1.58; 95% CI, 1.18-2.12), compared to warfarin alone.12
Posthoc analyses of randomized clinical trials have also demonstrated an increased bleeding risk with oral anticoagulation and concomitant NSAID use.13,14 In the RE-LY trial, NSAID users on warfarin or dabigatran had a statistically significant increased risk of major bleeding compared to non-NSAID users (hazard ratio [HR] 1.68; 95% CI, 1.40- 2.02; P < .001).13 In the ARISTOTLE trial, patients on warfarin or apixaban who were incident NSAID users were found to have an increased risk of major bleeding (HR 1.61; 95% CI, 1.11-2.33) and clinically relevant nonmajor bleeding (HR 1.70; 95% CI, 1.16- 2.48).14 These trials found a statistically significant increased bleeding risk associated with NSAID use, though the populations evaluated included patients taking warfarin and patients taking DOACs. These trials did not evaluate the bleeding risk of concomitant NSAID use among DOACs alone.
Evidence on NSAID-associated bleeding risk with DOACs is lacking in settings where the patient population, prescribing practices, and monitoring levels are variable. Within the Veterans Health Administration, clinical pharmacist practitioners (CPPs) in anticoagulation clinics oversee DOAC therapy management. CPPs monitor safety and efficacy of DOAC therapies through a population health management tool, the DOAC Dashboard.15 The DOAC Dashboard creates alerts for patients who may require an intervention based on certain clinical parameters, such as drug-drug interactions.16 Whenever a patient on a DOAC is prescribed an NSAID, an alert is generated on the DOAC Dashboard to flag the CPPs for the potential need for an intervention. If NSAID therapy remains clinically indicated, CPPs may recommend risk reduction strategies such as a COX-2 selective NSAID or coprescribing a PPI.10
The DOAC Dashboard provides an ideal setting for investigating the effects of NSAID use, NSAID selectivity, and PPI coprescribing on DOAC bleeding rates. With an increasing population of patients receiving anticoagulation therapy with a DOAC, more guidance regarding the bleeding risk of concomitant NSAID use with DOACs is needed. Studies evaluating the bleeding risk with concomitant NSAID use in patients on a DOAC alone are limited. This is the first study to date to compare bleeding risk with concomitant NSAID use between DOACs. This study provides information on bleeding risk with NSAID use among commonly prescribed DOACs, rivaroxaban and apixaban, and the potential impacts of current risk reduction strategies.
METHODS
This single-center retrospective cohort review was performed using the electronic health records (EHRs) of patients enrolled in the US Department of Veterans Affairs (VA) Mountain Home Healthcare System who received rivaroxaban or apixaban from December 2020 to December 2022. This study received approval from the East Tennessee State University/VA Institutional Review Board committee.
Patients were identified through the DOAC Dashboard, aged 21 to 100 years, and received rivaroxaban or apixaban at a therapeutic dose: rivaroxaban 10 to 20 mg daily or apixaban 2.5 to 5 mg twice daily. Patients were excluded if they were prescribed dual antiplatelet therapy, received rivaroxaban at dosing indicated for peripheral vascular disease, were undergoing dialysis, had evidence of moderate to severe hepatic impairment or any hepatic disease with coagulopathy, were undergoing chemotherapy or radiation, or had hematological conditions with predisposed bleeding risk. These patients were excluded to mitigate the potential confounding impact from nontherapeutic DOAC dosing strategies and conditions associated with an increased bleeding risk.
Eligible patients were stratified based on NSAID use. NSAID users were defined as patients prescribed an oral NSAID, including both acute and chronic courses, at any point during the study time frame while actively on a DOAC. Bleeding events were reviewed to evaluate rates between rivaroxaban and apixaban among NSAID and nonNSAID users. Identified NSAID users were further assessed for NSAID selectivity and PPI coprescribing as a subgroup analysis for the secondary assessment.
Data Collection
Baseline data were collected, including age, body mass index, anticoagulation indication, DOAC agent, DOAC dose, and DOAC total daily dose. Baseline serum creatinine levels, liver function tests, hemoglobin levels, and platelet counts were collected from the most recent data available immediately prior to the bleeding event, if applicable.
The DOAC Dashboard was reviewed for active and dismissed drug interaction alerts to identify patients taking rivaroxaban or apixaban who were prescribed an NSAID. Patients were categorized in the NSAID group if an interacting drug alert with an NSAID was reported during the study time frame. Data available through the interacting drug alerts on NSAID use were limited to the interacting drug name and date of the reported flag. Manual EHR review was required to confirm dates of NSAID therapy initiation and NSAID discontinuation, if applicable.
Data regarding concomitant antiplatelet use were obtained through review of the active and dismissed drug interaction alerts on the DOAC Dashboard. Concomitant antiplatelet use was defined as the prescribing of a single antiplatelet agent at any point while receiving DOAC therapy. Data on concomitant antiplatelets were collected regardless of NSAID status.
Data on coprescribed PPI therapy were obtained through manual EHR review of identified NSAID users. Coprescribed PPI therapy was defined as the prescribing of a PPI at any point during NSAID therapy. Data regarding PPI use among non-NSAID users were not collected because the secondary endpoint was designed to assess PPI use only among patients coprescribed a DOAC and NSAID.
Outcomes
Bleeding events were identified through an outcomes report generated by the DOAC Dashboard based on International Classification of Diseases, Tenth Revision diagnosis codes associated with a bleeding event. The outcomes report captures diagnoses from the outpatient and inpatient care settings. Reported bleeding events were limited to patients who received a DOAC at any point in the 6 months prior to the event and excluded patients with recent DOAC initiation within 7 days of the event, as these patients are not captured on the DOAC Dashboard.
All reported bleeding events were manually reviewed in the EHR and categorized as a major or clinically relevant nonmajor bleed, according to International Society of Thrombosis and Haemostasis criteria. Validated bleeding events were then crossreferenced with the interacting drug alerts report to identify events with potentially overlapping NSAID therapy at the time of the event. Overlapping NSAID therapy was defined as the prescribing of an NSAID at any point in the 6 months prior to the event. All events with potential overlapping NSAID therapies were manually reviewed for confirmation of NSAID status at the time of the event.
The primary endpoint was a composite of any bleeding event per International Society of Thrombosis and Haemostasis criteria. The secondary endpoint evaluated the potential impact of NSAID selectivity or PPI coprescribing on the bleeding rate among the NSAID user groups.
Statistical Analysis
Analyses were performed consistent with the methods used in the ARISTOTLE and RE-LY trials. It was determined that a sample size of 504 patients, with ≥ 168 patients in each group, would provide 80% power using a 2-sided a of 0.05. HRs with 95% CIs and respective P values were calculated using a SPSS-adapted online calculator.
RESULTS
The DOAC Dashboard identified 681 patients on rivaroxaban and 3225 patients on apixaban; 72 patients on rivaroxaban (10.6%) and 300 patients on apixaban (9.3%) were NSAID users. The mean age of NSAID users was 66.9 years in the rivaroxaban group and 72.4 years in the apixaban group. The mean age of non-NSAID users was 71.5 years in the rivaroxaban group and 75.6 years in the apixaban group. No appreciable differences were observed among subgroups in body mass index, renal function, hepatic function, hemoglobin, or platelet counts, and no statistically significant differences were identified (Table 1). Antiplatelet agents identified included aspirin, clopidogrel, prasugrel, and ticagrelor. Fifteen patients (20.3%) in the rivaroxaban group and 87 patients (28.7%) in the apixaban group had concomitant antiplatelet and NSAID use. Forty-five patients on rivaroxaban (60.8%) and 170 (55.9%) on apixaban were prescribed concomitant PPI and NSAID at baseline. Among non-NSAID users, there was concomitant antiplatelet use for 265 patients (43.6%) in the rivaroxaban group and 1401 patients (47.9%) in the apixaban group. Concomitant PPI use was identified among 63 patients (60.0%) taking selective NSAIDs and 182 (57.2%) taking nonselective NSAIDs.

A total of 423 courses of NSAIDs were identified: 85 NSAID courses in the rivaroxaban group and 338 NSAID courses in the apixaban group. Most NSAID courses involved a nonselective NSAID in the rivaroxaban and apixaban NSAID user groups: 75.2% (n = 318) aggregately compared to 71.8% (n = 61) and 76.0% (n = 257) in the rivaroxaban and apixaban groups, respectively. The most frequent NSAID courses identified were meloxicam (26.7%; n = 113), celecoxib (24.8%; n = 105), ibuprofen (19.1%; n = 81), and naproxen (13.5%; n = 57). Data regarding NSAID therapy initiation and discontinuation dates were not readily available. As a result, the duration of NSAID courses was not captured.
There was no statistically significant difference in bleeding rates between rivaroxaban and apixaban among NSAID users (HR 1.04; 95% CI, 0.98-1.12) or non-NSAID users (HR 1.15; 95% CI, 0.80-1.66) (Table 2). Apixaban non-NSAID users had a higher rate of major bleeds (HR 0.32; 95% CI, 0.17-0.61) while rivaroxaban non-NSAID users had a higher rate of clinically relevant nonmajor bleeds (HR 1.63; 95% CI, 1.10-2.54).

The sample size for the secondary endpoint consisted of bleeding events that were confirmed to have had an overlapping NSAID prescribed at the time of the event. For this secondary assessment, there was 1 rivaroxaban NSAID user bleeding event and 4 apixaban NSAID user bleeding events. For the rivaroxaban NSAID user bleeding event, the NSAID was nonselective and a PPI was not coprescribed. For the apixaban NSAID user bleeding events, 2 NSAIDs were nonselective and 2 were selective. All patients with apixaban and NSAID bleeding events had a coprescribed PPI. There was no clinically significant difference in the bleeding rates observed for NSAID selectivity or PPI coprescribing among the NSAID user subgroups.
DISCUSSION
This study found that there was no statistically significant difference for bleeding rates of major and nonmajor bleeding events between rivaroxaban and apixaban among NSAID users and non-NSAID users. This study did not identify a clinically significant impact on bleeding rates from NSAID selectivity or PPI coprescribing among the NSAID users.
There were notable but not statistically significant differences in baseline characteristics observed between the NSAID and non-NSAID user groups. On average, the rivaroxaban and apixaban NSAID users were younger compared with those not taking NSAIDs. NSAIDs, specifically nonselective NSAIDs, are recognized as potentially inappropriate medications for older adults given that this population is at an increased risk for GI ulcer development and/or GI bleeding.17 The non-NSAID user group likely consisted of older patients compared to the NSAID user group as clinicians may avoid prescribing NSAIDs to older adults regardless of concomitant DOAC therapy.
In addition to having an older patient population, non-NSAID users were more frequently prescribed a concomitant antiplatelet when compared with NSAID users. This prescribing pattern may be due to clinicians avoiding the use of NSAIDs in patients receiving DOAC therapy in combination with antiplatelet therapy, as these patients have been found to have an increased bleeding rate compared to DOAC therapy alone.18
Non-NSAID users had an overall higher bleeding rate for both major and nonmajor bleeding events. Based on this observation, it could be hypothesized that antiplatelet agents have a higher risk of bleeding in comparison to NSAIDs. In a subanalysis of the EXPAND study evaluating risk factors of major bleeding in patients receiving rivaroxaban, concomitant use of antiplatelet agents demonstrated a statistically significant increased risk of bleeding (HR 1.6; 95% CI, 1.2-2.3; P = .003) while concomitant use of NSAIDs did not (HR 0.8; 95% CI, 0.3-2.2; P = .67).19
In assessing PPI status at baseline, a majority of both rivaroxaban and apixaban NSAID users were coprescribed a PPI. This trend aligns with current clinical guideline recommendations for the prescribing of PPI therapy for GI protection in high-risk patients, such as those on DOAC therapy and concomitant NSAID therapy.10 Given the high proportion of NSAID users coprescribed a PPI at baseline, it may be possible that the true incidence of NSAID-associated bleeding events was higher than what this study found. This observation may reflect the impact from timely implementation of risk mitigation strategies by CPPs in the anticoagulation clinic. However, this study was not constructed to assess the efficacy of PPI use in this manner.
It is important to note the patients included in this study were followed by a pharmacist in an anticoagulation clinic using the DOAC Dashboard.15 This population management tool allows CPPs to make proactive interventions when a patient taking a DOAC receives an NSAID prescription, such as recommending the coprescribing of a PPI or use of a selective NSAID.10,16 These standards of care may have contributed to an overall reduced bleeding rate among the NSAID user group and may not be reflective of private practice.
The planned analysis of this study was modeled after the posthoc analysis of the RE-LY and ARISTOTLE trials. Both trials demonstrated an increased risk of bleeding with oral anticoagulation, including DOAC and warfarin, in combination with NSAID use. However, both trials found that NSAID use in patients treated with a DOAC was not independently associated with increased bleeding events compared with warfarin.13,14 The results of this study are comparable to the RE-LY and ARISTOTLE findings that NSAID use among patients treated with rivaroxaban or apixaban did not demonstrate a statistically significant increased bleeding risk.
Studies of NSAID use in combination with DOAC therapy have been limited to patient populations consisting of both DOAC and warfarin. Evidence from these trials outlines the increased bleeding risk associated with NSAID use in combination with oral anticoagulation; however, these patient populations include those on a DOAC and warfarin.13,14,19,20 Given the limited evidence on NSAID use among DOACs alone, it is assumed NSAID use in combination with DOACs has a similar risk of bleeding as warfarin use. This may cause clinicians to automatically exclude NSAID therapy as a treatment option for patients on a DOAC who are otherwise clinically appropriate candidates, such as those with underlying inflammatory conditions. Avoiding NSAID therapy in this patient population may lead to suboptimal pain management and increase the risk of patient harm from methods such as inappropriate opioid therapy prescribing.
DOAC therapy should not be a universal limitation to the use of NSAIDs. Although the risk of bleeding with NSAID therapy is always present, deliberate NSAID prescribing in addition to the timely implementation of risk mitigation strategies may provide an avenue for safe NSAID prescribing in patients receiving a DOAC. A population health-based approach to DOAC management, such as the DOAC Dashboard, appears to be effective at preventing patient harm when NSAIDs are prescribed in conjunction with DOACs.
Limitations
The DOAC Dashboard has been shown to be effective and efficient at monitoring DOAC therapy from a population-based approach.16 Reports generated through the DOAC Dashboard provide convenient access to patient data which allows for timely interventions; however, there are limits to its use for data collection. All the data elements necessary to properly assess bleeding risk with validated tools, such as HAS-BLED (hypertension, abnormal renal/liver function, stroke, bleeding history or predisposition, labile international normalized ratio, elderly, drugs/ alcohol concomitantly), are not available on DOAC Dashboard reports. Due to this constraint, bleeding risk assessments were not conducted at baseline and this study was unable to include risk modeling. Additionally, data elements like initiation and discontinuation dates and duration of therapies were not readily available. As a result, this study was unable to incorporate time as a data point.
This was a retrospective study that relied on manual review of chart documentation to verify bleeding events, but data obtained through the DOAC Dashboard were transferred directly from the EHR.15 Bleeding events available for evaluation were restricted to those that occurred at a VA facility. Additionally, the sample size within the rivaroxaban NSAID user group did not reach the predefined sample size required to reach power and may have been too small to detect a difference if one did exist. The secondary assessment had a low sample size of NSAID user bleeding events, making it difficult to fully assess its impact on NSAID selectivity and PPI coprescribing on bleeding rates. All courses of NSAIDs were equally valued regardless of the dose or therapy duration; however, this is consistent with how NSAID use was defined in the RE-LY and ARISTOTLE trials.
CONCLUSIONS
This retrospective cohort review found no statistically significant difference in the composite bleeding rates between rivaroxaban and apixaban among NSAID users and non-NSAID users. Moreover, there was no clinically significant impact observed for bleeding rates in regard to NSAID selectivity and PPI coprescribing among NSAID users. However, coprescribing of PPI therapy to patients on a DOAC who are clinically indicated for an NSAID may reduce the risk of bleeding. Population health management tools, such as the DOAC Dashboard, may also allow clinicians to safely prescribe NSAIDs to patients on a DOAC. Further large-scale observational studies are needed to quantify the real-world risk of bleeding with concomitant NSAID use among DOACs alone and to evaluate the impact from NSAID selectivity or PPI coprescribing.
- Ruff CT, Giugliano RP, Braunwald E, et al. Comparison of the efficacy and safety of new oral anticoagulants with warfarin in patients with atrial fibrillation: a meta-analysis of randomised trials. Lancet. 2014;383(9921):955-962. doi:10.1016/S0140-6736(13)62343-0
- Ageno W, Gallus AS, Wittkowsky A, Crowther M, Hylek EM, Palareti G. Oral anticoagulant therapy: antithrombotic therapy and prevention of thrombosis, 9th ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines. Chest. 2012;141(2 Suppl):e44S-e88S. doi:10.1378/chest.11-2292
- Eikelboom J, Merli G. Bleeding with direct oral anticoagulants vs warfarin: clinical experience. Am J Med. 2016;129(11S):S33-S40. doi:10.1016/j.amjmed.2016.06.003
- Vranckx P, Valgimigli M, Heidbuchel H. The significance of drug-drug and drug-food interactions of oral anticoagulation. Arrhythm Electrophysiol Rev. 2018;7(1):55-61. doi:10.15420/aer.2017.50.1
- Davis JS, Lee HY, Kim J, et al. Use of non-steroidal antiinflammatory drugs in US adults: changes over time and by demographic. Open Heart. 2017;4(1):e000550. doi:10.1136/openhrt-2016-000550
- Schafer AI. Effects of nonsteroidal antiinflammatory drugs on platelet function and systemic hemostasis. J Clin Pharmacol. 1995;35(3):209-219. doi:10.1002/j.1552-4604.1995.tb04050.x
- Al-Saeed A. Gastrointestinal and cardiovascular risk of nonsteroidal anti-inflammatory drugs. Oman Med J. 2011;26(6):385-391. doi:10.5001/omj.2011.101
- Gabriel SE, Jaakkimainen L, Bombardier C. Risk for serious gastrointestinal complications related to use of nonsteroidal anti-inflammatory drugs. Ann Intern Med. 1991;115(10):787-796. doi:10.7326/0003-4819-115-10-787
- Scheiman JM, Yeomans ND, Talley NJ, et al. Prevention of ulcers by esomeprazole in at-risk patients using non-selective NSAIDs and COX-2 inhibitors. Am J Gastroenterol. 2006;101(4):701-710. doi:10.1111/j.1572-0241.2006.00499.x
- Freedberg DE, Kim LS, Yang YX. The risks and benefits of long-term use of proton pump inhibitors: expert review and best practice advice from the American Gastroenterological Association. Gastroenterology. 2017;152(4):706-715. doi:10.1053/j.gastro.2017.01.031
- Lamberts M, Lip GYH, Hansen ML, et al. Relation of nonsteroidal anti-inflammatory drugs to serious bleeding and thromboembolism risk in patients with atrial fibrillation receiving antithrombotic therapy: a nationwide cohort study. Ann Intern Med. 2014;161(10):690-698. doi:10.7326/M13-1581
- Villa Zapata L, Hansten PD, Panic J, et al. Risk of bleeding with exposure to warfarin and nonsteroidal anti-inflammatory drugs: a systematic review and metaanalysis. Thromb Haemost. 2020;120(7):1066-1074. doi:10.1055/s-0040-1710592
- Kent AP, Brueckmann M, Fraessdorf M, et al. Concomitant oral anticoagulant and nonsteroidal anti-inflammatory drug therapy in patients with atrial fibrillation. J Am Coll Cardiol. 2018;72(3):255-267. doi:10.1016/j.jacc.2018.04.063
- Dalgaard F, Mulder H, Wojdyla DM, et al. Patients with atrial fibrillation taking nonsteroidal antiinflammatory drugs and oral anticoagulants in the ARISTOTLE Trial. Circulation. 2020;141(1):10-20. doi:10.1161/CIRCULATIONAHA.119.041296
- Allen AL, Lucas J, Parra D, et al. Shifting the paradigm: a population health approach to the management of direct oral anticoagulants. J Am Heart Asssoc. 2021;10(24):e022758. doi:10.1161/JAHA.121.022758
- . Valencia D, Spoutz P, Stoppi J, et al. Impact of a direct oral anticoagulant population management tool on anticoagulation therapy monitoring in clinical practice. Ann Pharmacother. 2019;53(8):806-811. doi:10.1177/1060028019835843
- By the 2023 American Geriatrics Society Beers Criteria® Update Expert Panel. American Geriatrics Society 2023 Updated AGS Beers Criteria® for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2023;71(7):2052-2081. doi:10.1111/jgs.18372
- Kumar S, Danik SB, Altman RK, et al. Non-vitamin K antagonist oral anticoagulants and antiplatelet therapy for stroke prevention in patients with atrial fibrillation. Cardiol Rev. 2016;24(5):218-223. doi:10.1097/CRD.0000000000000088
- Sakuma I, Uchiyama S, Atarashi H, et al. Clinical risk factors of stroke and major bleeding in patients with nonvalvular atrial fibrillation under rivaroxaban: the EXPAND study sub-analysis. Heart Vessels. 2019;34(11):1839-1851. doi:10.1007/s00380-019-01425-x
- Davidson BL, Verheijen S, Lensing AWA, et al. Bleeding risk of patients with acute venous thromboembolism taking nonsteroidal anti-inflammatory drugs or aspirin. JAMA Intern Med. 2014;174(6):947-953. doi:10.1001/jamainternmed.2014.946
Clinical practice has shifted from vitamin K antagonists to direct oral anticoagulants (DOACs) for atrial fibrillation treatment due to their more favorable risk-benefit profile and less lifestyle modification required.1,2 However, the advantage of a lower bleeding risk with DOACs could be compromised by potentially problematic pharmacokinetic interactions like those conferred by antiplatelets or nonsteroidal anti-inflammatory drugs (NSAIDs).3,4 Treating a patient needing anticoagulation with a DOAC who has comorbidities may introduce unavoidable drug-drug interactions. This particularly happens with over-the-counter and prescription NSAIDs used for the management of pain and inflammatory conditions.5
NSAIDs primarily affect 2 cyclooxygenase (COX) enzyme isomers, COX-1 and COX-2.6 COX-1 helps maintain gastrointestinal (GI) mucosa integrity and platelet aggregation processes, whereas COX-2 is engaged in pain signaling and inflammation mediation. COX-1 inhibition is associated with more bleeding-related adverse events (AEs), especially in the GI tract. COX-2 inhibition is thought to provide analgesia and anti-inflammatory properties without elevating bleeding risk. This premise is responsible for the preferential use of celecoxib, a COX-2 selective NSAID, which should confer a lower bleeding risk compared to nonselective NSAIDs such as ibuprofen and naproxen.7 NSAIDs have been documented as independent risk factors for bleeding. NSAID users are about 3 times as likely to develop GI AEs compared to nonNSAID users.8
Many clinicians aim to further mitigate NSAID-associated bleeding risk by coprescribing a proton pump inhibitor (PPI). PPIs provide gastroprotection against NSAID-induced mucosal injury and sequential complication of GI bleeding. In a multicenter randomized control trial, patients who received concomitant PPI therapy while undergoing chronic NSAID therapy—including nonselective and COX-2 selective NSAIDs—had a significantly lower risk of GI ulcer development (placebo, 17.0%; 20 mg esomeprazole, 5.2%; 40 mg esomeprazole, 4.6%).9 Current clinical guidelines for preventing NSAIDassociated bleeding complications recommend using a COX-2 selective NSAID in combination with PPI therapy for patients at high risk for GI-related bleeding, including the concomitant use of anticoagulants.10
There is evidence suggesting an increased bleeding risk with NSAIDs when used in combination with vitamin K antagonists such as warfarin.11,12 A systematic review of warfarin and concomitant NSAID use found an increased risk of overall bleeding with NSAID use in combination with warfarin (odds ratio 1.58; 95% CI, 1.18-2.12), compared to warfarin alone.12
Posthoc analyses of randomized clinical trials have also demonstrated an increased bleeding risk with oral anticoagulation and concomitant NSAID use.13,14 In the RE-LY trial, NSAID users on warfarin or dabigatran had a statistically significant increased risk of major bleeding compared to non-NSAID users (hazard ratio [HR] 1.68; 95% CI, 1.40- 2.02; P < .001).13 In the ARISTOTLE trial, patients on warfarin or apixaban who were incident NSAID users were found to have an increased risk of major bleeding (HR 1.61; 95% CI, 1.11-2.33) and clinically relevant nonmajor bleeding (HR 1.70; 95% CI, 1.16- 2.48).14 These trials found a statistically significant increased bleeding risk associated with NSAID use, though the populations evaluated included patients taking warfarin and patients taking DOACs. These trials did not evaluate the bleeding risk of concomitant NSAID use among DOACs alone.
Evidence on NSAID-associated bleeding risk with DOACs is lacking in settings where the patient population, prescribing practices, and monitoring levels are variable. Within the Veterans Health Administration, clinical pharmacist practitioners (CPPs) in anticoagulation clinics oversee DOAC therapy management. CPPs monitor safety and efficacy of DOAC therapies through a population health management tool, the DOAC Dashboard.15 The DOAC Dashboard creates alerts for patients who may require an intervention based on certain clinical parameters, such as drug-drug interactions.16 Whenever a patient on a DOAC is prescribed an NSAID, an alert is generated on the DOAC Dashboard to flag the CPPs for the potential need for an intervention. If NSAID therapy remains clinically indicated, CPPs may recommend risk reduction strategies such as a COX-2 selective NSAID or coprescribing a PPI.10
The DOAC Dashboard provides an ideal setting for investigating the effects of NSAID use, NSAID selectivity, and PPI coprescribing on DOAC bleeding rates. With an increasing population of patients receiving anticoagulation therapy with a DOAC, more guidance regarding the bleeding risk of concomitant NSAID use with DOACs is needed. Studies evaluating the bleeding risk with concomitant NSAID use in patients on a DOAC alone are limited. This is the first study to date to compare bleeding risk with concomitant NSAID use between DOACs. This study provides information on bleeding risk with NSAID use among commonly prescribed DOACs, rivaroxaban and apixaban, and the potential impacts of current risk reduction strategies.
METHODS
This single-center retrospective cohort review was performed using the electronic health records (EHRs) of patients enrolled in the US Department of Veterans Affairs (VA) Mountain Home Healthcare System who received rivaroxaban or apixaban from December 2020 to December 2022. This study received approval from the East Tennessee State University/VA Institutional Review Board committee.
Patients were identified through the DOAC Dashboard, aged 21 to 100 years, and received rivaroxaban or apixaban at a therapeutic dose: rivaroxaban 10 to 20 mg daily or apixaban 2.5 to 5 mg twice daily. Patients were excluded if they were prescribed dual antiplatelet therapy, received rivaroxaban at dosing indicated for peripheral vascular disease, were undergoing dialysis, had evidence of moderate to severe hepatic impairment or any hepatic disease with coagulopathy, were undergoing chemotherapy or radiation, or had hematological conditions with predisposed bleeding risk. These patients were excluded to mitigate the potential confounding impact from nontherapeutic DOAC dosing strategies and conditions associated with an increased bleeding risk.
Eligible patients were stratified based on NSAID use. NSAID users were defined as patients prescribed an oral NSAID, including both acute and chronic courses, at any point during the study time frame while actively on a DOAC. Bleeding events were reviewed to evaluate rates between rivaroxaban and apixaban among NSAID and nonNSAID users. Identified NSAID users were further assessed for NSAID selectivity and PPI coprescribing as a subgroup analysis for the secondary assessment.
Data Collection
Baseline data were collected, including age, body mass index, anticoagulation indication, DOAC agent, DOAC dose, and DOAC total daily dose. Baseline serum creatinine levels, liver function tests, hemoglobin levels, and platelet counts were collected from the most recent data available immediately prior to the bleeding event, if applicable.
The DOAC Dashboard was reviewed for active and dismissed drug interaction alerts to identify patients taking rivaroxaban or apixaban who were prescribed an NSAID. Patients were categorized in the NSAID group if an interacting drug alert with an NSAID was reported during the study time frame. Data available through the interacting drug alerts on NSAID use were limited to the interacting drug name and date of the reported flag. Manual EHR review was required to confirm dates of NSAID therapy initiation and NSAID discontinuation, if applicable.
Data regarding concomitant antiplatelet use were obtained through review of the active and dismissed drug interaction alerts on the DOAC Dashboard. Concomitant antiplatelet use was defined as the prescribing of a single antiplatelet agent at any point while receiving DOAC therapy. Data on concomitant antiplatelets were collected regardless of NSAID status.
Data on coprescribed PPI therapy were obtained through manual EHR review of identified NSAID users. Coprescribed PPI therapy was defined as the prescribing of a PPI at any point during NSAID therapy. Data regarding PPI use among non-NSAID users were not collected because the secondary endpoint was designed to assess PPI use only among patients coprescribed a DOAC and NSAID.
Outcomes
Bleeding events were identified through an outcomes report generated by the DOAC Dashboard based on International Classification of Diseases, Tenth Revision diagnosis codes associated with a bleeding event. The outcomes report captures diagnoses from the outpatient and inpatient care settings. Reported bleeding events were limited to patients who received a DOAC at any point in the 6 months prior to the event and excluded patients with recent DOAC initiation within 7 days of the event, as these patients are not captured on the DOAC Dashboard.
All reported bleeding events were manually reviewed in the EHR and categorized as a major or clinically relevant nonmajor bleed, according to International Society of Thrombosis and Haemostasis criteria. Validated bleeding events were then crossreferenced with the interacting drug alerts report to identify events with potentially overlapping NSAID therapy at the time of the event. Overlapping NSAID therapy was defined as the prescribing of an NSAID at any point in the 6 months prior to the event. All events with potential overlapping NSAID therapies were manually reviewed for confirmation of NSAID status at the time of the event.
The primary endpoint was a composite of any bleeding event per International Society of Thrombosis and Haemostasis criteria. The secondary endpoint evaluated the potential impact of NSAID selectivity or PPI coprescribing on the bleeding rate among the NSAID user groups.
Statistical Analysis
Analyses were performed consistent with the methods used in the ARISTOTLE and RE-LY trials. It was determined that a sample size of 504 patients, with ≥ 168 patients in each group, would provide 80% power using a 2-sided a of 0.05. HRs with 95% CIs and respective P values were calculated using a SPSS-adapted online calculator.
RESULTS
The DOAC Dashboard identified 681 patients on rivaroxaban and 3225 patients on apixaban; 72 patients on rivaroxaban (10.6%) and 300 patients on apixaban (9.3%) were NSAID users. The mean age of NSAID users was 66.9 years in the rivaroxaban group and 72.4 years in the apixaban group. The mean age of non-NSAID users was 71.5 years in the rivaroxaban group and 75.6 years in the apixaban group. No appreciable differences were observed among subgroups in body mass index, renal function, hepatic function, hemoglobin, or platelet counts, and no statistically significant differences were identified (Table 1). Antiplatelet agents identified included aspirin, clopidogrel, prasugrel, and ticagrelor. Fifteen patients (20.3%) in the rivaroxaban group and 87 patients (28.7%) in the apixaban group had concomitant antiplatelet and NSAID use. Forty-five patients on rivaroxaban (60.8%) and 170 (55.9%) on apixaban were prescribed concomitant PPI and NSAID at baseline. Among non-NSAID users, there was concomitant antiplatelet use for 265 patients (43.6%) in the rivaroxaban group and 1401 patients (47.9%) in the apixaban group. Concomitant PPI use was identified among 63 patients (60.0%) taking selective NSAIDs and 182 (57.2%) taking nonselective NSAIDs.

A total of 423 courses of NSAIDs were identified: 85 NSAID courses in the rivaroxaban group and 338 NSAID courses in the apixaban group. Most NSAID courses involved a nonselective NSAID in the rivaroxaban and apixaban NSAID user groups: 75.2% (n = 318) aggregately compared to 71.8% (n = 61) and 76.0% (n = 257) in the rivaroxaban and apixaban groups, respectively. The most frequent NSAID courses identified were meloxicam (26.7%; n = 113), celecoxib (24.8%; n = 105), ibuprofen (19.1%; n = 81), and naproxen (13.5%; n = 57). Data regarding NSAID therapy initiation and discontinuation dates were not readily available. As a result, the duration of NSAID courses was not captured.
There was no statistically significant difference in bleeding rates between rivaroxaban and apixaban among NSAID users (HR 1.04; 95% CI, 0.98-1.12) or non-NSAID users (HR 1.15; 95% CI, 0.80-1.66) (Table 2). Apixaban non-NSAID users had a higher rate of major bleeds (HR 0.32; 95% CI, 0.17-0.61) while rivaroxaban non-NSAID users had a higher rate of clinically relevant nonmajor bleeds (HR 1.63; 95% CI, 1.10-2.54).

The sample size for the secondary endpoint consisted of bleeding events that were confirmed to have had an overlapping NSAID prescribed at the time of the event. For this secondary assessment, there was 1 rivaroxaban NSAID user bleeding event and 4 apixaban NSAID user bleeding events. For the rivaroxaban NSAID user bleeding event, the NSAID was nonselective and a PPI was not coprescribed. For the apixaban NSAID user bleeding events, 2 NSAIDs were nonselective and 2 were selective. All patients with apixaban and NSAID bleeding events had a coprescribed PPI. There was no clinically significant difference in the bleeding rates observed for NSAID selectivity or PPI coprescribing among the NSAID user subgroups.
DISCUSSION
This study found that there was no statistically significant difference for bleeding rates of major and nonmajor bleeding events between rivaroxaban and apixaban among NSAID users and non-NSAID users. This study did not identify a clinically significant impact on bleeding rates from NSAID selectivity or PPI coprescribing among the NSAID users.
There were notable but not statistically significant differences in baseline characteristics observed between the NSAID and non-NSAID user groups. On average, the rivaroxaban and apixaban NSAID users were younger compared with those not taking NSAIDs. NSAIDs, specifically nonselective NSAIDs, are recognized as potentially inappropriate medications for older adults given that this population is at an increased risk for GI ulcer development and/or GI bleeding.17 The non-NSAID user group likely consisted of older patients compared to the NSAID user group as clinicians may avoid prescribing NSAIDs to older adults regardless of concomitant DOAC therapy.
In addition to having an older patient population, non-NSAID users were more frequently prescribed a concomitant antiplatelet when compared with NSAID users. This prescribing pattern may be due to clinicians avoiding the use of NSAIDs in patients receiving DOAC therapy in combination with antiplatelet therapy, as these patients have been found to have an increased bleeding rate compared to DOAC therapy alone.18
Non-NSAID users had an overall higher bleeding rate for both major and nonmajor bleeding events. Based on this observation, it could be hypothesized that antiplatelet agents have a higher risk of bleeding in comparison to NSAIDs. In a subanalysis of the EXPAND study evaluating risk factors of major bleeding in patients receiving rivaroxaban, concomitant use of antiplatelet agents demonstrated a statistically significant increased risk of bleeding (HR 1.6; 95% CI, 1.2-2.3; P = .003) while concomitant use of NSAIDs did not (HR 0.8; 95% CI, 0.3-2.2; P = .67).19
In assessing PPI status at baseline, a majority of both rivaroxaban and apixaban NSAID users were coprescribed a PPI. This trend aligns with current clinical guideline recommendations for the prescribing of PPI therapy for GI protection in high-risk patients, such as those on DOAC therapy and concomitant NSAID therapy.10 Given the high proportion of NSAID users coprescribed a PPI at baseline, it may be possible that the true incidence of NSAID-associated bleeding events was higher than what this study found. This observation may reflect the impact from timely implementation of risk mitigation strategies by CPPs in the anticoagulation clinic. However, this study was not constructed to assess the efficacy of PPI use in this manner.
It is important to note the patients included in this study were followed by a pharmacist in an anticoagulation clinic using the DOAC Dashboard.15 This population management tool allows CPPs to make proactive interventions when a patient taking a DOAC receives an NSAID prescription, such as recommending the coprescribing of a PPI or use of a selective NSAID.10,16 These standards of care may have contributed to an overall reduced bleeding rate among the NSAID user group and may not be reflective of private practice.
The planned analysis of this study was modeled after the posthoc analysis of the RE-LY and ARISTOTLE trials. Both trials demonstrated an increased risk of bleeding with oral anticoagulation, including DOAC and warfarin, in combination with NSAID use. However, both trials found that NSAID use in patients treated with a DOAC was not independently associated with increased bleeding events compared with warfarin.13,14 The results of this study are comparable to the RE-LY and ARISTOTLE findings that NSAID use among patients treated with rivaroxaban or apixaban did not demonstrate a statistically significant increased bleeding risk.
Studies of NSAID use in combination with DOAC therapy have been limited to patient populations consisting of both DOAC and warfarin. Evidence from these trials outlines the increased bleeding risk associated with NSAID use in combination with oral anticoagulation; however, these patient populations include those on a DOAC and warfarin.13,14,19,20 Given the limited evidence on NSAID use among DOACs alone, it is assumed NSAID use in combination with DOACs has a similar risk of bleeding as warfarin use. This may cause clinicians to automatically exclude NSAID therapy as a treatment option for patients on a DOAC who are otherwise clinically appropriate candidates, such as those with underlying inflammatory conditions. Avoiding NSAID therapy in this patient population may lead to suboptimal pain management and increase the risk of patient harm from methods such as inappropriate opioid therapy prescribing.
DOAC therapy should not be a universal limitation to the use of NSAIDs. Although the risk of bleeding with NSAID therapy is always present, deliberate NSAID prescribing in addition to the timely implementation of risk mitigation strategies may provide an avenue for safe NSAID prescribing in patients receiving a DOAC. A population health-based approach to DOAC management, such as the DOAC Dashboard, appears to be effective at preventing patient harm when NSAIDs are prescribed in conjunction with DOACs.
Limitations
The DOAC Dashboard has been shown to be effective and efficient at monitoring DOAC therapy from a population-based approach.16 Reports generated through the DOAC Dashboard provide convenient access to patient data which allows for timely interventions; however, there are limits to its use for data collection. All the data elements necessary to properly assess bleeding risk with validated tools, such as HAS-BLED (hypertension, abnormal renal/liver function, stroke, bleeding history or predisposition, labile international normalized ratio, elderly, drugs/ alcohol concomitantly), are not available on DOAC Dashboard reports. Due to this constraint, bleeding risk assessments were not conducted at baseline and this study was unable to include risk modeling. Additionally, data elements like initiation and discontinuation dates and duration of therapies were not readily available. As a result, this study was unable to incorporate time as a data point.
This was a retrospective study that relied on manual review of chart documentation to verify bleeding events, but data obtained through the DOAC Dashboard were transferred directly from the EHR.15 Bleeding events available for evaluation were restricted to those that occurred at a VA facility. Additionally, the sample size within the rivaroxaban NSAID user group did not reach the predefined sample size required to reach power and may have been too small to detect a difference if one did exist. The secondary assessment had a low sample size of NSAID user bleeding events, making it difficult to fully assess its impact on NSAID selectivity and PPI coprescribing on bleeding rates. All courses of NSAIDs were equally valued regardless of the dose or therapy duration; however, this is consistent with how NSAID use was defined in the RE-LY and ARISTOTLE trials.
CONCLUSIONS
This retrospective cohort review found no statistically significant difference in the composite bleeding rates between rivaroxaban and apixaban among NSAID users and non-NSAID users. Moreover, there was no clinically significant impact observed for bleeding rates in regard to NSAID selectivity and PPI coprescribing among NSAID users. However, coprescribing of PPI therapy to patients on a DOAC who are clinically indicated for an NSAID may reduce the risk of bleeding. Population health management tools, such as the DOAC Dashboard, may also allow clinicians to safely prescribe NSAIDs to patients on a DOAC. Further large-scale observational studies are needed to quantify the real-world risk of bleeding with concomitant NSAID use among DOACs alone and to evaluate the impact from NSAID selectivity or PPI coprescribing.
Clinical practice has shifted from vitamin K antagonists to direct oral anticoagulants (DOACs) for atrial fibrillation treatment due to their more favorable risk-benefit profile and less lifestyle modification required.1,2 However, the advantage of a lower bleeding risk with DOACs could be compromised by potentially problematic pharmacokinetic interactions like those conferred by antiplatelets or nonsteroidal anti-inflammatory drugs (NSAIDs).3,4 Treating a patient needing anticoagulation with a DOAC who has comorbidities may introduce unavoidable drug-drug interactions. This particularly happens with over-the-counter and prescription NSAIDs used for the management of pain and inflammatory conditions.5
NSAIDs primarily affect 2 cyclooxygenase (COX) enzyme isomers, COX-1 and COX-2.6 COX-1 helps maintain gastrointestinal (GI) mucosa integrity and platelet aggregation processes, whereas COX-2 is engaged in pain signaling and inflammation mediation. COX-1 inhibition is associated with more bleeding-related adverse events (AEs), especially in the GI tract. COX-2 inhibition is thought to provide analgesia and anti-inflammatory properties without elevating bleeding risk. This premise is responsible for the preferential use of celecoxib, a COX-2 selective NSAID, which should confer a lower bleeding risk compared to nonselective NSAIDs such as ibuprofen and naproxen.7 NSAIDs have been documented as independent risk factors for bleeding. NSAID users are about 3 times as likely to develop GI AEs compared to nonNSAID users.8
Many clinicians aim to further mitigate NSAID-associated bleeding risk by coprescribing a proton pump inhibitor (PPI). PPIs provide gastroprotection against NSAID-induced mucosal injury and sequential complication of GI bleeding. In a multicenter randomized control trial, patients who received concomitant PPI therapy while undergoing chronic NSAID therapy—including nonselective and COX-2 selective NSAIDs—had a significantly lower risk of GI ulcer development (placebo, 17.0%; 20 mg esomeprazole, 5.2%; 40 mg esomeprazole, 4.6%).9 Current clinical guidelines for preventing NSAIDassociated bleeding complications recommend using a COX-2 selective NSAID in combination with PPI therapy for patients at high risk for GI-related bleeding, including the concomitant use of anticoagulants.10
There is evidence suggesting an increased bleeding risk with NSAIDs when used in combination with vitamin K antagonists such as warfarin.11,12 A systematic review of warfarin and concomitant NSAID use found an increased risk of overall bleeding with NSAID use in combination with warfarin (odds ratio 1.58; 95% CI, 1.18-2.12), compared to warfarin alone.12
Posthoc analyses of randomized clinical trials have also demonstrated an increased bleeding risk with oral anticoagulation and concomitant NSAID use.13,14 In the RE-LY trial, NSAID users on warfarin or dabigatran had a statistically significant increased risk of major bleeding compared to non-NSAID users (hazard ratio [HR] 1.68; 95% CI, 1.40- 2.02; P < .001).13 In the ARISTOTLE trial, patients on warfarin or apixaban who were incident NSAID users were found to have an increased risk of major bleeding (HR 1.61; 95% CI, 1.11-2.33) and clinically relevant nonmajor bleeding (HR 1.70; 95% CI, 1.16- 2.48).14 These trials found a statistically significant increased bleeding risk associated with NSAID use, though the populations evaluated included patients taking warfarin and patients taking DOACs. These trials did not evaluate the bleeding risk of concomitant NSAID use among DOACs alone.
Evidence on NSAID-associated bleeding risk with DOACs is lacking in settings where the patient population, prescribing practices, and monitoring levels are variable. Within the Veterans Health Administration, clinical pharmacist practitioners (CPPs) in anticoagulation clinics oversee DOAC therapy management. CPPs monitor safety and efficacy of DOAC therapies through a population health management tool, the DOAC Dashboard.15 The DOAC Dashboard creates alerts for patients who may require an intervention based on certain clinical parameters, such as drug-drug interactions.16 Whenever a patient on a DOAC is prescribed an NSAID, an alert is generated on the DOAC Dashboard to flag the CPPs for the potential need for an intervention. If NSAID therapy remains clinically indicated, CPPs may recommend risk reduction strategies such as a COX-2 selective NSAID or coprescribing a PPI.10
The DOAC Dashboard provides an ideal setting for investigating the effects of NSAID use, NSAID selectivity, and PPI coprescribing on DOAC bleeding rates. With an increasing population of patients receiving anticoagulation therapy with a DOAC, more guidance regarding the bleeding risk of concomitant NSAID use with DOACs is needed. Studies evaluating the bleeding risk with concomitant NSAID use in patients on a DOAC alone are limited. This is the first study to date to compare bleeding risk with concomitant NSAID use between DOACs. This study provides information on bleeding risk with NSAID use among commonly prescribed DOACs, rivaroxaban and apixaban, and the potential impacts of current risk reduction strategies.
METHODS
This single-center retrospective cohort review was performed using the electronic health records (EHRs) of patients enrolled in the US Department of Veterans Affairs (VA) Mountain Home Healthcare System who received rivaroxaban or apixaban from December 2020 to December 2022. This study received approval from the East Tennessee State University/VA Institutional Review Board committee.
Patients were identified through the DOAC Dashboard, aged 21 to 100 years, and received rivaroxaban or apixaban at a therapeutic dose: rivaroxaban 10 to 20 mg daily or apixaban 2.5 to 5 mg twice daily. Patients were excluded if they were prescribed dual antiplatelet therapy, received rivaroxaban at dosing indicated for peripheral vascular disease, were undergoing dialysis, had evidence of moderate to severe hepatic impairment or any hepatic disease with coagulopathy, were undergoing chemotherapy or radiation, or had hematological conditions with predisposed bleeding risk. These patients were excluded to mitigate the potential confounding impact from nontherapeutic DOAC dosing strategies and conditions associated with an increased bleeding risk.
Eligible patients were stratified based on NSAID use. NSAID users were defined as patients prescribed an oral NSAID, including both acute and chronic courses, at any point during the study time frame while actively on a DOAC. Bleeding events were reviewed to evaluate rates between rivaroxaban and apixaban among NSAID and nonNSAID users. Identified NSAID users were further assessed for NSAID selectivity and PPI coprescribing as a subgroup analysis for the secondary assessment.
Data Collection
Baseline data were collected, including age, body mass index, anticoagulation indication, DOAC agent, DOAC dose, and DOAC total daily dose. Baseline serum creatinine levels, liver function tests, hemoglobin levels, and platelet counts were collected from the most recent data available immediately prior to the bleeding event, if applicable.
The DOAC Dashboard was reviewed for active and dismissed drug interaction alerts to identify patients taking rivaroxaban or apixaban who were prescribed an NSAID. Patients were categorized in the NSAID group if an interacting drug alert with an NSAID was reported during the study time frame. Data available through the interacting drug alerts on NSAID use were limited to the interacting drug name and date of the reported flag. Manual EHR review was required to confirm dates of NSAID therapy initiation and NSAID discontinuation, if applicable.
Data regarding concomitant antiplatelet use were obtained through review of the active and dismissed drug interaction alerts on the DOAC Dashboard. Concomitant antiplatelet use was defined as the prescribing of a single antiplatelet agent at any point while receiving DOAC therapy. Data on concomitant antiplatelets were collected regardless of NSAID status.
Data on coprescribed PPI therapy were obtained through manual EHR review of identified NSAID users. Coprescribed PPI therapy was defined as the prescribing of a PPI at any point during NSAID therapy. Data regarding PPI use among non-NSAID users were not collected because the secondary endpoint was designed to assess PPI use only among patients coprescribed a DOAC and NSAID.
Outcomes
Bleeding events were identified through an outcomes report generated by the DOAC Dashboard based on International Classification of Diseases, Tenth Revision diagnosis codes associated with a bleeding event. The outcomes report captures diagnoses from the outpatient and inpatient care settings. Reported bleeding events were limited to patients who received a DOAC at any point in the 6 months prior to the event and excluded patients with recent DOAC initiation within 7 days of the event, as these patients are not captured on the DOAC Dashboard.
All reported bleeding events were manually reviewed in the EHR and categorized as a major or clinically relevant nonmajor bleed, according to International Society of Thrombosis and Haemostasis criteria. Validated bleeding events were then crossreferenced with the interacting drug alerts report to identify events with potentially overlapping NSAID therapy at the time of the event. Overlapping NSAID therapy was defined as the prescribing of an NSAID at any point in the 6 months prior to the event. All events with potential overlapping NSAID therapies were manually reviewed for confirmation of NSAID status at the time of the event.
The primary endpoint was a composite of any bleeding event per International Society of Thrombosis and Haemostasis criteria. The secondary endpoint evaluated the potential impact of NSAID selectivity or PPI coprescribing on the bleeding rate among the NSAID user groups.
Statistical Analysis
Analyses were performed consistent with the methods used in the ARISTOTLE and RE-LY trials. It was determined that a sample size of 504 patients, with ≥ 168 patients in each group, would provide 80% power using a 2-sided a of 0.05. HRs with 95% CIs and respective P values were calculated using a SPSS-adapted online calculator.
RESULTS
The DOAC Dashboard identified 681 patients on rivaroxaban and 3225 patients on apixaban; 72 patients on rivaroxaban (10.6%) and 300 patients on apixaban (9.3%) were NSAID users. The mean age of NSAID users was 66.9 years in the rivaroxaban group and 72.4 years in the apixaban group. The mean age of non-NSAID users was 71.5 years in the rivaroxaban group and 75.6 years in the apixaban group. No appreciable differences were observed among subgroups in body mass index, renal function, hepatic function, hemoglobin, or platelet counts, and no statistically significant differences were identified (Table 1). Antiplatelet agents identified included aspirin, clopidogrel, prasugrel, and ticagrelor. Fifteen patients (20.3%) in the rivaroxaban group and 87 patients (28.7%) in the apixaban group had concomitant antiplatelet and NSAID use. Forty-five patients on rivaroxaban (60.8%) and 170 (55.9%) on apixaban were prescribed concomitant PPI and NSAID at baseline. Among non-NSAID users, there was concomitant antiplatelet use for 265 patients (43.6%) in the rivaroxaban group and 1401 patients (47.9%) in the apixaban group. Concomitant PPI use was identified among 63 patients (60.0%) taking selective NSAIDs and 182 (57.2%) taking nonselective NSAIDs.

A total of 423 courses of NSAIDs were identified: 85 NSAID courses in the rivaroxaban group and 338 NSAID courses in the apixaban group. Most NSAID courses involved a nonselective NSAID in the rivaroxaban and apixaban NSAID user groups: 75.2% (n = 318) aggregately compared to 71.8% (n = 61) and 76.0% (n = 257) in the rivaroxaban and apixaban groups, respectively. The most frequent NSAID courses identified were meloxicam (26.7%; n = 113), celecoxib (24.8%; n = 105), ibuprofen (19.1%; n = 81), and naproxen (13.5%; n = 57). Data regarding NSAID therapy initiation and discontinuation dates were not readily available. As a result, the duration of NSAID courses was not captured.
There was no statistically significant difference in bleeding rates between rivaroxaban and apixaban among NSAID users (HR 1.04; 95% CI, 0.98-1.12) or non-NSAID users (HR 1.15; 95% CI, 0.80-1.66) (Table 2). Apixaban non-NSAID users had a higher rate of major bleeds (HR 0.32; 95% CI, 0.17-0.61) while rivaroxaban non-NSAID users had a higher rate of clinically relevant nonmajor bleeds (HR 1.63; 95% CI, 1.10-2.54).

The sample size for the secondary endpoint consisted of bleeding events that were confirmed to have had an overlapping NSAID prescribed at the time of the event. For this secondary assessment, there was 1 rivaroxaban NSAID user bleeding event and 4 apixaban NSAID user bleeding events. For the rivaroxaban NSAID user bleeding event, the NSAID was nonselective and a PPI was not coprescribed. For the apixaban NSAID user bleeding events, 2 NSAIDs were nonselective and 2 were selective. All patients with apixaban and NSAID bleeding events had a coprescribed PPI. There was no clinically significant difference in the bleeding rates observed for NSAID selectivity or PPI coprescribing among the NSAID user subgroups.
DISCUSSION
This study found that there was no statistically significant difference for bleeding rates of major and nonmajor bleeding events between rivaroxaban and apixaban among NSAID users and non-NSAID users. This study did not identify a clinically significant impact on bleeding rates from NSAID selectivity or PPI coprescribing among the NSAID users.
There were notable but not statistically significant differences in baseline characteristics observed between the NSAID and non-NSAID user groups. On average, the rivaroxaban and apixaban NSAID users were younger compared with those not taking NSAIDs. NSAIDs, specifically nonselective NSAIDs, are recognized as potentially inappropriate medications for older adults given that this population is at an increased risk for GI ulcer development and/or GI bleeding.17 The non-NSAID user group likely consisted of older patients compared to the NSAID user group as clinicians may avoid prescribing NSAIDs to older adults regardless of concomitant DOAC therapy.
In addition to having an older patient population, non-NSAID users were more frequently prescribed a concomitant antiplatelet when compared with NSAID users. This prescribing pattern may be due to clinicians avoiding the use of NSAIDs in patients receiving DOAC therapy in combination with antiplatelet therapy, as these patients have been found to have an increased bleeding rate compared to DOAC therapy alone.18
Non-NSAID users had an overall higher bleeding rate for both major and nonmajor bleeding events. Based on this observation, it could be hypothesized that antiplatelet agents have a higher risk of bleeding in comparison to NSAIDs. In a subanalysis of the EXPAND study evaluating risk factors of major bleeding in patients receiving rivaroxaban, concomitant use of antiplatelet agents demonstrated a statistically significant increased risk of bleeding (HR 1.6; 95% CI, 1.2-2.3; P = .003) while concomitant use of NSAIDs did not (HR 0.8; 95% CI, 0.3-2.2; P = .67).19
In assessing PPI status at baseline, a majority of both rivaroxaban and apixaban NSAID users were coprescribed a PPI. This trend aligns with current clinical guideline recommendations for the prescribing of PPI therapy for GI protection in high-risk patients, such as those on DOAC therapy and concomitant NSAID therapy.10 Given the high proportion of NSAID users coprescribed a PPI at baseline, it may be possible that the true incidence of NSAID-associated bleeding events was higher than what this study found. This observation may reflect the impact from timely implementation of risk mitigation strategies by CPPs in the anticoagulation clinic. However, this study was not constructed to assess the efficacy of PPI use in this manner.
It is important to note the patients included in this study were followed by a pharmacist in an anticoagulation clinic using the DOAC Dashboard.15 This population management tool allows CPPs to make proactive interventions when a patient taking a DOAC receives an NSAID prescription, such as recommending the coprescribing of a PPI or use of a selective NSAID.10,16 These standards of care may have contributed to an overall reduced bleeding rate among the NSAID user group and may not be reflective of private practice.
The planned analysis of this study was modeled after the posthoc analysis of the RE-LY and ARISTOTLE trials. Both trials demonstrated an increased risk of bleeding with oral anticoagulation, including DOAC and warfarin, in combination with NSAID use. However, both trials found that NSAID use in patients treated with a DOAC was not independently associated with increased bleeding events compared with warfarin.13,14 The results of this study are comparable to the RE-LY and ARISTOTLE findings that NSAID use among patients treated with rivaroxaban or apixaban did not demonstrate a statistically significant increased bleeding risk.
Studies of NSAID use in combination with DOAC therapy have been limited to patient populations consisting of both DOAC and warfarin. Evidence from these trials outlines the increased bleeding risk associated with NSAID use in combination with oral anticoagulation; however, these patient populations include those on a DOAC and warfarin.13,14,19,20 Given the limited evidence on NSAID use among DOACs alone, it is assumed NSAID use in combination with DOACs has a similar risk of bleeding as warfarin use. This may cause clinicians to automatically exclude NSAID therapy as a treatment option for patients on a DOAC who are otherwise clinically appropriate candidates, such as those with underlying inflammatory conditions. Avoiding NSAID therapy in this patient population may lead to suboptimal pain management and increase the risk of patient harm from methods such as inappropriate opioid therapy prescribing.
DOAC therapy should not be a universal limitation to the use of NSAIDs. Although the risk of bleeding with NSAID therapy is always present, deliberate NSAID prescribing in addition to the timely implementation of risk mitigation strategies may provide an avenue for safe NSAID prescribing in patients receiving a DOAC. A population health-based approach to DOAC management, such as the DOAC Dashboard, appears to be effective at preventing patient harm when NSAIDs are prescribed in conjunction with DOACs.
Limitations
The DOAC Dashboard has been shown to be effective and efficient at monitoring DOAC therapy from a population-based approach.16 Reports generated through the DOAC Dashboard provide convenient access to patient data which allows for timely interventions; however, there are limits to its use for data collection. All the data elements necessary to properly assess bleeding risk with validated tools, such as HAS-BLED (hypertension, abnormal renal/liver function, stroke, bleeding history or predisposition, labile international normalized ratio, elderly, drugs/ alcohol concomitantly), are not available on DOAC Dashboard reports. Due to this constraint, bleeding risk assessments were not conducted at baseline and this study was unable to include risk modeling. Additionally, data elements like initiation and discontinuation dates and duration of therapies were not readily available. As a result, this study was unable to incorporate time as a data point.
This was a retrospective study that relied on manual review of chart documentation to verify bleeding events, but data obtained through the DOAC Dashboard were transferred directly from the EHR.15 Bleeding events available for evaluation were restricted to those that occurred at a VA facility. Additionally, the sample size within the rivaroxaban NSAID user group did not reach the predefined sample size required to reach power and may have been too small to detect a difference if one did exist. The secondary assessment had a low sample size of NSAID user bleeding events, making it difficult to fully assess its impact on NSAID selectivity and PPI coprescribing on bleeding rates. All courses of NSAIDs were equally valued regardless of the dose or therapy duration; however, this is consistent with how NSAID use was defined in the RE-LY and ARISTOTLE trials.
CONCLUSIONS
This retrospective cohort review found no statistically significant difference in the composite bleeding rates between rivaroxaban and apixaban among NSAID users and non-NSAID users. Moreover, there was no clinically significant impact observed for bleeding rates in regard to NSAID selectivity and PPI coprescribing among NSAID users. However, coprescribing of PPI therapy to patients on a DOAC who are clinically indicated for an NSAID may reduce the risk of bleeding. Population health management tools, such as the DOAC Dashboard, may also allow clinicians to safely prescribe NSAIDs to patients on a DOAC. Further large-scale observational studies are needed to quantify the real-world risk of bleeding with concomitant NSAID use among DOACs alone and to evaluate the impact from NSAID selectivity or PPI coprescribing.
- Ruff CT, Giugliano RP, Braunwald E, et al. Comparison of the efficacy and safety of new oral anticoagulants with warfarin in patients with atrial fibrillation: a meta-analysis of randomised trials. Lancet. 2014;383(9921):955-962. doi:10.1016/S0140-6736(13)62343-0
- Ageno W, Gallus AS, Wittkowsky A, Crowther M, Hylek EM, Palareti G. Oral anticoagulant therapy: antithrombotic therapy and prevention of thrombosis, 9th ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines. Chest. 2012;141(2 Suppl):e44S-e88S. doi:10.1378/chest.11-2292
- Eikelboom J, Merli G. Bleeding with direct oral anticoagulants vs warfarin: clinical experience. Am J Med. 2016;129(11S):S33-S40. doi:10.1016/j.amjmed.2016.06.003
- Vranckx P, Valgimigli M, Heidbuchel H. The significance of drug-drug and drug-food interactions of oral anticoagulation. Arrhythm Electrophysiol Rev. 2018;7(1):55-61. doi:10.15420/aer.2017.50.1
- Davis JS, Lee HY, Kim J, et al. Use of non-steroidal antiinflammatory drugs in US adults: changes over time and by demographic. Open Heart. 2017;4(1):e000550. doi:10.1136/openhrt-2016-000550
- Schafer AI. Effects of nonsteroidal antiinflammatory drugs on platelet function and systemic hemostasis. J Clin Pharmacol. 1995;35(3):209-219. doi:10.1002/j.1552-4604.1995.tb04050.x
- Al-Saeed A. Gastrointestinal and cardiovascular risk of nonsteroidal anti-inflammatory drugs. Oman Med J. 2011;26(6):385-391. doi:10.5001/omj.2011.101
- Gabriel SE, Jaakkimainen L, Bombardier C. Risk for serious gastrointestinal complications related to use of nonsteroidal anti-inflammatory drugs. Ann Intern Med. 1991;115(10):787-796. doi:10.7326/0003-4819-115-10-787
- Scheiman JM, Yeomans ND, Talley NJ, et al. Prevention of ulcers by esomeprazole in at-risk patients using non-selective NSAIDs and COX-2 inhibitors. Am J Gastroenterol. 2006;101(4):701-710. doi:10.1111/j.1572-0241.2006.00499.x
- Freedberg DE, Kim LS, Yang YX. The risks and benefits of long-term use of proton pump inhibitors: expert review and best practice advice from the American Gastroenterological Association. Gastroenterology. 2017;152(4):706-715. doi:10.1053/j.gastro.2017.01.031
- Lamberts M, Lip GYH, Hansen ML, et al. Relation of nonsteroidal anti-inflammatory drugs to serious bleeding and thromboembolism risk in patients with atrial fibrillation receiving antithrombotic therapy: a nationwide cohort study. Ann Intern Med. 2014;161(10):690-698. doi:10.7326/M13-1581
- Villa Zapata L, Hansten PD, Panic J, et al. Risk of bleeding with exposure to warfarin and nonsteroidal anti-inflammatory drugs: a systematic review and metaanalysis. Thromb Haemost. 2020;120(7):1066-1074. doi:10.1055/s-0040-1710592
- Kent AP, Brueckmann M, Fraessdorf M, et al. Concomitant oral anticoagulant and nonsteroidal anti-inflammatory drug therapy in patients with atrial fibrillation. J Am Coll Cardiol. 2018;72(3):255-267. doi:10.1016/j.jacc.2018.04.063
- Dalgaard F, Mulder H, Wojdyla DM, et al. Patients with atrial fibrillation taking nonsteroidal antiinflammatory drugs and oral anticoagulants in the ARISTOTLE Trial. Circulation. 2020;141(1):10-20. doi:10.1161/CIRCULATIONAHA.119.041296
- Allen AL, Lucas J, Parra D, et al. Shifting the paradigm: a population health approach to the management of direct oral anticoagulants. J Am Heart Asssoc. 2021;10(24):e022758. doi:10.1161/JAHA.121.022758
- . Valencia D, Spoutz P, Stoppi J, et al. Impact of a direct oral anticoagulant population management tool on anticoagulation therapy monitoring in clinical practice. Ann Pharmacother. 2019;53(8):806-811. doi:10.1177/1060028019835843
- By the 2023 American Geriatrics Society Beers Criteria® Update Expert Panel. American Geriatrics Society 2023 Updated AGS Beers Criteria® for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2023;71(7):2052-2081. doi:10.1111/jgs.18372
- Kumar S, Danik SB, Altman RK, et al. Non-vitamin K antagonist oral anticoagulants and antiplatelet therapy for stroke prevention in patients with atrial fibrillation. Cardiol Rev. 2016;24(5):218-223. doi:10.1097/CRD.0000000000000088
- Sakuma I, Uchiyama S, Atarashi H, et al. Clinical risk factors of stroke and major bleeding in patients with nonvalvular atrial fibrillation under rivaroxaban: the EXPAND study sub-analysis. Heart Vessels. 2019;34(11):1839-1851. doi:10.1007/s00380-019-01425-x
- Davidson BL, Verheijen S, Lensing AWA, et al. Bleeding risk of patients with acute venous thromboembolism taking nonsteroidal anti-inflammatory drugs or aspirin. JAMA Intern Med. 2014;174(6):947-953. doi:10.1001/jamainternmed.2014.946
- Ruff CT, Giugliano RP, Braunwald E, et al. Comparison of the efficacy and safety of new oral anticoagulants with warfarin in patients with atrial fibrillation: a meta-analysis of randomised trials. Lancet. 2014;383(9921):955-962. doi:10.1016/S0140-6736(13)62343-0
- Ageno W, Gallus AS, Wittkowsky A, Crowther M, Hylek EM, Palareti G. Oral anticoagulant therapy: antithrombotic therapy and prevention of thrombosis, 9th ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines. Chest. 2012;141(2 Suppl):e44S-e88S. doi:10.1378/chest.11-2292
- Eikelboom J, Merli G. Bleeding with direct oral anticoagulants vs warfarin: clinical experience. Am J Med. 2016;129(11S):S33-S40. doi:10.1016/j.amjmed.2016.06.003
- Vranckx P, Valgimigli M, Heidbuchel H. The significance of drug-drug and drug-food interactions of oral anticoagulation. Arrhythm Electrophysiol Rev. 2018;7(1):55-61. doi:10.15420/aer.2017.50.1
- Davis JS, Lee HY, Kim J, et al. Use of non-steroidal antiinflammatory drugs in US adults: changes over time and by demographic. Open Heart. 2017;4(1):e000550. doi:10.1136/openhrt-2016-000550
- Schafer AI. Effects of nonsteroidal antiinflammatory drugs on platelet function and systemic hemostasis. J Clin Pharmacol. 1995;35(3):209-219. doi:10.1002/j.1552-4604.1995.tb04050.x
- Al-Saeed A. Gastrointestinal and cardiovascular risk of nonsteroidal anti-inflammatory drugs. Oman Med J. 2011;26(6):385-391. doi:10.5001/omj.2011.101
- Gabriel SE, Jaakkimainen L, Bombardier C. Risk for serious gastrointestinal complications related to use of nonsteroidal anti-inflammatory drugs. Ann Intern Med. 1991;115(10):787-796. doi:10.7326/0003-4819-115-10-787
- Scheiman JM, Yeomans ND, Talley NJ, et al. Prevention of ulcers by esomeprazole in at-risk patients using non-selective NSAIDs and COX-2 inhibitors. Am J Gastroenterol. 2006;101(4):701-710. doi:10.1111/j.1572-0241.2006.00499.x
- Freedberg DE, Kim LS, Yang YX. The risks and benefits of long-term use of proton pump inhibitors: expert review and best practice advice from the American Gastroenterological Association. Gastroenterology. 2017;152(4):706-715. doi:10.1053/j.gastro.2017.01.031
- Lamberts M, Lip GYH, Hansen ML, et al. Relation of nonsteroidal anti-inflammatory drugs to serious bleeding and thromboembolism risk in patients with atrial fibrillation receiving antithrombotic therapy: a nationwide cohort study. Ann Intern Med. 2014;161(10):690-698. doi:10.7326/M13-1581
- Villa Zapata L, Hansten PD, Panic J, et al. Risk of bleeding with exposure to warfarin and nonsteroidal anti-inflammatory drugs: a systematic review and metaanalysis. Thromb Haemost. 2020;120(7):1066-1074. doi:10.1055/s-0040-1710592
- Kent AP, Brueckmann M, Fraessdorf M, et al. Concomitant oral anticoagulant and nonsteroidal anti-inflammatory drug therapy in patients with atrial fibrillation. J Am Coll Cardiol. 2018;72(3):255-267. doi:10.1016/j.jacc.2018.04.063
- Dalgaard F, Mulder H, Wojdyla DM, et al. Patients with atrial fibrillation taking nonsteroidal antiinflammatory drugs and oral anticoagulants in the ARISTOTLE Trial. Circulation. 2020;141(1):10-20. doi:10.1161/CIRCULATIONAHA.119.041296
- Allen AL, Lucas J, Parra D, et al. Shifting the paradigm: a population health approach to the management of direct oral anticoagulants. J Am Heart Asssoc. 2021;10(24):e022758. doi:10.1161/JAHA.121.022758
- . Valencia D, Spoutz P, Stoppi J, et al. Impact of a direct oral anticoagulant population management tool on anticoagulation therapy monitoring in clinical practice. Ann Pharmacother. 2019;53(8):806-811. doi:10.1177/1060028019835843
- By the 2023 American Geriatrics Society Beers Criteria® Update Expert Panel. American Geriatrics Society 2023 Updated AGS Beers Criteria® for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2023;71(7):2052-2081. doi:10.1111/jgs.18372
- Kumar S, Danik SB, Altman RK, et al. Non-vitamin K antagonist oral anticoagulants and antiplatelet therapy for stroke prevention in patients with atrial fibrillation. Cardiol Rev. 2016;24(5):218-223. doi:10.1097/CRD.0000000000000088
- Sakuma I, Uchiyama S, Atarashi H, et al. Clinical risk factors of stroke and major bleeding in patients with nonvalvular atrial fibrillation under rivaroxaban: the EXPAND study sub-analysis. Heart Vessels. 2019;34(11):1839-1851. doi:10.1007/s00380-019-01425-x
- Davidson BL, Verheijen S, Lensing AWA, et al. Bleeding risk of patients with acute venous thromboembolism taking nonsteroidal anti-inflammatory drugs or aspirin. JAMA Intern Med. 2014;174(6):947-953. doi:10.1001/jamainternmed.2014.946
Impact of NSAID Use on Bleeding Rates for Patients Taking Rivaroxaban or Apixaban
Impact of NSAID Use on Bleeding Rates for Patients Taking Rivaroxaban or Apixaban
Pharmacist-Driven Deprescribing to Reduce Anticholinergic Burden in Veterans With Dementia
Pharmacist-Driven Deprescribing to Reduce Anticholinergic Burden in Veterans With Dementia
Anticholinergic medications block the activity of the neurotransmitter acetylcholine by binding to either muscarinic or nicotinic receptors in both the peripheral and central nervous system. Anticholinergic medications typically refer to antimuscarinic medications and have been prescribed to treat a variety of conditions common in older adults, including overactive bladder, allergies, muscle spasms, and sleep disorders.1,2 Since muscarinic receptors are present throughout the body, anticholinergic medications are associated with many adverse effects (AEs), including constipation, urinary retention, xerostomia, and delirium. Older adults are more sensitive to these AEs due to physiological changes associated with aging.1
The American Geriatric Society Beers Criteria for Potentially Inappropriate Medications Use in Older Adults identifies drugs with strong anticholinergic properties. The Beers Criteria strongly recommends avoiding these medications in patients with dementia or cognitive impairment due to the risk of central nervous system AEs. In the updated 2023 Beers Criteria, the rationale was expanded to recognize the risks of the cumulative anticholinergic burden associated with concurrent anticholinergic use.3,4
Given the prevalent use of anticholinergic medications in older adults, there has been significant research demonstrating their AEs, specifically delirium and cognitive impairment in geriatric patients. A systematic review of 14 articles conducted in 7 different countries of patients with median age of 76.4 to 86.1 years reviewed clinical outcomes of anticholinergic use in patients with dementia. Five studies found anticholinergics were associated with increased all-cause mortality in patients with dementia, and 3 studies found anticholinergics were associated with longer hospital stays. Other studies found that anticholinergics were associated with delirium and reduced health-related quality of life.5
About 35% of veterans with dementia have been prescribed a medication regimen with a high anticholinergic burden.6 In 2018, the US Department of Veterans Affairs (VA) Pharmacy Benfits Management Center for Medical Safety completed a centrally aggregated medication use evaluation (CAMUE) to assess the appropriateness of anticholinergic medication use in patients with dementia. The retrospective chart review included 1094 veterans from 19 sites. Overall, about 15% of the veterans experienced new falls, delirium, or worsening dementia within 30 days of starting an anticholinergic medication. Furthermore, < 40% had documentation of a nonanticholinergic alternative medication trial, and < 20% had documented nonpharmacologic therapy. The documentation of risk-benefit assessment acknowledging the risks of anticholinergic medication use in veterans with dementia occurred only about 13% of the time. The CAMUE concluded that the risks of initiating an anticholinergic medication in veterans with dementia are likely underdocumented and possibly under considered by prescribers.7
Developed within the Veterans Health Administration (VHA), VIONE (Vital, Important, Optional, Not Indicated, Every medication has an indication) is a medication management methodology that aims to reduce polypharmacy and improve patient safety consistent with high-reliability organizations. Since it launched in 2016, VIONE has gradually been implemented at many VHA facilities. The VIONE deprescribing dashboard had not been used at the VA Louisville Healthcare System prior to this quality improvement project.
This dashboard uses the Beers Criteria to identify potentially inappropriate anticholinergic medications. It uses the Anticholinergic Cognitive Burden (ACB) scale to calculate the cumulative anticholinergic risk for each patient. Medications with an ACB score of 2 or 3 have clinically relevant cognitive effects such as delirium and dementia (Table 1). For each point increase in total ACB score, a decline in mini-mental state examination score of 0.33 points over 2 years has been shown. Each point increase has also been correlated with a 26% increase in risk of death.8-10

Methods
The purpose of this quality improvement project was to determine the impact of pharmacist-driven deprescribing on the anticholinergic burden in veterans with dementia at VA Louisville Healthcare System. Data were obtained through the Computerized Patient Record System (CPRS) and VIONE deprescribing dashboard and entered in a secure Microsoft Excel spreadsheet. Pharmacist deprescribing steps were entered as CPRS progress notes. A deprescribing note template was created, and 11 templates with indication-specific recommendations were created for each anticholinergic indication identified (contact authors for deprescribing note template examples). Usage of anticholinergic medications was reexamined 3 months after the deprescribing note was entered.
Eligible patients identified in the VIONE deprescribing dashboard had an outpatient order for a medication with strong anticholinergic properties as identified using the Beers Criteria and were aged ≥ 65 years. Patients also had to be diagnosed with dementia or cognitive impairment. Patients were excluded if they were receiving hospice care or if the anticholinergic medication was from a non-VA prescriber or filled at a non-VA pharmacy. The VIONE deprescribing dashboard also excluded skeletal muscle relaxants if the patient had a spinal cord-related visit in the previous 2 years, first-generation antihistamines if the patient had a vertigo diagnosis, hydroxyzine if the indication was for anxiety, trospium if the indication was for overactive bladder, and antipsychotics if the patient had been diagnosed with schizophrenia or bipolar disorder. The following were included in the deprescribing recommendations if the dashboard identified the patient due to receiving a second strongly anticholinergic medication: first generation antihistamines if the patient was diagnosed with vertigo and hydroxyzine if the indication is for anxiety.
Each eligible patient received a focused medication review by a pharmacist via electronic chart review and a templated CPRS progress note with patient-specific recommendations. The prescriber and the patient’s primary care practitioner were recommended to perform a patient-specific risk-benefit assessment, deprescribe potentially inappropriate anticholinergic medications, and consider nonanticholinergic alternatives (both pharmacologic and nonpharmacologic). Data collected included baseline age, sex, prespecified comorbidities (type of dementia, cognitive impairment, delirium, benign prostatic hyperplasia/lower urinary tract symptoms), duration of prescribed anticholinergic medication, indication and deprescribing rate for each anticholinergic agent, and concurrent dementia medications (acetylcholinesterase inhibitors, memantine, or both).
The primary outcome was the number of patients that had = 1 medication with strong anticholinergic properties deprescribed. Deprescribing was defined as medication discontinuation or reduction of total daily dose. Secondary outcomes were the mean change in ACB scale, the number of patients with dose tapering, documented patient-specific risk-benefit assessment, and initiated nonanticholinergic alternative per pharmacist recommendation.
Results
The VIONE deprescribing dashboard identified 121 patients; 45 were excluded for non-VA prescriber or pharmacy, and 8 patients were excluded for other reasons. Sixty-eight patients were included in the deprescribing initiative. The mean age was 73.4 years (range, 67-93), 65 (96%) were male, and 34 (50%) had unspecified dementia (Table 2). Thirty-one patients (46%) had concurrent cholinesterase inhibitor prescriptions for dementia. The median duration of use of a strong anticholinergic medication was 11 months.

Twenty-nine patients (43%) had ≥ 1 medication with strong anticholinergic properties deprescribed. Anticholinergic medication was discontinued for 26 patients, and the dose was decreased for 3 patients. ACB score fell by a mean of 1.1 per patient. There was an increase in the documented risk-benefit assessment for anticholinergic medications from a baseline of 4 (6%) to 19 (28%) 3 months after the deprescribing note. Cyclobenzaprine, paroxetine, and oxybutynin were deprescribed the most, and amitriptyline had the lowest rate of deprescribing (Table 3). Thirty patients (44%) had a pharmacologic, nonanticholinergic alternative initiated per pharmacist recommendation, and 6 patients (9%) had a nonpharmacologic alternative initiated per pharmacist recommendation.

Discussion
This quality improvement project suggests that with the use of population health management tools such as the VIONE deprescribing dashboard, pharmacists can help identify and deprescribe strong anticholinergic medications in patients with cognitive impairment or dementia. Pharmacists can also aid in deprescribing through evidence-based recommendations to guide risk-benefit discussion and consider safer, nonanticholinergic alternatives. The authors were able to help reduce anticholinergic cognitive burden in 43% of patients in this sample. The mean 1.1 ACB score reduction was considered clinically significant based on prior studies that found that each 1-point increase in ACB score correlated with declined cognition and increased mortality.8,10 The VIONE deprescribing dashboard provided real-time patient data and helped target patients at the highest risk of anticholinergic AEs. The creation of the note templates based on the indication helped streamline recommendations. Typically, the prescriber addressed the recommendations at a routine follow-up appointment. The deprescribing method used in this project was time-efficient and could be easily replicated once the CPRS note templates were created. Future deprescribing projects could consider more direct pharmacist intervention and medication management.
Limitations
There was no direct assessment of clinical outcomes such as change in cognition using cognitive function tests. However, multiple studies have demonstrated AEs associated with strong anticholinergic medication use and additive anticholinergic burden in patients with dementia or cognitive impairment.1,5 Also, the 3-month follow-up period was relatively short. The pharmacist’s deprescribing recommendations may have been accepted after 3 months, or patients could have restarted their anticholinergic medications. Longer follow-up time could provide more robust results and conclusions. Thirdly, there was no formal definition of what constituted a risk-benefit assessment of anticholinergic medications. The risk-benefit assessment was determined at the discretion of the authors, which was subjective and allowed for bias. Finally, 6 patients died during the 3-month follow-up. The data for these patients were included in the baseline characteristics but not in the study outcomes. If these patients had been excluded from the results, a higher percentage of patients (47%) would have had ≥ 1 anticholinergic medication deprescribed.
Conclusions
In collaboration with the interdisciplinary team, pharmacist recommendations resulted in deprescribing of anticholinergic medications in veterans with dementia or cognitive impairment. The VIONE deprescribing dashboard, an easily accessible population health management tool, can identify patients prescribed potentially inappropriate medications and help target patients at the highest risk of anticholinergic AEs. To prevent worsening cognitive impairment, delirium, falls, and other AEs, this deprescribing initiative can be replicated at other VHA facilities. Future projects could have a longer follow-up period, incorporate more direct pharmacist intervention, and assess clinical outcomes of deprescribing.
- Gray SL, Hanlon JT. Anticholinergic medication use and dementia: latest evidence and clinical implications. Ther Adv Drug Saf. 2016;7(5):217-224. doi:10.1177/2042098616658399
- Kersten H, Wyller TB. Anticholinergic drug burden in older people’s brain - how well is it measured? Basic Clin Pharmacol Toxicol. 2014;114(2):151-159. doi:10.1111/bcpt.12140
- By the 2019 American Geriatrics Society Beers Criteria® Update Expert Panel. American Geriatrics Society 2019 updated AGS beers criteria® for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2019;67(4):674-694. doi:10.1111/jgs.15767
- By the 2023 American Geriatrics Society Beers Criteria® Update Expert Panel. American Geriatrics Society 2023 updated AGS Beers Criteria® for potentially inappropriate medication use in older adults J Am Geriatr Soc. 2023;71(7):2052-2081. doi:10.1111/jgs.18372
- Wang K, Alan J, Page AT, Dimopoulos E, Etherton-Beer C. Anticholinergics and clinical outcomes amongst people with pre-existing dementia: a systematic review. Maturitas. 2021;151:1-14. doi:10.1016/j.maturitas.2021.06.004
- Thorpe JM, Thorpe CT, Gellad WF, et al. Dual health care system use and high-risk prescribing in patients with dementia: a national cohort study. Ann Intern Med. 2017;166(3):157-163. doi:10.7326/M16-0551
- McCarren M, Burk M, Carico R, Glassman P, Good CB, Cunningham F. Design of a centrally aggregated medication use evaluation (CAMUE): anticholinergics in dementia. Presented at: 2019 HSR&D/QUERI National Conference; October 29-31, 2019; Washington, DC. https://www.hsrd.research.va.gov/meetings/2019/abstract-display.cfm?AbsNum=4027
- Boustani, M, Campbell, N, Munger S, et al. Impact of anticholinergics on the aging brain: a review and practical application. Aging Health. 2008;4(3):311-320. doi:10.2217/1745509.x
- Constantino-Corpuz JK, Alonso MTD. Assessment of a medication deprescribing tool on polypharmacy and cost avoidance. Fed Pract. 2021;38(7):332-336. doi:10.12788/fp.0146
- Fox C, Richardson K, Maidment ID, et al. Anticholinergic medication use and cognitive impairment in the older population: the medical research council cognitive function and ageing study. J Am Geriatr Soc. 2011;59(8):1477-1483. doi:10.1111/j.1532-5415.2011.03491.x
Anticholinergic medications block the activity of the neurotransmitter acetylcholine by binding to either muscarinic or nicotinic receptors in both the peripheral and central nervous system. Anticholinergic medications typically refer to antimuscarinic medications and have been prescribed to treat a variety of conditions common in older adults, including overactive bladder, allergies, muscle spasms, and sleep disorders.1,2 Since muscarinic receptors are present throughout the body, anticholinergic medications are associated with many adverse effects (AEs), including constipation, urinary retention, xerostomia, and delirium. Older adults are more sensitive to these AEs due to physiological changes associated with aging.1
The American Geriatric Society Beers Criteria for Potentially Inappropriate Medications Use in Older Adults identifies drugs with strong anticholinergic properties. The Beers Criteria strongly recommends avoiding these medications in patients with dementia or cognitive impairment due to the risk of central nervous system AEs. In the updated 2023 Beers Criteria, the rationale was expanded to recognize the risks of the cumulative anticholinergic burden associated with concurrent anticholinergic use.3,4
Given the prevalent use of anticholinergic medications in older adults, there has been significant research demonstrating their AEs, specifically delirium and cognitive impairment in geriatric patients. A systematic review of 14 articles conducted in 7 different countries of patients with median age of 76.4 to 86.1 years reviewed clinical outcomes of anticholinergic use in patients with dementia. Five studies found anticholinergics were associated with increased all-cause mortality in patients with dementia, and 3 studies found anticholinergics were associated with longer hospital stays. Other studies found that anticholinergics were associated with delirium and reduced health-related quality of life.5
About 35% of veterans with dementia have been prescribed a medication regimen with a high anticholinergic burden.6 In 2018, the US Department of Veterans Affairs (VA) Pharmacy Benfits Management Center for Medical Safety completed a centrally aggregated medication use evaluation (CAMUE) to assess the appropriateness of anticholinergic medication use in patients with dementia. The retrospective chart review included 1094 veterans from 19 sites. Overall, about 15% of the veterans experienced new falls, delirium, or worsening dementia within 30 days of starting an anticholinergic medication. Furthermore, < 40% had documentation of a nonanticholinergic alternative medication trial, and < 20% had documented nonpharmacologic therapy. The documentation of risk-benefit assessment acknowledging the risks of anticholinergic medication use in veterans with dementia occurred only about 13% of the time. The CAMUE concluded that the risks of initiating an anticholinergic medication in veterans with dementia are likely underdocumented and possibly under considered by prescribers.7
Developed within the Veterans Health Administration (VHA), VIONE (Vital, Important, Optional, Not Indicated, Every medication has an indication) is a medication management methodology that aims to reduce polypharmacy and improve patient safety consistent with high-reliability organizations. Since it launched in 2016, VIONE has gradually been implemented at many VHA facilities. The VIONE deprescribing dashboard had not been used at the VA Louisville Healthcare System prior to this quality improvement project.
This dashboard uses the Beers Criteria to identify potentially inappropriate anticholinergic medications. It uses the Anticholinergic Cognitive Burden (ACB) scale to calculate the cumulative anticholinergic risk for each patient. Medications with an ACB score of 2 or 3 have clinically relevant cognitive effects such as delirium and dementia (Table 1). For each point increase in total ACB score, a decline in mini-mental state examination score of 0.33 points over 2 years has been shown. Each point increase has also been correlated with a 26% increase in risk of death.8-10

Methods
The purpose of this quality improvement project was to determine the impact of pharmacist-driven deprescribing on the anticholinergic burden in veterans with dementia at VA Louisville Healthcare System. Data were obtained through the Computerized Patient Record System (CPRS) and VIONE deprescribing dashboard and entered in a secure Microsoft Excel spreadsheet. Pharmacist deprescribing steps were entered as CPRS progress notes. A deprescribing note template was created, and 11 templates with indication-specific recommendations were created for each anticholinergic indication identified (contact authors for deprescribing note template examples). Usage of anticholinergic medications was reexamined 3 months after the deprescribing note was entered.
Eligible patients identified in the VIONE deprescribing dashboard had an outpatient order for a medication with strong anticholinergic properties as identified using the Beers Criteria and were aged ≥ 65 years. Patients also had to be diagnosed with dementia or cognitive impairment. Patients were excluded if they were receiving hospice care or if the anticholinergic medication was from a non-VA prescriber or filled at a non-VA pharmacy. The VIONE deprescribing dashboard also excluded skeletal muscle relaxants if the patient had a spinal cord-related visit in the previous 2 years, first-generation antihistamines if the patient had a vertigo diagnosis, hydroxyzine if the indication was for anxiety, trospium if the indication was for overactive bladder, and antipsychotics if the patient had been diagnosed with schizophrenia or bipolar disorder. The following were included in the deprescribing recommendations if the dashboard identified the patient due to receiving a second strongly anticholinergic medication: first generation antihistamines if the patient was diagnosed with vertigo and hydroxyzine if the indication is for anxiety.
Each eligible patient received a focused medication review by a pharmacist via electronic chart review and a templated CPRS progress note with patient-specific recommendations. The prescriber and the patient’s primary care practitioner were recommended to perform a patient-specific risk-benefit assessment, deprescribe potentially inappropriate anticholinergic medications, and consider nonanticholinergic alternatives (both pharmacologic and nonpharmacologic). Data collected included baseline age, sex, prespecified comorbidities (type of dementia, cognitive impairment, delirium, benign prostatic hyperplasia/lower urinary tract symptoms), duration of prescribed anticholinergic medication, indication and deprescribing rate for each anticholinergic agent, and concurrent dementia medications (acetylcholinesterase inhibitors, memantine, or both).
The primary outcome was the number of patients that had = 1 medication with strong anticholinergic properties deprescribed. Deprescribing was defined as medication discontinuation or reduction of total daily dose. Secondary outcomes were the mean change in ACB scale, the number of patients with dose tapering, documented patient-specific risk-benefit assessment, and initiated nonanticholinergic alternative per pharmacist recommendation.
Results
The VIONE deprescribing dashboard identified 121 patients; 45 were excluded for non-VA prescriber or pharmacy, and 8 patients were excluded for other reasons. Sixty-eight patients were included in the deprescribing initiative. The mean age was 73.4 years (range, 67-93), 65 (96%) were male, and 34 (50%) had unspecified dementia (Table 2). Thirty-one patients (46%) had concurrent cholinesterase inhibitor prescriptions for dementia. The median duration of use of a strong anticholinergic medication was 11 months.

Twenty-nine patients (43%) had ≥ 1 medication with strong anticholinergic properties deprescribed. Anticholinergic medication was discontinued for 26 patients, and the dose was decreased for 3 patients. ACB score fell by a mean of 1.1 per patient. There was an increase in the documented risk-benefit assessment for anticholinergic medications from a baseline of 4 (6%) to 19 (28%) 3 months after the deprescribing note. Cyclobenzaprine, paroxetine, and oxybutynin were deprescribed the most, and amitriptyline had the lowest rate of deprescribing (Table 3). Thirty patients (44%) had a pharmacologic, nonanticholinergic alternative initiated per pharmacist recommendation, and 6 patients (9%) had a nonpharmacologic alternative initiated per pharmacist recommendation.

Discussion
This quality improvement project suggests that with the use of population health management tools such as the VIONE deprescribing dashboard, pharmacists can help identify and deprescribe strong anticholinergic medications in patients with cognitive impairment or dementia. Pharmacists can also aid in deprescribing through evidence-based recommendations to guide risk-benefit discussion and consider safer, nonanticholinergic alternatives. The authors were able to help reduce anticholinergic cognitive burden in 43% of patients in this sample. The mean 1.1 ACB score reduction was considered clinically significant based on prior studies that found that each 1-point increase in ACB score correlated with declined cognition and increased mortality.8,10 The VIONE deprescribing dashboard provided real-time patient data and helped target patients at the highest risk of anticholinergic AEs. The creation of the note templates based on the indication helped streamline recommendations. Typically, the prescriber addressed the recommendations at a routine follow-up appointment. The deprescribing method used in this project was time-efficient and could be easily replicated once the CPRS note templates were created. Future deprescribing projects could consider more direct pharmacist intervention and medication management.
Limitations
There was no direct assessment of clinical outcomes such as change in cognition using cognitive function tests. However, multiple studies have demonstrated AEs associated with strong anticholinergic medication use and additive anticholinergic burden in patients with dementia or cognitive impairment.1,5 Also, the 3-month follow-up period was relatively short. The pharmacist’s deprescribing recommendations may have been accepted after 3 months, or patients could have restarted their anticholinergic medications. Longer follow-up time could provide more robust results and conclusions. Thirdly, there was no formal definition of what constituted a risk-benefit assessment of anticholinergic medications. The risk-benefit assessment was determined at the discretion of the authors, which was subjective and allowed for bias. Finally, 6 patients died during the 3-month follow-up. The data for these patients were included in the baseline characteristics but not in the study outcomes. If these patients had been excluded from the results, a higher percentage of patients (47%) would have had ≥ 1 anticholinergic medication deprescribed.
Conclusions
In collaboration with the interdisciplinary team, pharmacist recommendations resulted in deprescribing of anticholinergic medications in veterans with dementia or cognitive impairment. The VIONE deprescribing dashboard, an easily accessible population health management tool, can identify patients prescribed potentially inappropriate medications and help target patients at the highest risk of anticholinergic AEs. To prevent worsening cognitive impairment, delirium, falls, and other AEs, this deprescribing initiative can be replicated at other VHA facilities. Future projects could have a longer follow-up period, incorporate more direct pharmacist intervention, and assess clinical outcomes of deprescribing.
Anticholinergic medications block the activity of the neurotransmitter acetylcholine by binding to either muscarinic or nicotinic receptors in both the peripheral and central nervous system. Anticholinergic medications typically refer to antimuscarinic medications and have been prescribed to treat a variety of conditions common in older adults, including overactive bladder, allergies, muscle spasms, and sleep disorders.1,2 Since muscarinic receptors are present throughout the body, anticholinergic medications are associated with many adverse effects (AEs), including constipation, urinary retention, xerostomia, and delirium. Older adults are more sensitive to these AEs due to physiological changes associated with aging.1
The American Geriatric Society Beers Criteria for Potentially Inappropriate Medications Use in Older Adults identifies drugs with strong anticholinergic properties. The Beers Criteria strongly recommends avoiding these medications in patients with dementia or cognitive impairment due to the risk of central nervous system AEs. In the updated 2023 Beers Criteria, the rationale was expanded to recognize the risks of the cumulative anticholinergic burden associated with concurrent anticholinergic use.3,4
Given the prevalent use of anticholinergic medications in older adults, there has been significant research demonstrating their AEs, specifically delirium and cognitive impairment in geriatric patients. A systematic review of 14 articles conducted in 7 different countries of patients with median age of 76.4 to 86.1 years reviewed clinical outcomes of anticholinergic use in patients with dementia. Five studies found anticholinergics were associated with increased all-cause mortality in patients with dementia, and 3 studies found anticholinergics were associated with longer hospital stays. Other studies found that anticholinergics were associated with delirium and reduced health-related quality of life.5
About 35% of veterans with dementia have been prescribed a medication regimen with a high anticholinergic burden.6 In 2018, the US Department of Veterans Affairs (VA) Pharmacy Benfits Management Center for Medical Safety completed a centrally aggregated medication use evaluation (CAMUE) to assess the appropriateness of anticholinergic medication use in patients with dementia. The retrospective chart review included 1094 veterans from 19 sites. Overall, about 15% of the veterans experienced new falls, delirium, or worsening dementia within 30 days of starting an anticholinergic medication. Furthermore, < 40% had documentation of a nonanticholinergic alternative medication trial, and < 20% had documented nonpharmacologic therapy. The documentation of risk-benefit assessment acknowledging the risks of anticholinergic medication use in veterans with dementia occurred only about 13% of the time. The CAMUE concluded that the risks of initiating an anticholinergic medication in veterans with dementia are likely underdocumented and possibly under considered by prescribers.7
Developed within the Veterans Health Administration (VHA), VIONE (Vital, Important, Optional, Not Indicated, Every medication has an indication) is a medication management methodology that aims to reduce polypharmacy and improve patient safety consistent with high-reliability organizations. Since it launched in 2016, VIONE has gradually been implemented at many VHA facilities. The VIONE deprescribing dashboard had not been used at the VA Louisville Healthcare System prior to this quality improvement project.
This dashboard uses the Beers Criteria to identify potentially inappropriate anticholinergic medications. It uses the Anticholinergic Cognitive Burden (ACB) scale to calculate the cumulative anticholinergic risk for each patient. Medications with an ACB score of 2 or 3 have clinically relevant cognitive effects such as delirium and dementia (Table 1). For each point increase in total ACB score, a decline in mini-mental state examination score of 0.33 points over 2 years has been shown. Each point increase has also been correlated with a 26% increase in risk of death.8-10

Methods
The purpose of this quality improvement project was to determine the impact of pharmacist-driven deprescribing on the anticholinergic burden in veterans with dementia at VA Louisville Healthcare System. Data were obtained through the Computerized Patient Record System (CPRS) and VIONE deprescribing dashboard and entered in a secure Microsoft Excel spreadsheet. Pharmacist deprescribing steps were entered as CPRS progress notes. A deprescribing note template was created, and 11 templates with indication-specific recommendations were created for each anticholinergic indication identified (contact authors for deprescribing note template examples). Usage of anticholinergic medications was reexamined 3 months after the deprescribing note was entered.
Eligible patients identified in the VIONE deprescribing dashboard had an outpatient order for a medication with strong anticholinergic properties as identified using the Beers Criteria and were aged ≥ 65 years. Patients also had to be diagnosed with dementia or cognitive impairment. Patients were excluded if they were receiving hospice care or if the anticholinergic medication was from a non-VA prescriber or filled at a non-VA pharmacy. The VIONE deprescribing dashboard also excluded skeletal muscle relaxants if the patient had a spinal cord-related visit in the previous 2 years, first-generation antihistamines if the patient had a vertigo diagnosis, hydroxyzine if the indication was for anxiety, trospium if the indication was for overactive bladder, and antipsychotics if the patient had been diagnosed with schizophrenia or bipolar disorder. The following were included in the deprescribing recommendations if the dashboard identified the patient due to receiving a second strongly anticholinergic medication: first generation antihistamines if the patient was diagnosed with vertigo and hydroxyzine if the indication is for anxiety.
Each eligible patient received a focused medication review by a pharmacist via electronic chart review and a templated CPRS progress note with patient-specific recommendations. The prescriber and the patient’s primary care practitioner were recommended to perform a patient-specific risk-benefit assessment, deprescribe potentially inappropriate anticholinergic medications, and consider nonanticholinergic alternatives (both pharmacologic and nonpharmacologic). Data collected included baseline age, sex, prespecified comorbidities (type of dementia, cognitive impairment, delirium, benign prostatic hyperplasia/lower urinary tract symptoms), duration of prescribed anticholinergic medication, indication and deprescribing rate for each anticholinergic agent, and concurrent dementia medications (acetylcholinesterase inhibitors, memantine, or both).
The primary outcome was the number of patients that had = 1 medication with strong anticholinergic properties deprescribed. Deprescribing was defined as medication discontinuation or reduction of total daily dose. Secondary outcomes were the mean change in ACB scale, the number of patients with dose tapering, documented patient-specific risk-benefit assessment, and initiated nonanticholinergic alternative per pharmacist recommendation.
Results
The VIONE deprescribing dashboard identified 121 patients; 45 were excluded for non-VA prescriber or pharmacy, and 8 patients were excluded for other reasons. Sixty-eight patients were included in the deprescribing initiative. The mean age was 73.4 years (range, 67-93), 65 (96%) were male, and 34 (50%) had unspecified dementia (Table 2). Thirty-one patients (46%) had concurrent cholinesterase inhibitor prescriptions for dementia. The median duration of use of a strong anticholinergic medication was 11 months.

Twenty-nine patients (43%) had ≥ 1 medication with strong anticholinergic properties deprescribed. Anticholinergic medication was discontinued for 26 patients, and the dose was decreased for 3 patients. ACB score fell by a mean of 1.1 per patient. There was an increase in the documented risk-benefit assessment for anticholinergic medications from a baseline of 4 (6%) to 19 (28%) 3 months after the deprescribing note. Cyclobenzaprine, paroxetine, and oxybutynin were deprescribed the most, and amitriptyline had the lowest rate of deprescribing (Table 3). Thirty patients (44%) had a pharmacologic, nonanticholinergic alternative initiated per pharmacist recommendation, and 6 patients (9%) had a nonpharmacologic alternative initiated per pharmacist recommendation.

Discussion
This quality improvement project suggests that with the use of population health management tools such as the VIONE deprescribing dashboard, pharmacists can help identify and deprescribe strong anticholinergic medications in patients with cognitive impairment or dementia. Pharmacists can also aid in deprescribing through evidence-based recommendations to guide risk-benefit discussion and consider safer, nonanticholinergic alternatives. The authors were able to help reduce anticholinergic cognitive burden in 43% of patients in this sample. The mean 1.1 ACB score reduction was considered clinically significant based on prior studies that found that each 1-point increase in ACB score correlated with declined cognition and increased mortality.8,10 The VIONE deprescribing dashboard provided real-time patient data and helped target patients at the highest risk of anticholinergic AEs. The creation of the note templates based on the indication helped streamline recommendations. Typically, the prescriber addressed the recommendations at a routine follow-up appointment. The deprescribing method used in this project was time-efficient and could be easily replicated once the CPRS note templates were created. Future deprescribing projects could consider more direct pharmacist intervention and medication management.
Limitations
There was no direct assessment of clinical outcomes such as change in cognition using cognitive function tests. However, multiple studies have demonstrated AEs associated with strong anticholinergic medication use and additive anticholinergic burden in patients with dementia or cognitive impairment.1,5 Also, the 3-month follow-up period was relatively short. The pharmacist’s deprescribing recommendations may have been accepted after 3 months, or patients could have restarted their anticholinergic medications. Longer follow-up time could provide more robust results and conclusions. Thirdly, there was no formal definition of what constituted a risk-benefit assessment of anticholinergic medications. The risk-benefit assessment was determined at the discretion of the authors, which was subjective and allowed for bias. Finally, 6 patients died during the 3-month follow-up. The data for these patients were included in the baseline characteristics but not in the study outcomes. If these patients had been excluded from the results, a higher percentage of patients (47%) would have had ≥ 1 anticholinergic medication deprescribed.
Conclusions
In collaboration with the interdisciplinary team, pharmacist recommendations resulted in deprescribing of anticholinergic medications in veterans with dementia or cognitive impairment. The VIONE deprescribing dashboard, an easily accessible population health management tool, can identify patients prescribed potentially inappropriate medications and help target patients at the highest risk of anticholinergic AEs. To prevent worsening cognitive impairment, delirium, falls, and other AEs, this deprescribing initiative can be replicated at other VHA facilities. Future projects could have a longer follow-up period, incorporate more direct pharmacist intervention, and assess clinical outcomes of deprescribing.
- Gray SL, Hanlon JT. Anticholinergic medication use and dementia: latest evidence and clinical implications. Ther Adv Drug Saf. 2016;7(5):217-224. doi:10.1177/2042098616658399
- Kersten H, Wyller TB. Anticholinergic drug burden in older people’s brain - how well is it measured? Basic Clin Pharmacol Toxicol. 2014;114(2):151-159. doi:10.1111/bcpt.12140
- By the 2019 American Geriatrics Society Beers Criteria® Update Expert Panel. American Geriatrics Society 2019 updated AGS beers criteria® for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2019;67(4):674-694. doi:10.1111/jgs.15767
- By the 2023 American Geriatrics Society Beers Criteria® Update Expert Panel. American Geriatrics Society 2023 updated AGS Beers Criteria® for potentially inappropriate medication use in older adults J Am Geriatr Soc. 2023;71(7):2052-2081. doi:10.1111/jgs.18372
- Wang K, Alan J, Page AT, Dimopoulos E, Etherton-Beer C. Anticholinergics and clinical outcomes amongst people with pre-existing dementia: a systematic review. Maturitas. 2021;151:1-14. doi:10.1016/j.maturitas.2021.06.004
- Thorpe JM, Thorpe CT, Gellad WF, et al. Dual health care system use and high-risk prescribing in patients with dementia: a national cohort study. Ann Intern Med. 2017;166(3):157-163. doi:10.7326/M16-0551
- McCarren M, Burk M, Carico R, Glassman P, Good CB, Cunningham F. Design of a centrally aggregated medication use evaluation (CAMUE): anticholinergics in dementia. Presented at: 2019 HSR&D/QUERI National Conference; October 29-31, 2019; Washington, DC. https://www.hsrd.research.va.gov/meetings/2019/abstract-display.cfm?AbsNum=4027
- Boustani, M, Campbell, N, Munger S, et al. Impact of anticholinergics on the aging brain: a review and practical application. Aging Health. 2008;4(3):311-320. doi:10.2217/1745509.x
- Constantino-Corpuz JK, Alonso MTD. Assessment of a medication deprescribing tool on polypharmacy and cost avoidance. Fed Pract. 2021;38(7):332-336. doi:10.12788/fp.0146
- Fox C, Richardson K, Maidment ID, et al. Anticholinergic medication use and cognitive impairment in the older population: the medical research council cognitive function and ageing study. J Am Geriatr Soc. 2011;59(8):1477-1483. doi:10.1111/j.1532-5415.2011.03491.x
- Gray SL, Hanlon JT. Anticholinergic medication use and dementia: latest evidence and clinical implications. Ther Adv Drug Saf. 2016;7(5):217-224. doi:10.1177/2042098616658399
- Kersten H, Wyller TB. Anticholinergic drug burden in older people’s brain - how well is it measured? Basic Clin Pharmacol Toxicol. 2014;114(2):151-159. doi:10.1111/bcpt.12140
- By the 2019 American Geriatrics Society Beers Criteria® Update Expert Panel. American Geriatrics Society 2019 updated AGS beers criteria® for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2019;67(4):674-694. doi:10.1111/jgs.15767
- By the 2023 American Geriatrics Society Beers Criteria® Update Expert Panel. American Geriatrics Society 2023 updated AGS Beers Criteria® for potentially inappropriate medication use in older adults J Am Geriatr Soc. 2023;71(7):2052-2081. doi:10.1111/jgs.18372
- Wang K, Alan J, Page AT, Dimopoulos E, Etherton-Beer C. Anticholinergics and clinical outcomes amongst people with pre-existing dementia: a systematic review. Maturitas. 2021;151:1-14. doi:10.1016/j.maturitas.2021.06.004
- Thorpe JM, Thorpe CT, Gellad WF, et al. Dual health care system use and high-risk prescribing in patients with dementia: a national cohort study. Ann Intern Med. 2017;166(3):157-163. doi:10.7326/M16-0551
- McCarren M, Burk M, Carico R, Glassman P, Good CB, Cunningham F. Design of a centrally aggregated medication use evaluation (CAMUE): anticholinergics in dementia. Presented at: 2019 HSR&D/QUERI National Conference; October 29-31, 2019; Washington, DC. https://www.hsrd.research.va.gov/meetings/2019/abstract-display.cfm?AbsNum=4027
- Boustani, M, Campbell, N, Munger S, et al. Impact of anticholinergics on the aging brain: a review and practical application. Aging Health. 2008;4(3):311-320. doi:10.2217/1745509.x
- Constantino-Corpuz JK, Alonso MTD. Assessment of a medication deprescribing tool on polypharmacy and cost avoidance. Fed Pract. 2021;38(7):332-336. doi:10.12788/fp.0146
- Fox C, Richardson K, Maidment ID, et al. Anticholinergic medication use and cognitive impairment in the older population: the medical research council cognitive function and ageing study. J Am Geriatr Soc. 2011;59(8):1477-1483. doi:10.1111/j.1532-5415.2011.03491.x
Pharmacist-Driven Deprescribing to Reduce Anticholinergic Burden in Veterans With Dementia
Pharmacist-Driven Deprescribing to Reduce Anticholinergic Burden in Veterans With Dementia
Evaluating Use of Empagliflozin for Diabetes Management in Veterans With Chronic Kidney Disease
More than 37 million Americans have diabetes mellitus (DM), and approximately 90% have type 2 DM (T2DM), including about 25% of veterans.1,2 The current guidelines suggest that therapy depends on a patient's comorbidities, management needs, and patient-centered treatment factors.3 About 1 in 3 adults with DM have chronic kidney disease (CKD), defined as the presence of kidney damage or an estimated glomerular filtration rate (eGFR) < 60 mL/min per 1.73 m2, persisting for ≥ 3 months.4
Sodium-glucose cotransporter-2 (SGLT-2) inhibitors are a class of antihyperglycemic agents acting on the SGLT-2 proteins expressed in the renal proximal convoluted tubules. They exert their effects by preventing the reabsorption of filtered glucose from the tubular lumen. There are 4 SGLT-2 inhibitors approved by the US Food and Drug Administration: canagliflozin, dapagliflozin, empagliflozin, and ertugliflozin. Empagliflozin is currently the preferred SGLT-2 inhibitor on the US Department of Veterans Affairs (VA) formulary.
According to the American Diabetes Association guidelines, empagliflozin is considered when an individual has or is at risk for atherosclerotic cardiovascular disease, heart failure, and CKD.3 SGLT-2 inhibitors are a favorable option due to their low risk for hypoglycemia while also promoting weight loss. The EMPEROR-Reduced trial demonstrated that, in addition to benefits for patients with heart failure, empagliflozin also slowed the progressive decline in kidney function in those with and without DM.5 The purpose of this study was to evaluate the effectiveness of empagliflozin on hemoglobin A1c (HbA1c) levels in patients with CKD at the Hershel “Woody” Williams VA Medical Center (HWWVAMC) in Huntington, West Virginia, along with other laboratory test markers.
Methods
The Marshall University Institutional Review Board #1 (Medical) and the HWWVAMC institutional review board and research and development committee each reviewed and approved this study. A retrospective chart review was conducted on patients diagnosed with T2DM and stage 3 CKD who were prescribed empagliflozin for DM management between January 1, 2015, and October 1, 2022, yielding 1771 patients. Data were obtained through the VHA Corporate Data Warehouse (CDW) and stored on the VA Informatics and Computing Infrastructure (VINCI) research server.
Patients were included if they were aged 18 to 89 years, prescribed empagliflozin by a VA clinician for the treatment of T2DM, had an eGFR between 30 and 59 mL/min/1.73 m2, and had an initial HbA1c between 7% and 10%. Using further random sampling, patients were either excluded or divided into, those with stage 3a CKD and those with stage 3b CKD. The primary endpoint of this study was the change in HbA1c levels in patients with stage 3b CKD (eGFR 30-44 mL/min/1.73 m2) compared with stage 3a (eGFR 45-59 mL/min/1.73 m2) after 12 months. The secondary endpoints included effects on renal function, weight, blood pressure, incidence of adverse drug events, and cardiovascular events. Of the excluded, 38 had HbA1c < 7%, 30 had HbA1c ≥ 10%, 21 did not have data at 1-year mark, 15 had the medication discontinued due to decline in renal function, 14 discontinued their medication without documented reason, 10 discontinued their medication due to adverse drug reactions (ADRs), 12 had eGFR > 60 mL/ min/1.73 m2, 9 died within 1 year of initiation, 4 had eGFR < 30 mL/min/1.73 m2, 1 had no baseline eGFR, and 1 was the spouse of a veteran.
Statistical Analysis
All statistical analyses were performed using STATA v.15. We used t tests to examine changes within each group, along with paired t tests to compare the 2 groups. Two-sample t tests were used to analyze the continuous data at both the primary and secondary endpoints.
Results
Of the 1771 patients included in the initial data set, a randomized sample of 255 charts were reviewed, 155 were excluded, and 100 were included. Fifty patients, had stage 3a CKD and 50 had stage 3b CKD. Baseline demographics were similar between the stage 3a and 3b groups (Table 1). Both groups were predominantly White and male, with mean age > 70 years.
The primary endpoint was the differences in HbA1c levels over time and between groups for patients with stage 3a and stage 3b CKD 1 year after initiation of empagliflozin. The starting doses of empagliflozin were either 12.5 mg or 25.0 mg. For both groups, the changes in HbA1c levels were statistically significant (Table 2). HbA1c levels dropped 0.65% for the stage 3a group and 0.48% for the 3b group. When compared to one another, the results were not statistically significant (P = .51).
Secondary Endpoint
There was no statistically significant difference in serum creatinine levels within each group between baselines and 1 year later for the stage 3a (P = .21) and stage 3b (P = .22) groups, or when compared to each other (P = .67). There were statistically significant changes in weight for patients in the stage 3a group (P < .05), but not for stage 3b group (P = .06) or when compared to each other (P = .41). A statistically significant change in systolic blood pressure was observed for the stage 3a group (P = .003), but not the stage 3b group (P = .16) or when compared to each other (P = .27). There were statistically significant changes in diastolic blood pressure within the stage 3a group (P = .04), but not within the stage 3b group (P = .61) or when compared to each other (P = .31).
Ten patients discontinued empagliflozin before the 1-year mark due to ADRs, including dizziness, increased incidence of urinary tract infections, rash, and tachycardia (Table 3). Additionally, 3 ADRs resulted in the empagliflozin discontinuation after 1 year (Table 3).
Discussion
This study showed a statistically significant change in HbA1c levels for patients with stage 3a and stage 3b CKD. With eGFR levels in these 2 groups > 30 mL/min/1.73 m2, patients were able to achieve glycemic benefits. There were no significant changes to the serum creatinine levels. Both groups saw statistically significant changes in weight loss within their own group; however, there were no statistically significant changes when compared to each other. With both systolic and diastolic blood pressure, the stage 3a group had statistically significant changes.
The EMPA-REG BP study demonstrated that empagliflozin was associated with significant and clinically meaningful reductions in blood pressure and HbA1c levels compared with placebo and was well tolerated in patients with T2DM and hypertension.6,7,8
Limitations
This study had a retrospective study design, which resulted in missing information for many patients and higher rates of exclusion. The population was predominantly older, White, and male and may not reflect other populations. The starting doses of empagliflozin varied between the groups. The VA employs tablet splitting for some patients, and the available doses were either 10.0 mg, 12.5 mg, or 25.0 mg. Some prescribers start veterans at lower doses and gradually increase to the higher dose of 25.0 mg, adding to the variability in starting doses.
Patients with eGFR < 30 mL/min/1.73 m2 make it difficult to determine any potential benefit in this population. The EMPA-KIDNEY trial demonstrated that the benefits of empagliflozin treatment were consistent among patients with or without DM and regardless of eGFR at randomization.9 Furthermore, many veterans had an initial HbA1c levels outside the inclusion criteria range, which was a factor in the smaller sample size.
Conclusions
While the reduction in HbA1c levels was less in patients with stage 3b CKD compared to patients stage 3a CKD, all patients experienced a benefit. The overall incidence of ADRs was low in the study population, showing empagliflozin as a favorable choice for those with T2DM and CKD. Based on the findings of this study, empagliflozin is a potentially beneficial option for reducing HbA1c levels in patients with CKD.
- Centers for Disease Control and Prevention. Type 2 diabetes. Updated May 25, 2024. Accessed September 27, 2024. https://www.cdc.gov/diabetes/about/about-type-2-diabetes.html?CDC_AAref_Val
- US Department of Veterans Affairs, VA research on diabetes. Updated September 2019. Accessed September 27, 2024. https://www.research.va.gov/pubs/docs/va_factsheets/Diabetes.pdf
- American Diabetes Association. Standards of Medical Care in Diabetes-2022 Abridged for Primary Care Providers. Clin Diabetes. 2022;40(1):10-38. doi:10.2337/cd22-as01
- Centers for Disease Control and Prevention. Diabetes, chronic kidney disease. Updated May 15, 2024. Accessed September 27, 2024. https://www.cdc.gov/diabetes/diabetes-complications/diabetes-and-chronic-kidney-disease.html
- Packer M, Anker SD, Butler J, et al. Cardiovascular and Renal Outcomes with Empagliflozin in Heart Failure. N Engl J Med. 2020;383(15):1413-1424. doi:10.1056/NEJMoa2022190
- Tikkanen I, Narko K, Zeller C, et al. Empagliflozin reduces blood pressure in patients with type 2 diabetes and hypertension. Diabetes Care. 2015;38(3):420-428. doi:10.2337/dc14-1096
- Zinman B, Wanner C, Lachin JM, et al. Empagliflozin, cardiovascular outcomes, and mortality in type 2 diabetes. N Engl J Med. 2015;373(22):2117-2128. doi:10.1056/NEJMoa1504720
- Chilton R, Tikkanen I, Cannon CP, et al. Effects of empagliflozin on blood pressure and markers of arterial stiffness and vascular resistance in patients with type 2 diabetes. Diabetes Obes Metab. 2015;17(12):1180-1193. doi:10.1111/dom.12572
- The EMPA-KIDNEY Collaborative Group, Herrington WG, Staplin N, et al. Empagliflozin in Patients with Chronic Kidney Disease. N Engl J Med. 2023;388(2):117-127. doi:10.1056/NEJMoa2204233
More than 37 million Americans have diabetes mellitus (DM), and approximately 90% have type 2 DM (T2DM), including about 25% of veterans.1,2 The current guidelines suggest that therapy depends on a patient's comorbidities, management needs, and patient-centered treatment factors.3 About 1 in 3 adults with DM have chronic kidney disease (CKD), defined as the presence of kidney damage or an estimated glomerular filtration rate (eGFR) < 60 mL/min per 1.73 m2, persisting for ≥ 3 months.4
Sodium-glucose cotransporter-2 (SGLT-2) inhibitors are a class of antihyperglycemic agents acting on the SGLT-2 proteins expressed in the renal proximal convoluted tubules. They exert their effects by preventing the reabsorption of filtered glucose from the tubular lumen. There are 4 SGLT-2 inhibitors approved by the US Food and Drug Administration: canagliflozin, dapagliflozin, empagliflozin, and ertugliflozin. Empagliflozin is currently the preferred SGLT-2 inhibitor on the US Department of Veterans Affairs (VA) formulary.
According to the American Diabetes Association guidelines, empagliflozin is considered when an individual has or is at risk for atherosclerotic cardiovascular disease, heart failure, and CKD.3 SGLT-2 inhibitors are a favorable option due to their low risk for hypoglycemia while also promoting weight loss. The EMPEROR-Reduced trial demonstrated that, in addition to benefits for patients with heart failure, empagliflozin also slowed the progressive decline in kidney function in those with and without DM.5 The purpose of this study was to evaluate the effectiveness of empagliflozin on hemoglobin A1c (HbA1c) levels in patients with CKD at the Hershel “Woody” Williams VA Medical Center (HWWVAMC) in Huntington, West Virginia, along with other laboratory test markers.
Methods
The Marshall University Institutional Review Board #1 (Medical) and the HWWVAMC institutional review board and research and development committee each reviewed and approved this study. A retrospective chart review was conducted on patients diagnosed with T2DM and stage 3 CKD who were prescribed empagliflozin for DM management between January 1, 2015, and October 1, 2022, yielding 1771 patients. Data were obtained through the VHA Corporate Data Warehouse (CDW) and stored on the VA Informatics and Computing Infrastructure (VINCI) research server.
Patients were included if they were aged 18 to 89 years, prescribed empagliflozin by a VA clinician for the treatment of T2DM, had an eGFR between 30 and 59 mL/min/1.73 m2, and had an initial HbA1c between 7% and 10%. Using further random sampling, patients were either excluded or divided into, those with stage 3a CKD and those with stage 3b CKD. The primary endpoint of this study was the change in HbA1c levels in patients with stage 3b CKD (eGFR 30-44 mL/min/1.73 m2) compared with stage 3a (eGFR 45-59 mL/min/1.73 m2) after 12 months. The secondary endpoints included effects on renal function, weight, blood pressure, incidence of adverse drug events, and cardiovascular events. Of the excluded, 38 had HbA1c < 7%, 30 had HbA1c ≥ 10%, 21 did not have data at 1-year mark, 15 had the medication discontinued due to decline in renal function, 14 discontinued their medication without documented reason, 10 discontinued their medication due to adverse drug reactions (ADRs), 12 had eGFR > 60 mL/ min/1.73 m2, 9 died within 1 year of initiation, 4 had eGFR < 30 mL/min/1.73 m2, 1 had no baseline eGFR, and 1 was the spouse of a veteran.
Statistical Analysis
All statistical analyses were performed using STATA v.15. We used t tests to examine changes within each group, along with paired t tests to compare the 2 groups. Two-sample t tests were used to analyze the continuous data at both the primary and secondary endpoints.
Results
Of the 1771 patients included in the initial data set, a randomized sample of 255 charts were reviewed, 155 were excluded, and 100 were included. Fifty patients, had stage 3a CKD and 50 had stage 3b CKD. Baseline demographics were similar between the stage 3a and 3b groups (Table 1). Both groups were predominantly White and male, with mean age > 70 years.
The primary endpoint was the differences in HbA1c levels over time and between groups for patients with stage 3a and stage 3b CKD 1 year after initiation of empagliflozin. The starting doses of empagliflozin were either 12.5 mg or 25.0 mg. For both groups, the changes in HbA1c levels were statistically significant (Table 2). HbA1c levels dropped 0.65% for the stage 3a group and 0.48% for the 3b group. When compared to one another, the results were not statistically significant (P = .51).
Secondary Endpoint
There was no statistically significant difference in serum creatinine levels within each group between baselines and 1 year later for the stage 3a (P = .21) and stage 3b (P = .22) groups, or when compared to each other (P = .67). There were statistically significant changes in weight for patients in the stage 3a group (P < .05), but not for stage 3b group (P = .06) or when compared to each other (P = .41). A statistically significant change in systolic blood pressure was observed for the stage 3a group (P = .003), but not the stage 3b group (P = .16) or when compared to each other (P = .27). There were statistically significant changes in diastolic blood pressure within the stage 3a group (P = .04), but not within the stage 3b group (P = .61) or when compared to each other (P = .31).
Ten patients discontinued empagliflozin before the 1-year mark due to ADRs, including dizziness, increased incidence of urinary tract infections, rash, and tachycardia (Table 3). Additionally, 3 ADRs resulted in the empagliflozin discontinuation after 1 year (Table 3).
Discussion
This study showed a statistically significant change in HbA1c levels for patients with stage 3a and stage 3b CKD. With eGFR levels in these 2 groups > 30 mL/min/1.73 m2, patients were able to achieve glycemic benefits. There were no significant changes to the serum creatinine levels. Both groups saw statistically significant changes in weight loss within their own group; however, there were no statistically significant changes when compared to each other. With both systolic and diastolic blood pressure, the stage 3a group had statistically significant changes.
The EMPA-REG BP study demonstrated that empagliflozin was associated with significant and clinically meaningful reductions in blood pressure and HbA1c levels compared with placebo and was well tolerated in patients with T2DM and hypertension.6,7,8
Limitations
This study had a retrospective study design, which resulted in missing information for many patients and higher rates of exclusion. The population was predominantly older, White, and male and may not reflect other populations. The starting doses of empagliflozin varied between the groups. The VA employs tablet splitting for some patients, and the available doses were either 10.0 mg, 12.5 mg, or 25.0 mg. Some prescribers start veterans at lower doses and gradually increase to the higher dose of 25.0 mg, adding to the variability in starting doses.
Patients with eGFR < 30 mL/min/1.73 m2 make it difficult to determine any potential benefit in this population. The EMPA-KIDNEY trial demonstrated that the benefits of empagliflozin treatment were consistent among patients with or without DM and regardless of eGFR at randomization.9 Furthermore, many veterans had an initial HbA1c levels outside the inclusion criteria range, which was a factor in the smaller sample size.
Conclusions
While the reduction in HbA1c levels was less in patients with stage 3b CKD compared to patients stage 3a CKD, all patients experienced a benefit. The overall incidence of ADRs was low in the study population, showing empagliflozin as a favorable choice for those with T2DM and CKD. Based on the findings of this study, empagliflozin is a potentially beneficial option for reducing HbA1c levels in patients with CKD.
More than 37 million Americans have diabetes mellitus (DM), and approximately 90% have type 2 DM (T2DM), including about 25% of veterans.1,2 The current guidelines suggest that therapy depends on a patient's comorbidities, management needs, and patient-centered treatment factors.3 About 1 in 3 adults with DM have chronic kidney disease (CKD), defined as the presence of kidney damage or an estimated glomerular filtration rate (eGFR) < 60 mL/min per 1.73 m2, persisting for ≥ 3 months.4
Sodium-glucose cotransporter-2 (SGLT-2) inhibitors are a class of antihyperglycemic agents acting on the SGLT-2 proteins expressed in the renal proximal convoluted tubules. They exert their effects by preventing the reabsorption of filtered glucose from the tubular lumen. There are 4 SGLT-2 inhibitors approved by the US Food and Drug Administration: canagliflozin, dapagliflozin, empagliflozin, and ertugliflozin. Empagliflozin is currently the preferred SGLT-2 inhibitor on the US Department of Veterans Affairs (VA) formulary.
According to the American Diabetes Association guidelines, empagliflozin is considered when an individual has or is at risk for atherosclerotic cardiovascular disease, heart failure, and CKD.3 SGLT-2 inhibitors are a favorable option due to their low risk for hypoglycemia while also promoting weight loss. The EMPEROR-Reduced trial demonstrated that, in addition to benefits for patients with heart failure, empagliflozin also slowed the progressive decline in kidney function in those with and without DM.5 The purpose of this study was to evaluate the effectiveness of empagliflozin on hemoglobin A1c (HbA1c) levels in patients with CKD at the Hershel “Woody” Williams VA Medical Center (HWWVAMC) in Huntington, West Virginia, along with other laboratory test markers.
Methods
The Marshall University Institutional Review Board #1 (Medical) and the HWWVAMC institutional review board and research and development committee each reviewed and approved this study. A retrospective chart review was conducted on patients diagnosed with T2DM and stage 3 CKD who were prescribed empagliflozin for DM management between January 1, 2015, and October 1, 2022, yielding 1771 patients. Data were obtained through the VHA Corporate Data Warehouse (CDW) and stored on the VA Informatics and Computing Infrastructure (VINCI) research server.
Patients were included if they were aged 18 to 89 years, prescribed empagliflozin by a VA clinician for the treatment of T2DM, had an eGFR between 30 and 59 mL/min/1.73 m2, and had an initial HbA1c between 7% and 10%. Using further random sampling, patients were either excluded or divided into, those with stage 3a CKD and those with stage 3b CKD. The primary endpoint of this study was the change in HbA1c levels in patients with stage 3b CKD (eGFR 30-44 mL/min/1.73 m2) compared with stage 3a (eGFR 45-59 mL/min/1.73 m2) after 12 months. The secondary endpoints included effects on renal function, weight, blood pressure, incidence of adverse drug events, and cardiovascular events. Of the excluded, 38 had HbA1c < 7%, 30 had HbA1c ≥ 10%, 21 did not have data at 1-year mark, 15 had the medication discontinued due to decline in renal function, 14 discontinued their medication without documented reason, 10 discontinued their medication due to adverse drug reactions (ADRs), 12 had eGFR > 60 mL/ min/1.73 m2, 9 died within 1 year of initiation, 4 had eGFR < 30 mL/min/1.73 m2, 1 had no baseline eGFR, and 1 was the spouse of a veteran.
Statistical Analysis
All statistical analyses were performed using STATA v.15. We used t tests to examine changes within each group, along with paired t tests to compare the 2 groups. Two-sample t tests were used to analyze the continuous data at both the primary and secondary endpoints.
Results
Of the 1771 patients included in the initial data set, a randomized sample of 255 charts were reviewed, 155 were excluded, and 100 were included. Fifty patients, had stage 3a CKD and 50 had stage 3b CKD. Baseline demographics were similar between the stage 3a and 3b groups (Table 1). Both groups were predominantly White and male, with mean age > 70 years.
The primary endpoint was the differences in HbA1c levels over time and between groups for patients with stage 3a and stage 3b CKD 1 year after initiation of empagliflozin. The starting doses of empagliflozin were either 12.5 mg or 25.0 mg. For both groups, the changes in HbA1c levels were statistically significant (Table 2). HbA1c levels dropped 0.65% for the stage 3a group and 0.48% for the 3b group. When compared to one another, the results were not statistically significant (P = .51).
Secondary Endpoint
There was no statistically significant difference in serum creatinine levels within each group between baselines and 1 year later for the stage 3a (P = .21) and stage 3b (P = .22) groups, or when compared to each other (P = .67). There were statistically significant changes in weight for patients in the stage 3a group (P < .05), but not for stage 3b group (P = .06) or when compared to each other (P = .41). A statistically significant change in systolic blood pressure was observed for the stage 3a group (P = .003), but not the stage 3b group (P = .16) or when compared to each other (P = .27). There were statistically significant changes in diastolic blood pressure within the stage 3a group (P = .04), but not within the stage 3b group (P = .61) or when compared to each other (P = .31).
Ten patients discontinued empagliflozin before the 1-year mark due to ADRs, including dizziness, increased incidence of urinary tract infections, rash, and tachycardia (Table 3). Additionally, 3 ADRs resulted in the empagliflozin discontinuation after 1 year (Table 3).
Discussion
This study showed a statistically significant change in HbA1c levels for patients with stage 3a and stage 3b CKD. With eGFR levels in these 2 groups > 30 mL/min/1.73 m2, patients were able to achieve glycemic benefits. There were no significant changes to the serum creatinine levels. Both groups saw statistically significant changes in weight loss within their own group; however, there were no statistically significant changes when compared to each other. With both systolic and diastolic blood pressure, the stage 3a group had statistically significant changes.
The EMPA-REG BP study demonstrated that empagliflozin was associated with significant and clinically meaningful reductions in blood pressure and HbA1c levels compared with placebo and was well tolerated in patients with T2DM and hypertension.6,7,8
Limitations
This study had a retrospective study design, which resulted in missing information for many patients and higher rates of exclusion. The population was predominantly older, White, and male and may not reflect other populations. The starting doses of empagliflozin varied between the groups. The VA employs tablet splitting for some patients, and the available doses were either 10.0 mg, 12.5 mg, or 25.0 mg. Some prescribers start veterans at lower doses and gradually increase to the higher dose of 25.0 mg, adding to the variability in starting doses.
Patients with eGFR < 30 mL/min/1.73 m2 make it difficult to determine any potential benefit in this population. The EMPA-KIDNEY trial demonstrated that the benefits of empagliflozin treatment were consistent among patients with or without DM and regardless of eGFR at randomization.9 Furthermore, many veterans had an initial HbA1c levels outside the inclusion criteria range, which was a factor in the smaller sample size.
Conclusions
While the reduction in HbA1c levels was less in patients with stage 3b CKD compared to patients stage 3a CKD, all patients experienced a benefit. The overall incidence of ADRs was low in the study population, showing empagliflozin as a favorable choice for those with T2DM and CKD. Based on the findings of this study, empagliflozin is a potentially beneficial option for reducing HbA1c levels in patients with CKD.
- Centers for Disease Control and Prevention. Type 2 diabetes. Updated May 25, 2024. Accessed September 27, 2024. https://www.cdc.gov/diabetes/about/about-type-2-diabetes.html?CDC_AAref_Val
- US Department of Veterans Affairs, VA research on diabetes. Updated September 2019. Accessed September 27, 2024. https://www.research.va.gov/pubs/docs/va_factsheets/Diabetes.pdf
- American Diabetes Association. Standards of Medical Care in Diabetes-2022 Abridged for Primary Care Providers. Clin Diabetes. 2022;40(1):10-38. doi:10.2337/cd22-as01
- Centers for Disease Control and Prevention. Diabetes, chronic kidney disease. Updated May 15, 2024. Accessed September 27, 2024. https://www.cdc.gov/diabetes/diabetes-complications/diabetes-and-chronic-kidney-disease.html
- Packer M, Anker SD, Butler J, et al. Cardiovascular and Renal Outcomes with Empagliflozin in Heart Failure. N Engl J Med. 2020;383(15):1413-1424. doi:10.1056/NEJMoa2022190
- Tikkanen I, Narko K, Zeller C, et al. Empagliflozin reduces blood pressure in patients with type 2 diabetes and hypertension. Diabetes Care. 2015;38(3):420-428. doi:10.2337/dc14-1096
- Zinman B, Wanner C, Lachin JM, et al. Empagliflozin, cardiovascular outcomes, and mortality in type 2 diabetes. N Engl J Med. 2015;373(22):2117-2128. doi:10.1056/NEJMoa1504720
- Chilton R, Tikkanen I, Cannon CP, et al. Effects of empagliflozin on blood pressure and markers of arterial stiffness and vascular resistance in patients with type 2 diabetes. Diabetes Obes Metab. 2015;17(12):1180-1193. doi:10.1111/dom.12572
- The EMPA-KIDNEY Collaborative Group, Herrington WG, Staplin N, et al. Empagliflozin in Patients with Chronic Kidney Disease. N Engl J Med. 2023;388(2):117-127. doi:10.1056/NEJMoa2204233
- Centers for Disease Control and Prevention. Type 2 diabetes. Updated May 25, 2024. Accessed September 27, 2024. https://www.cdc.gov/diabetes/about/about-type-2-diabetes.html?CDC_AAref_Val
- US Department of Veterans Affairs, VA research on diabetes. Updated September 2019. Accessed September 27, 2024. https://www.research.va.gov/pubs/docs/va_factsheets/Diabetes.pdf
- American Diabetes Association. Standards of Medical Care in Diabetes-2022 Abridged for Primary Care Providers. Clin Diabetes. 2022;40(1):10-38. doi:10.2337/cd22-as01
- Centers for Disease Control and Prevention. Diabetes, chronic kidney disease. Updated May 15, 2024. Accessed September 27, 2024. https://www.cdc.gov/diabetes/diabetes-complications/diabetes-and-chronic-kidney-disease.html
- Packer M, Anker SD, Butler J, et al. Cardiovascular and Renal Outcomes with Empagliflozin in Heart Failure. N Engl J Med. 2020;383(15):1413-1424. doi:10.1056/NEJMoa2022190
- Tikkanen I, Narko K, Zeller C, et al. Empagliflozin reduces blood pressure in patients with type 2 diabetes and hypertension. Diabetes Care. 2015;38(3):420-428. doi:10.2337/dc14-1096
- Zinman B, Wanner C, Lachin JM, et al. Empagliflozin, cardiovascular outcomes, and mortality in type 2 diabetes. N Engl J Med. 2015;373(22):2117-2128. doi:10.1056/NEJMoa1504720
- Chilton R, Tikkanen I, Cannon CP, et al. Effects of empagliflozin on blood pressure and markers of arterial stiffness and vascular resistance in patients with type 2 diabetes. Diabetes Obes Metab. 2015;17(12):1180-1193. doi:10.1111/dom.12572
- The EMPA-KIDNEY Collaborative Group, Herrington WG, Staplin N, et al. Empagliflozin in Patients with Chronic Kidney Disease. N Engl J Med. 2023;388(2):117-127. doi:10.1056/NEJMoa2204233
Vancomycin AUC-Dosing Initiative at a Regional Antibiotic Stewardship Collaborative
Antimicrobial resistance is a global threat and burden to health care, with > 2.8 million antibiotic-resistant infections occurring annually in the United States.1 To combat this issue and improve patient care, the US Department of Veterans Affairs (VA) has implemented antimicrobial stewardship programs (ASPs) across its health care systems. ASPs are multidisciplinary teams that promote evidence-based use of antimicrobials through activities supporting appropriate selection, dosing, route, and duration of antimicrobial therapy. ASP best practices are also included in the Joint Commission and Centers for Medicare and Medicaid Services accreditation standards.2
The foundational charge for VA facilities to develop and maintain ASPs was outlined in 2014 and updated in 2023 in the Veterans Health Administration (VHA) Directive 1031 on antimicrobial stewardship programs.2 This directive outlines specific requirements for all VA ASPs, including personnel, staffing levels, and the roles and responsibilities of all team members. VHA now requires that Veterans Integrated Services Networks (VISNs) establish robust ASP collaboratives. A VISN ASP collaborative consists of stewardship champions from each VA medical center in the VISN and is designed to support, develop, and enhance ASP programs across all facilities within that VISN.2 Some VISNs may lack an ASP collaborative altogether, and others with existing groups may seek ways to expand their collaboratives in line with the updated directive. Prior to VHA Directive 1031, the VA Sunshine Healthcare Network (VISN 8) established an ASP collaborative. This article describes the structure and activities of the VISN 8 ASP collaborative and highlights a recent VISN 8 quality assurance initiative related to vancomycin area under the curve (AUC) dosing that illustrates how ASP collaboratives can enhance stewardship and clinical care across broad geographic areas.
VISN 8 ASP
The VHA, the largest integrated US health care system, is divided into 18 VISNs that provide regional systems of care to enhance access and meet the local health care needs of veterans.3 VISN 8 serves > 1.5 million veterans across 165,759 km2 in Florida, South Georgia, Puerto Rico, and the US Virgin Islands.4 The network is composed of 7 health systems with 8 medical centers and > 60 outpatient clinics. These facilities provide comprehensive acute, primary, and specialty care, as well as mental health and extended care services in inpatient, outpatient, nursing home, and home care settings.4
The 2023 VHA Directive 1031 update recognizes the importance of VISN-level coordination of ASP activities to enhance the standardization of care and build partnerships in stewardship across all levels of care. The VISN 8 ASP collaborative workgroup (ASPWG) was established in 2015. Consistent with Directive 1031, the ASPWG is guided by clinician and pharmacist VISN leads. These leads serve as subject matter experts, facilitate access to resources, establish VISN-level consensus, and enhance communication among local ASP champions at medical centers within the VISN. All 7 health systems include = 1 ASP champion (clinician or pharmacist) in the ASPWG. Ad hoc members, whose routine duties are not solely focused on antimicrobial stewardship, contribute to specific stewardship projects as needed. For example, the ASPWG has included internal medicine, emergency department, community living center pharmacists, representatives from pharmacy administration, and trainees (pharmacy students and residents, and infectious diseases fellows) in antimicrobial stewardship initiatives. The inclusion of non-ASP champions is not discussed in VHA Directive 1031. However, these members have made valuable contributions to the ASPWG.
The ASPWG meets monthly. Agendas and priorities are developed by the VISN pharmacist and health care practitioner (HCP) leads. Monthly discussions may include but are not limited to a review of national formulary decisions, VISN goals and metrics, infectious diseases hot topics, pharmacoeconomic initiatives, strong practice presentations, regulatory and accreditation preparation, preparation of tracking reports, as well as the development of both patient-level and HCPlevel tools, resources, and education materials. This forum facilitates collaborative learning: members process and synthesize information, share and reframe ideas, and listen to other viewpoints to gain a complete understanding as a group.5 For example, ASPWG members have leaned on each other to prepare for Joint Commission accreditation surveys and strengthen the VISN 8 COVID-19 program through the rollout of vaccines and treatments. Other collaborative projects completed over the past few years included a penicillin allergy testing initiative and anti-methicillin-resistant Staphylococcus aureus (MRSA) and pseudomonal medication use evaluations. This team-centric problem-solving approach is highly effective while also fostering professional and social relationships. However, collaboratives could be perceived to have drawbacks. There may be opportunity costs if ASP time is allocated for issues that have already been addressed locally or concerns that standardization might hinder rapid adoption of practices at individual sites. Therefore, participation in each distinct group initiative is optional. This allows sites to choose projects related to their high priority areas and maintain bandwidth to implement practices not yet adopted by the larger group.
The ASPWG tracks metrics related to antimicrobial use with quarterly data presented by the VISN pharmacist lead. Both inpatient and outpatient metrics are evaluated, such as days of therapy per 1000 days and outpatient antibiotic prescriptions per 1000 unique patients. Facilities are benchmarked against their own historical data and other VISN sites, as well as other VISNs across the country. When outliers are identified, facilities are encouraged to conduct local projects to identify reasons for different antimicrobial use patterns and subsequent initiatives to optimize antimicrobial use. Benchmarking against VISN facilities can be useful since VISN facilities may be more similar than facilities in different geographic regions. Each year, the ASPWG reviews the current metrics, makes adjustments to address VISN priorities, and votes for approval of the metrics that will be tracked in the coming year.
Participation in an ASP collaborative streamlines the rollout of ASP and quality improvement initiatives across multiple sites, allowing ASPs to impact a greater number of veterans and evaluate initiatives on a larger scale. In 2019, with the anticipation of revised vancomycin dosing and monitoring guidelines, our ASPWG began to strategize the transition to AUC-based vancomycin monitoring.6 This multisite initiative showcases the strengths of implementing and evaluating practice changes as part of an ASP collaborative.
Vancomycin Dosing
The antibiotic vancomycin is used primarily for the treatment of MRSA infections.6 The 2020 consensus guidelines for vancomycin therapeutic monitoring recommend using the AUC to minimum inhibitory concentration (MIC) ratio as the pharmacodynamic target for serious MRSA infections, with an AUC/MIC goal of 400 to 600 mcg*h/mL.6 Prior guidelines recommended using vancomycin trough concentrations of 15 to 20 mcg/mL as a surrogate for this AUC target. However, subsequent studies have shown that trough-based dosing is associated with higher vancomycin exposures, supratherapeutic AUCs, and increased risk of vancomycin-associated acute kidney injury (AKI).7,8 Therefore, more direct AUC estimation is now recommended.6 The preferred approach for AUC calculations is through Bayesian modeling. Due to limited resources and software availability, many facilities use an alternative method involving 2 postdistributive serum vancomycin concentrations and first-order pharmacokinetic equations. This approach can optimize vancomycin dosing but is more mathematically and logistically challenging. Transitioning from troughto AUC-based vancomycin monitoring requires careful planning and comprehensive staff education.
In 2019, the VISN 8 ASPWG created a comprehensive vancomycin AUC toolkit to facilitate implementation. Components included a pharmacokinetic management policy and procedure, a vancomycin dosing guide, a progress note template, educational materials specific to pharmacy, nursing, laboratory, and medical services, a pharmacist competency examination, and a vancomycin AUC calculator (eAppendix). Each component was developed by a subgroup with the understanding that sites could incorporate variations based on local practices and needs.
The vancomycin AUC calculator was developed to be user-friendly and included safety validation protocols to prevent the entry of erroneous data (eg, unrealistic patient weight or laboratory values). The calculator allowed users to copy data into the electronic health record to avoid manual transcription errors and improve operational efficiency. It offered suggested volume of distribution estimates and 2 methods to estimate elimination constant (Ke ) depending on the patient’s weight.9,10 Creatinine clearance could be estimated using serum creatinine or cystatin C and considered amputation history. The default AUC goal in the calculator was 400 to 550 mcg*h/mL. This range was chosen based on consensus guidelines, data suggesting increased risk of AKI with AUCs > 515 mcg*h/mL, and the preference for conservative empiric dosing in the generally older VA population.11 The calculator suggested loading doses of about 25 mg/kg with a 2500 mg limit. VHA facilities could make limited modifications to the calculator based on local policies and procedures (eg, adjusting default infusion times or a dosing intervals).
The VISN 8 Pharmacy Pharmacokinetic Dosing Manual was developed as a comprehensive document to guide pharmacy staff with dosing vancomycin across diverse patient populations. This document included recommendations for renal function assessment, patient-specific considerations when choosing an empiric vancomycin dose, methods of ordering vancomycin peak, trough, and surveillance levels, dose determination based on 2 levels, and other clinical insights or frequently asked questions.
ASPWG members presented an accredited continuing education webinar for pharmacists, which reviewed the rationale for AUC-targeted dosing, changes to the current pharmacokinetic dosing program, case-based scenarios across various patient populations, and potential challenges associated with vancomycin AUC-based dosing. A recording of the live training was also made available. A vancomycin AUC dosing competency test was developed with 11 basic pharmacokinetic and case-based questions and comprehensive explanations provided for each answer.
VHA facilities implemented AUC dosing in a staggered manner, allowing for lessons learned at earlier adopters to be addressed proactively at later sites. The dosing calculator and education documents were updated iteratively as opportunities for improvement were discovered. ASPWG members held local office hours to address questions or concerns from staff at their facilities. Sharing standardized materials across the VISN reduced individual site workload and complications in rolling out this complex new process.
VISN-WIDE QUALITY ASSURANCE
At the time of project conception, 4 of 7 VISN 8 health systems had transitioned to AUC-based dosing. A quality assurance protocol to compare patient outcomes before and after changing to AUC dosing was developed. Each site followed local protocols for project approval and data were deidentified, collected, and aggregated for analysis.
The primary objectives were to compare the incidence of AKI and persistent bacteremia and assess rates of AUC target attainment (400-600 mcg*h/mL) in the AUC-based and trough-based dosing groups.6 Data for both groups included anthropomorphic measurements, serum creatinine, amputation status, vancomycin dosing, and infection characteristics. The X2 test was used for categorical data and the t test was used for continuous data. A 2-tailed α of 0.05 was used to determine significance. Each site sequentially reviewed all patients receiving ≥ 48 hours of intravenous vancomycin over a 3-month period and contributed up to 50 patients for each group. Due to staggered implementation, the study periods for sites spanned 2018 to 2023. A minimum 6-month washout period was observed between the trough and AUC groups at each site. Patients were excluded if pregnant, receiving renal replacement therapy, or presenting with AKI at the time of vancomycin initiation.
There were 168 patients in the AUC group and 172 patients in the trough group (Table 1). The rate of AUC target attainment with the initial dosing regimen varied across sites from 18% to 69% (mean, 48%). Total daily vancomycin exposure was lower in the AUC group compared with the trough group (2402 mg vs 2605 mg, respectively), with AUC-dosed patients being less likely to experience troughs level ≥ 15 or 20 mcg/mL (Table 2). There was a statistically significant lower rate of AKI in the AUC group: 2.4% in the AUC group (range, 2%-3%) vs 10.4% (range 7%-12%) in the trough group (P = .002). Rates of AKI were comparable to those observed in previous interventions.6 There was no statistical difference in length of stay, time to blood culture clearance, or rate of persistent bacteremia in the 2 groups, but these assessments were limited by sample size.
We did not anticipate such variability in initial target attainment across sites. The multisite quality assurance design allowed for qualitative evaluation of variability in dosing practices, which likely arose from sites and individual pharmacists having some flexibility in adjusting dosing tool parameters. Further analysis revealed that the facility with low initial target attainment was not routinely utilizing vancomycin loading doses. Sites routinely use robust loading doses achieved earlier and more consistent target attainment. Some sites used a narrower AUC target range in certain clinical scenarios (eg, > 500 mcg*h/mL for septic patients and < 500 mcg*h/mL for patients with less severe infections) rather than the 400 to 550 mcg*h/mL range for all patients. Sites targeting broader AUC ranges for all patients had higher rates of target attainment. Reviewing differences among sites allowed the ASPWG to identify best practices to optimize future care.
CONCLUSIONS
VHA ASPs must meet the standards outlined in VHA Directive 1031, including the new requirement for each VISN to develop an ASP collaborative. The VISN 8 ASPWG demonstrates how ASP champions can collaborate to solve common issues, complete tasks, explore new infectious diseases concepts, and impact large veteran populations. Furthermore, ASP collaboratives can harness their collective size to complete robust quality assurance evaluations that might otherwise be underpowered if completed at a single center. A limitation of the collaborative model is that a site with a robust ASP may already have specific practices in place. Expanding the ASP collaborative model further highlights the VHA role as a nationwide leader in ASP best practices.
- Centers for Disease Control and Prevention. Antibiotic resistance threats in the United States, 2019. Updated December 2019. Accessed September 10, 2024. https:// www.cdc.gov/antimicrobial-resistance/media/pdfs/2019-ar-threats-report-508.pdf
- US Department of Veterans Affairs. Antimicrobial stewardship programs. Updated September 22, 2023. Accessed September 13, 2024. https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=11458
- US Department of Veterans Affairs, Veteran Health Administration. Veterans Integrated Service Networks (VISNs). Accessed September 13, 2024. https://www.va.gov/HEALTH/visns.asp
- US Department of Veterans Affairs. Veterans Health Administration, Veterans Integrated Service Networks, VISN 08. Updated September 10, 2024. Accessed September 13, 2024. https://department.va.gov/integrated-service-networks/visn-08/
- Andreev I. What is collaborative learning? Theory, examples of activities. Valamis. Updated July 10, 2024. Accessed September 10, 2024. https://www.valamis.com/hub/collaborative-learning
- Rybak MJ, Le J, Lodise TP, et al. Therapeutic monitoring of vancomycin for serious methicillin-resistant staphylococcus aureus infections: a revised consensus guideline and review by the American Society of Health-System Pharmacists, the Infectious Diseases Society of America, the Pediatric Infectious Diseases Society, and the Society of Infectious Diseases Pharmacists. Am J Health Syst Pharm. 2020;77(11):835-864. doi:10.1093/ajhp/zxaa036
- Finch NA, Zasowski EJ, Murray KP, et al. A quasi-experiment to study the impact of vancomycin area under the concentration-time curve-guided dosing on vancomycinassociated nephrotoxicity. Antimicrob Agents Chemother. 2017;61(12):e01293-17. doi:10.1128/AAC.01293-17
- Zasowski EJ, Murray KP, Trinh TD, et al. Identification of vancomycin exposure-toxicity thresholds in hospitalized patients receiving intravenous vancomycin. Antimicrob Agents Chemother. 2017;62(1):e01684-17. doi:10.1128/AAC.01684-17
- Matzke GR, Kovarik JM, Rybak MJ, Boike SC. Evaluation of the vancomycin-clearance: creatinine-clearance relationship for predicting vancomycin dosage. Clin Pharm. 1985;4(3):311-315.
- Crass RL, Dunn R, Hong J, Krop LC, Pai MP. Dosing vancomycin in the super obese: less is more. J Antimicrob Chemother. 2018;73(11):3081-3086. doi:10.1093/jac/dky310
- Lodise TP, Rosenkranz SL, Finnemeyer M, et al. The emperor’s new clothes: prospective observational evaluation of the association between initial vancomycIn exposure and failure rates among adult hospitalized patients with methicillin-resistant staphylococcus aureus bloodstream infections (PROVIDE). Clin Infect Dis. 2020;70(8):1536-1545. doi:10.1093/cid/ciz460
Antimicrobial resistance is a global threat and burden to health care, with > 2.8 million antibiotic-resistant infections occurring annually in the United States.1 To combat this issue and improve patient care, the US Department of Veterans Affairs (VA) has implemented antimicrobial stewardship programs (ASPs) across its health care systems. ASPs are multidisciplinary teams that promote evidence-based use of antimicrobials through activities supporting appropriate selection, dosing, route, and duration of antimicrobial therapy. ASP best practices are also included in the Joint Commission and Centers for Medicare and Medicaid Services accreditation standards.2
The foundational charge for VA facilities to develop and maintain ASPs was outlined in 2014 and updated in 2023 in the Veterans Health Administration (VHA) Directive 1031 on antimicrobial stewardship programs.2 This directive outlines specific requirements for all VA ASPs, including personnel, staffing levels, and the roles and responsibilities of all team members. VHA now requires that Veterans Integrated Services Networks (VISNs) establish robust ASP collaboratives. A VISN ASP collaborative consists of stewardship champions from each VA medical center in the VISN and is designed to support, develop, and enhance ASP programs across all facilities within that VISN.2 Some VISNs may lack an ASP collaborative altogether, and others with existing groups may seek ways to expand their collaboratives in line with the updated directive. Prior to VHA Directive 1031, the VA Sunshine Healthcare Network (VISN 8) established an ASP collaborative. This article describes the structure and activities of the VISN 8 ASP collaborative and highlights a recent VISN 8 quality assurance initiative related to vancomycin area under the curve (AUC) dosing that illustrates how ASP collaboratives can enhance stewardship and clinical care across broad geographic areas.
VISN 8 ASP
The VHA, the largest integrated US health care system, is divided into 18 VISNs that provide regional systems of care to enhance access and meet the local health care needs of veterans.3 VISN 8 serves > 1.5 million veterans across 165,759 km2 in Florida, South Georgia, Puerto Rico, and the US Virgin Islands.4 The network is composed of 7 health systems with 8 medical centers and > 60 outpatient clinics. These facilities provide comprehensive acute, primary, and specialty care, as well as mental health and extended care services in inpatient, outpatient, nursing home, and home care settings.4
The 2023 VHA Directive 1031 update recognizes the importance of VISN-level coordination of ASP activities to enhance the standardization of care and build partnerships in stewardship across all levels of care. The VISN 8 ASP collaborative workgroup (ASPWG) was established in 2015. Consistent with Directive 1031, the ASPWG is guided by clinician and pharmacist VISN leads. These leads serve as subject matter experts, facilitate access to resources, establish VISN-level consensus, and enhance communication among local ASP champions at medical centers within the VISN. All 7 health systems include = 1 ASP champion (clinician or pharmacist) in the ASPWG. Ad hoc members, whose routine duties are not solely focused on antimicrobial stewardship, contribute to specific stewardship projects as needed. For example, the ASPWG has included internal medicine, emergency department, community living center pharmacists, representatives from pharmacy administration, and trainees (pharmacy students and residents, and infectious diseases fellows) in antimicrobial stewardship initiatives. The inclusion of non-ASP champions is not discussed in VHA Directive 1031. However, these members have made valuable contributions to the ASPWG.
The ASPWG meets monthly. Agendas and priorities are developed by the VISN pharmacist and health care practitioner (HCP) leads. Monthly discussions may include but are not limited to a review of national formulary decisions, VISN goals and metrics, infectious diseases hot topics, pharmacoeconomic initiatives, strong practice presentations, regulatory and accreditation preparation, preparation of tracking reports, as well as the development of both patient-level and HCPlevel tools, resources, and education materials. This forum facilitates collaborative learning: members process and synthesize information, share and reframe ideas, and listen to other viewpoints to gain a complete understanding as a group.5 For example, ASPWG members have leaned on each other to prepare for Joint Commission accreditation surveys and strengthen the VISN 8 COVID-19 program through the rollout of vaccines and treatments. Other collaborative projects completed over the past few years included a penicillin allergy testing initiative and anti-methicillin-resistant Staphylococcus aureus (MRSA) and pseudomonal medication use evaluations. This team-centric problem-solving approach is highly effective while also fostering professional and social relationships. However, collaboratives could be perceived to have drawbacks. There may be opportunity costs if ASP time is allocated for issues that have already been addressed locally or concerns that standardization might hinder rapid adoption of practices at individual sites. Therefore, participation in each distinct group initiative is optional. This allows sites to choose projects related to their high priority areas and maintain bandwidth to implement practices not yet adopted by the larger group.
The ASPWG tracks metrics related to antimicrobial use with quarterly data presented by the VISN pharmacist lead. Both inpatient and outpatient metrics are evaluated, such as days of therapy per 1000 days and outpatient antibiotic prescriptions per 1000 unique patients. Facilities are benchmarked against their own historical data and other VISN sites, as well as other VISNs across the country. When outliers are identified, facilities are encouraged to conduct local projects to identify reasons for different antimicrobial use patterns and subsequent initiatives to optimize antimicrobial use. Benchmarking against VISN facilities can be useful since VISN facilities may be more similar than facilities in different geographic regions. Each year, the ASPWG reviews the current metrics, makes adjustments to address VISN priorities, and votes for approval of the metrics that will be tracked in the coming year.
Participation in an ASP collaborative streamlines the rollout of ASP and quality improvement initiatives across multiple sites, allowing ASPs to impact a greater number of veterans and evaluate initiatives on a larger scale. In 2019, with the anticipation of revised vancomycin dosing and monitoring guidelines, our ASPWG began to strategize the transition to AUC-based vancomycin monitoring.6 This multisite initiative showcases the strengths of implementing and evaluating practice changes as part of an ASP collaborative.
Vancomycin Dosing
The antibiotic vancomycin is used primarily for the treatment of MRSA infections.6 The 2020 consensus guidelines for vancomycin therapeutic monitoring recommend using the AUC to minimum inhibitory concentration (MIC) ratio as the pharmacodynamic target for serious MRSA infections, with an AUC/MIC goal of 400 to 600 mcg*h/mL.6 Prior guidelines recommended using vancomycin trough concentrations of 15 to 20 mcg/mL as a surrogate for this AUC target. However, subsequent studies have shown that trough-based dosing is associated with higher vancomycin exposures, supratherapeutic AUCs, and increased risk of vancomycin-associated acute kidney injury (AKI).7,8 Therefore, more direct AUC estimation is now recommended.6 The preferred approach for AUC calculations is through Bayesian modeling. Due to limited resources and software availability, many facilities use an alternative method involving 2 postdistributive serum vancomycin concentrations and first-order pharmacokinetic equations. This approach can optimize vancomycin dosing but is more mathematically and logistically challenging. Transitioning from troughto AUC-based vancomycin monitoring requires careful planning and comprehensive staff education.
In 2019, the VISN 8 ASPWG created a comprehensive vancomycin AUC toolkit to facilitate implementation. Components included a pharmacokinetic management policy and procedure, a vancomycin dosing guide, a progress note template, educational materials specific to pharmacy, nursing, laboratory, and medical services, a pharmacist competency examination, and a vancomycin AUC calculator (eAppendix). Each component was developed by a subgroup with the understanding that sites could incorporate variations based on local practices and needs.
The vancomycin AUC calculator was developed to be user-friendly and included safety validation protocols to prevent the entry of erroneous data (eg, unrealistic patient weight or laboratory values). The calculator allowed users to copy data into the electronic health record to avoid manual transcription errors and improve operational efficiency. It offered suggested volume of distribution estimates and 2 methods to estimate elimination constant (Ke ) depending on the patient’s weight.9,10 Creatinine clearance could be estimated using serum creatinine or cystatin C and considered amputation history. The default AUC goal in the calculator was 400 to 550 mcg*h/mL. This range was chosen based on consensus guidelines, data suggesting increased risk of AKI with AUCs > 515 mcg*h/mL, and the preference for conservative empiric dosing in the generally older VA population.11 The calculator suggested loading doses of about 25 mg/kg with a 2500 mg limit. VHA facilities could make limited modifications to the calculator based on local policies and procedures (eg, adjusting default infusion times or a dosing intervals).
The VISN 8 Pharmacy Pharmacokinetic Dosing Manual was developed as a comprehensive document to guide pharmacy staff with dosing vancomycin across diverse patient populations. This document included recommendations for renal function assessment, patient-specific considerations when choosing an empiric vancomycin dose, methods of ordering vancomycin peak, trough, and surveillance levels, dose determination based on 2 levels, and other clinical insights or frequently asked questions.
ASPWG members presented an accredited continuing education webinar for pharmacists, which reviewed the rationale for AUC-targeted dosing, changes to the current pharmacokinetic dosing program, case-based scenarios across various patient populations, and potential challenges associated with vancomycin AUC-based dosing. A recording of the live training was also made available. A vancomycin AUC dosing competency test was developed with 11 basic pharmacokinetic and case-based questions and comprehensive explanations provided for each answer.
VHA facilities implemented AUC dosing in a staggered manner, allowing for lessons learned at earlier adopters to be addressed proactively at later sites. The dosing calculator and education documents were updated iteratively as opportunities for improvement were discovered. ASPWG members held local office hours to address questions or concerns from staff at their facilities. Sharing standardized materials across the VISN reduced individual site workload and complications in rolling out this complex new process.
VISN-WIDE QUALITY ASSURANCE
At the time of project conception, 4 of 7 VISN 8 health systems had transitioned to AUC-based dosing. A quality assurance protocol to compare patient outcomes before and after changing to AUC dosing was developed. Each site followed local protocols for project approval and data were deidentified, collected, and aggregated for analysis.
The primary objectives were to compare the incidence of AKI and persistent bacteremia and assess rates of AUC target attainment (400-600 mcg*h/mL) in the AUC-based and trough-based dosing groups.6 Data for both groups included anthropomorphic measurements, serum creatinine, amputation status, vancomycin dosing, and infection characteristics. The X2 test was used for categorical data and the t test was used for continuous data. A 2-tailed α of 0.05 was used to determine significance. Each site sequentially reviewed all patients receiving ≥ 48 hours of intravenous vancomycin over a 3-month period and contributed up to 50 patients for each group. Due to staggered implementation, the study periods for sites spanned 2018 to 2023. A minimum 6-month washout period was observed between the trough and AUC groups at each site. Patients were excluded if pregnant, receiving renal replacement therapy, or presenting with AKI at the time of vancomycin initiation.
There were 168 patients in the AUC group and 172 patients in the trough group (Table 1). The rate of AUC target attainment with the initial dosing regimen varied across sites from 18% to 69% (mean, 48%). Total daily vancomycin exposure was lower in the AUC group compared with the trough group (2402 mg vs 2605 mg, respectively), with AUC-dosed patients being less likely to experience troughs level ≥ 15 or 20 mcg/mL (Table 2). There was a statistically significant lower rate of AKI in the AUC group: 2.4% in the AUC group (range, 2%-3%) vs 10.4% (range 7%-12%) in the trough group (P = .002). Rates of AKI were comparable to those observed in previous interventions.6 There was no statistical difference in length of stay, time to blood culture clearance, or rate of persistent bacteremia in the 2 groups, but these assessments were limited by sample size.
We did not anticipate such variability in initial target attainment across sites. The multisite quality assurance design allowed for qualitative evaluation of variability in dosing practices, which likely arose from sites and individual pharmacists having some flexibility in adjusting dosing tool parameters. Further analysis revealed that the facility with low initial target attainment was not routinely utilizing vancomycin loading doses. Sites routinely use robust loading doses achieved earlier and more consistent target attainment. Some sites used a narrower AUC target range in certain clinical scenarios (eg, > 500 mcg*h/mL for septic patients and < 500 mcg*h/mL for patients with less severe infections) rather than the 400 to 550 mcg*h/mL range for all patients. Sites targeting broader AUC ranges for all patients had higher rates of target attainment. Reviewing differences among sites allowed the ASPWG to identify best practices to optimize future care.
CONCLUSIONS
VHA ASPs must meet the standards outlined in VHA Directive 1031, including the new requirement for each VISN to develop an ASP collaborative. The VISN 8 ASPWG demonstrates how ASP champions can collaborate to solve common issues, complete tasks, explore new infectious diseases concepts, and impact large veteran populations. Furthermore, ASP collaboratives can harness their collective size to complete robust quality assurance evaluations that might otherwise be underpowered if completed at a single center. A limitation of the collaborative model is that a site with a robust ASP may already have specific practices in place. Expanding the ASP collaborative model further highlights the VHA role as a nationwide leader in ASP best practices.
Antimicrobial resistance is a global threat and burden to health care, with > 2.8 million antibiotic-resistant infections occurring annually in the United States.1 To combat this issue and improve patient care, the US Department of Veterans Affairs (VA) has implemented antimicrobial stewardship programs (ASPs) across its health care systems. ASPs are multidisciplinary teams that promote evidence-based use of antimicrobials through activities supporting appropriate selection, dosing, route, and duration of antimicrobial therapy. ASP best practices are also included in the Joint Commission and Centers for Medicare and Medicaid Services accreditation standards.2
The foundational charge for VA facilities to develop and maintain ASPs was outlined in 2014 and updated in 2023 in the Veterans Health Administration (VHA) Directive 1031 on antimicrobial stewardship programs.2 This directive outlines specific requirements for all VA ASPs, including personnel, staffing levels, and the roles and responsibilities of all team members. VHA now requires that Veterans Integrated Services Networks (VISNs) establish robust ASP collaboratives. A VISN ASP collaborative consists of stewardship champions from each VA medical center in the VISN and is designed to support, develop, and enhance ASP programs across all facilities within that VISN.2 Some VISNs may lack an ASP collaborative altogether, and others with existing groups may seek ways to expand their collaboratives in line with the updated directive. Prior to VHA Directive 1031, the VA Sunshine Healthcare Network (VISN 8) established an ASP collaborative. This article describes the structure and activities of the VISN 8 ASP collaborative and highlights a recent VISN 8 quality assurance initiative related to vancomycin area under the curve (AUC) dosing that illustrates how ASP collaboratives can enhance stewardship and clinical care across broad geographic areas.
VISN 8 ASP
The VHA, the largest integrated US health care system, is divided into 18 VISNs that provide regional systems of care to enhance access and meet the local health care needs of veterans.3 VISN 8 serves > 1.5 million veterans across 165,759 km2 in Florida, South Georgia, Puerto Rico, and the US Virgin Islands.4 The network is composed of 7 health systems with 8 medical centers and > 60 outpatient clinics. These facilities provide comprehensive acute, primary, and specialty care, as well as mental health and extended care services in inpatient, outpatient, nursing home, and home care settings.4
The 2023 VHA Directive 1031 update recognizes the importance of VISN-level coordination of ASP activities to enhance the standardization of care and build partnerships in stewardship across all levels of care. The VISN 8 ASP collaborative workgroup (ASPWG) was established in 2015. Consistent with Directive 1031, the ASPWG is guided by clinician and pharmacist VISN leads. These leads serve as subject matter experts, facilitate access to resources, establish VISN-level consensus, and enhance communication among local ASP champions at medical centers within the VISN. All 7 health systems include = 1 ASP champion (clinician or pharmacist) in the ASPWG. Ad hoc members, whose routine duties are not solely focused on antimicrobial stewardship, contribute to specific stewardship projects as needed. For example, the ASPWG has included internal medicine, emergency department, community living center pharmacists, representatives from pharmacy administration, and trainees (pharmacy students and residents, and infectious diseases fellows) in antimicrobial stewardship initiatives. The inclusion of non-ASP champions is not discussed in VHA Directive 1031. However, these members have made valuable contributions to the ASPWG.
The ASPWG meets monthly. Agendas and priorities are developed by the VISN pharmacist and health care practitioner (HCP) leads. Monthly discussions may include but are not limited to a review of national formulary decisions, VISN goals and metrics, infectious diseases hot topics, pharmacoeconomic initiatives, strong practice presentations, regulatory and accreditation preparation, preparation of tracking reports, as well as the development of both patient-level and HCPlevel tools, resources, and education materials. This forum facilitates collaborative learning: members process and synthesize information, share and reframe ideas, and listen to other viewpoints to gain a complete understanding as a group.5 For example, ASPWG members have leaned on each other to prepare for Joint Commission accreditation surveys and strengthen the VISN 8 COVID-19 program through the rollout of vaccines and treatments. Other collaborative projects completed over the past few years included a penicillin allergy testing initiative and anti-methicillin-resistant Staphylococcus aureus (MRSA) and pseudomonal medication use evaluations. This team-centric problem-solving approach is highly effective while also fostering professional and social relationships. However, collaboratives could be perceived to have drawbacks. There may be opportunity costs if ASP time is allocated for issues that have already been addressed locally or concerns that standardization might hinder rapid adoption of practices at individual sites. Therefore, participation in each distinct group initiative is optional. This allows sites to choose projects related to their high priority areas and maintain bandwidth to implement practices not yet adopted by the larger group.
The ASPWG tracks metrics related to antimicrobial use with quarterly data presented by the VISN pharmacist lead. Both inpatient and outpatient metrics are evaluated, such as days of therapy per 1000 days and outpatient antibiotic prescriptions per 1000 unique patients. Facilities are benchmarked against their own historical data and other VISN sites, as well as other VISNs across the country. When outliers are identified, facilities are encouraged to conduct local projects to identify reasons for different antimicrobial use patterns and subsequent initiatives to optimize antimicrobial use. Benchmarking against VISN facilities can be useful since VISN facilities may be more similar than facilities in different geographic regions. Each year, the ASPWG reviews the current metrics, makes adjustments to address VISN priorities, and votes for approval of the metrics that will be tracked in the coming year.
Participation in an ASP collaborative streamlines the rollout of ASP and quality improvement initiatives across multiple sites, allowing ASPs to impact a greater number of veterans and evaluate initiatives on a larger scale. In 2019, with the anticipation of revised vancomycin dosing and monitoring guidelines, our ASPWG began to strategize the transition to AUC-based vancomycin monitoring.6 This multisite initiative showcases the strengths of implementing and evaluating practice changes as part of an ASP collaborative.
Vancomycin Dosing
The antibiotic vancomycin is used primarily for the treatment of MRSA infections.6 The 2020 consensus guidelines for vancomycin therapeutic monitoring recommend using the AUC to minimum inhibitory concentration (MIC) ratio as the pharmacodynamic target for serious MRSA infections, with an AUC/MIC goal of 400 to 600 mcg*h/mL.6 Prior guidelines recommended using vancomycin trough concentrations of 15 to 20 mcg/mL as a surrogate for this AUC target. However, subsequent studies have shown that trough-based dosing is associated with higher vancomycin exposures, supratherapeutic AUCs, and increased risk of vancomycin-associated acute kidney injury (AKI).7,8 Therefore, more direct AUC estimation is now recommended.6 The preferred approach for AUC calculations is through Bayesian modeling. Due to limited resources and software availability, many facilities use an alternative method involving 2 postdistributive serum vancomycin concentrations and first-order pharmacokinetic equations. This approach can optimize vancomycin dosing but is more mathematically and logistically challenging. Transitioning from troughto AUC-based vancomycin monitoring requires careful planning and comprehensive staff education.
In 2019, the VISN 8 ASPWG created a comprehensive vancomycin AUC toolkit to facilitate implementation. Components included a pharmacokinetic management policy and procedure, a vancomycin dosing guide, a progress note template, educational materials specific to pharmacy, nursing, laboratory, and medical services, a pharmacist competency examination, and a vancomycin AUC calculator (eAppendix). Each component was developed by a subgroup with the understanding that sites could incorporate variations based on local practices and needs.
The vancomycin AUC calculator was developed to be user-friendly and included safety validation protocols to prevent the entry of erroneous data (eg, unrealistic patient weight or laboratory values). The calculator allowed users to copy data into the electronic health record to avoid manual transcription errors and improve operational efficiency. It offered suggested volume of distribution estimates and 2 methods to estimate elimination constant (Ke ) depending on the patient’s weight.9,10 Creatinine clearance could be estimated using serum creatinine or cystatin C and considered amputation history. The default AUC goal in the calculator was 400 to 550 mcg*h/mL. This range was chosen based on consensus guidelines, data suggesting increased risk of AKI with AUCs > 515 mcg*h/mL, and the preference for conservative empiric dosing in the generally older VA population.11 The calculator suggested loading doses of about 25 mg/kg with a 2500 mg limit. VHA facilities could make limited modifications to the calculator based on local policies and procedures (eg, adjusting default infusion times or a dosing intervals).
The VISN 8 Pharmacy Pharmacokinetic Dosing Manual was developed as a comprehensive document to guide pharmacy staff with dosing vancomycin across diverse patient populations. This document included recommendations for renal function assessment, patient-specific considerations when choosing an empiric vancomycin dose, methods of ordering vancomycin peak, trough, and surveillance levels, dose determination based on 2 levels, and other clinical insights or frequently asked questions.
ASPWG members presented an accredited continuing education webinar for pharmacists, which reviewed the rationale for AUC-targeted dosing, changes to the current pharmacokinetic dosing program, case-based scenarios across various patient populations, and potential challenges associated with vancomycin AUC-based dosing. A recording of the live training was also made available. A vancomycin AUC dosing competency test was developed with 11 basic pharmacokinetic and case-based questions and comprehensive explanations provided for each answer.
VHA facilities implemented AUC dosing in a staggered manner, allowing for lessons learned at earlier adopters to be addressed proactively at later sites. The dosing calculator and education documents were updated iteratively as opportunities for improvement were discovered. ASPWG members held local office hours to address questions or concerns from staff at their facilities. Sharing standardized materials across the VISN reduced individual site workload and complications in rolling out this complex new process.
VISN-WIDE QUALITY ASSURANCE
At the time of project conception, 4 of 7 VISN 8 health systems had transitioned to AUC-based dosing. A quality assurance protocol to compare patient outcomes before and after changing to AUC dosing was developed. Each site followed local protocols for project approval and data were deidentified, collected, and aggregated for analysis.
The primary objectives were to compare the incidence of AKI and persistent bacteremia and assess rates of AUC target attainment (400-600 mcg*h/mL) in the AUC-based and trough-based dosing groups.6 Data for both groups included anthropomorphic measurements, serum creatinine, amputation status, vancomycin dosing, and infection characteristics. The X2 test was used for categorical data and the t test was used for continuous data. A 2-tailed α of 0.05 was used to determine significance. Each site sequentially reviewed all patients receiving ≥ 48 hours of intravenous vancomycin over a 3-month period and contributed up to 50 patients for each group. Due to staggered implementation, the study periods for sites spanned 2018 to 2023. A minimum 6-month washout period was observed between the trough and AUC groups at each site. Patients were excluded if pregnant, receiving renal replacement therapy, or presenting with AKI at the time of vancomycin initiation.
There were 168 patients in the AUC group and 172 patients in the trough group (Table 1). The rate of AUC target attainment with the initial dosing regimen varied across sites from 18% to 69% (mean, 48%). Total daily vancomycin exposure was lower in the AUC group compared with the trough group (2402 mg vs 2605 mg, respectively), with AUC-dosed patients being less likely to experience troughs level ≥ 15 or 20 mcg/mL (Table 2). There was a statistically significant lower rate of AKI in the AUC group: 2.4% in the AUC group (range, 2%-3%) vs 10.4% (range 7%-12%) in the trough group (P = .002). Rates of AKI were comparable to those observed in previous interventions.6 There was no statistical difference in length of stay, time to blood culture clearance, or rate of persistent bacteremia in the 2 groups, but these assessments were limited by sample size.
We did not anticipate such variability in initial target attainment across sites. The multisite quality assurance design allowed for qualitative evaluation of variability in dosing practices, which likely arose from sites and individual pharmacists having some flexibility in adjusting dosing tool parameters. Further analysis revealed that the facility with low initial target attainment was not routinely utilizing vancomycin loading doses. Sites routinely use robust loading doses achieved earlier and more consistent target attainment. Some sites used a narrower AUC target range in certain clinical scenarios (eg, > 500 mcg*h/mL for septic patients and < 500 mcg*h/mL for patients with less severe infections) rather than the 400 to 550 mcg*h/mL range for all patients. Sites targeting broader AUC ranges for all patients had higher rates of target attainment. Reviewing differences among sites allowed the ASPWG to identify best practices to optimize future care.
CONCLUSIONS
VHA ASPs must meet the standards outlined in VHA Directive 1031, including the new requirement for each VISN to develop an ASP collaborative. The VISN 8 ASPWG demonstrates how ASP champions can collaborate to solve common issues, complete tasks, explore new infectious diseases concepts, and impact large veteran populations. Furthermore, ASP collaboratives can harness their collective size to complete robust quality assurance evaluations that might otherwise be underpowered if completed at a single center. A limitation of the collaborative model is that a site with a robust ASP may already have specific practices in place. Expanding the ASP collaborative model further highlights the VHA role as a nationwide leader in ASP best practices.
- Centers for Disease Control and Prevention. Antibiotic resistance threats in the United States, 2019. Updated December 2019. Accessed September 10, 2024. https:// www.cdc.gov/antimicrobial-resistance/media/pdfs/2019-ar-threats-report-508.pdf
- US Department of Veterans Affairs. Antimicrobial stewardship programs. Updated September 22, 2023. Accessed September 13, 2024. https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=11458
- US Department of Veterans Affairs, Veteran Health Administration. Veterans Integrated Service Networks (VISNs). Accessed September 13, 2024. https://www.va.gov/HEALTH/visns.asp
- US Department of Veterans Affairs. Veterans Health Administration, Veterans Integrated Service Networks, VISN 08. Updated September 10, 2024. Accessed September 13, 2024. https://department.va.gov/integrated-service-networks/visn-08/
- Andreev I. What is collaborative learning? Theory, examples of activities. Valamis. Updated July 10, 2024. Accessed September 10, 2024. https://www.valamis.com/hub/collaborative-learning
- Rybak MJ, Le J, Lodise TP, et al. Therapeutic monitoring of vancomycin for serious methicillin-resistant staphylococcus aureus infections: a revised consensus guideline and review by the American Society of Health-System Pharmacists, the Infectious Diseases Society of America, the Pediatric Infectious Diseases Society, and the Society of Infectious Diseases Pharmacists. Am J Health Syst Pharm. 2020;77(11):835-864. doi:10.1093/ajhp/zxaa036
- Finch NA, Zasowski EJ, Murray KP, et al. A quasi-experiment to study the impact of vancomycin area under the concentration-time curve-guided dosing on vancomycinassociated nephrotoxicity. Antimicrob Agents Chemother. 2017;61(12):e01293-17. doi:10.1128/AAC.01293-17
- Zasowski EJ, Murray KP, Trinh TD, et al. Identification of vancomycin exposure-toxicity thresholds in hospitalized patients receiving intravenous vancomycin. Antimicrob Agents Chemother. 2017;62(1):e01684-17. doi:10.1128/AAC.01684-17
- Matzke GR, Kovarik JM, Rybak MJ, Boike SC. Evaluation of the vancomycin-clearance: creatinine-clearance relationship for predicting vancomycin dosage. Clin Pharm. 1985;4(3):311-315.
- Crass RL, Dunn R, Hong J, Krop LC, Pai MP. Dosing vancomycin in the super obese: less is more. J Antimicrob Chemother. 2018;73(11):3081-3086. doi:10.1093/jac/dky310
- Lodise TP, Rosenkranz SL, Finnemeyer M, et al. The emperor’s new clothes: prospective observational evaluation of the association between initial vancomycIn exposure and failure rates among adult hospitalized patients with methicillin-resistant staphylococcus aureus bloodstream infections (PROVIDE). Clin Infect Dis. 2020;70(8):1536-1545. doi:10.1093/cid/ciz460
- Centers for Disease Control and Prevention. Antibiotic resistance threats in the United States, 2019. Updated December 2019. Accessed September 10, 2024. https:// www.cdc.gov/antimicrobial-resistance/media/pdfs/2019-ar-threats-report-508.pdf
- US Department of Veterans Affairs. Antimicrobial stewardship programs. Updated September 22, 2023. Accessed September 13, 2024. https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=11458
- US Department of Veterans Affairs, Veteran Health Administration. Veterans Integrated Service Networks (VISNs). Accessed September 13, 2024. https://www.va.gov/HEALTH/visns.asp
- US Department of Veterans Affairs. Veterans Health Administration, Veterans Integrated Service Networks, VISN 08. Updated September 10, 2024. Accessed September 13, 2024. https://department.va.gov/integrated-service-networks/visn-08/
- Andreev I. What is collaborative learning? Theory, examples of activities. Valamis. Updated July 10, 2024. Accessed September 10, 2024. https://www.valamis.com/hub/collaborative-learning
- Rybak MJ, Le J, Lodise TP, et al. Therapeutic monitoring of vancomycin for serious methicillin-resistant staphylococcus aureus infections: a revised consensus guideline and review by the American Society of Health-System Pharmacists, the Infectious Diseases Society of America, the Pediatric Infectious Diseases Society, and the Society of Infectious Diseases Pharmacists. Am J Health Syst Pharm. 2020;77(11):835-864. doi:10.1093/ajhp/zxaa036
- Finch NA, Zasowski EJ, Murray KP, et al. A quasi-experiment to study the impact of vancomycin area under the concentration-time curve-guided dosing on vancomycinassociated nephrotoxicity. Antimicrob Agents Chemother. 2017;61(12):e01293-17. doi:10.1128/AAC.01293-17
- Zasowski EJ, Murray KP, Trinh TD, et al. Identification of vancomycin exposure-toxicity thresholds in hospitalized patients receiving intravenous vancomycin. Antimicrob Agents Chemother. 2017;62(1):e01684-17. doi:10.1128/AAC.01684-17
- Matzke GR, Kovarik JM, Rybak MJ, Boike SC. Evaluation of the vancomycin-clearance: creatinine-clearance relationship for predicting vancomycin dosage. Clin Pharm. 1985;4(3):311-315.
- Crass RL, Dunn R, Hong J, Krop LC, Pai MP. Dosing vancomycin in the super obese: less is more. J Antimicrob Chemother. 2018;73(11):3081-3086. doi:10.1093/jac/dky310
- Lodise TP, Rosenkranz SL, Finnemeyer M, et al. The emperor’s new clothes: prospective observational evaluation of the association between initial vancomycIn exposure and failure rates among adult hospitalized patients with methicillin-resistant staphylococcus aureus bloodstream infections (PROVIDE). Clin Infect Dis. 2020;70(8):1536-1545. doi:10.1093/cid/ciz460