Oncology

PHOENIX – Medications used in oncology clinical trials pose unique challenges in areas such as labeling, packaging, and administration, a US Department of Veterans Affairs (VA) pharmacist cautioned colleagues, and placebos have special needs too.

Even basic safety protections can be lacking when a drug is investigational, said Emily Hennes, PharmD, BCOP, clinical pharmacy specialist for research at William S. Middleton Memorial Veterans Hospital in Shorewood Hills, Wisconsin, in a presentation at the annual meeting of the Association of VA Hematology/Oncology.

“All of the safety features that we have come to know and love in dispensing commercial drugs are absent. There’s no Tall Man lettering, there's no color differentiation, and there's no barcoding, because these are not registered drugs," she said.

A 2017 report found that 81% of pharmacists surveyed indicated some level of concern regarding the safety risk in using  investigational drugs. At the same time, Hennes noted, the Joint Commission has mandated that pharmacists must control the storage, dispensing, labeling, and distribution of investigational medications.

Here are things to know about the use of investigational cancer drugs:

Drug Interactions Are Common

Hennes highlighted a 2023 study of medication reconciliation of 501 patients in 79 clinical trials that found alarming levels of drug interactions: 

• 360 clinically relevant drug-drug interactions were identified among 189 patients, including 158 therapies that were prohibited by protocols. Of these, 57.7% involved cytochrome P450 enzymes, which are involved in metabolism. 

• Reconciliation revealed that 35.2% of medications were not otherwise known or documented.

• A median of 2 previously unknown therapies per patient was discovered in 74% of patients.

• Alternative medicine products such as supplements and over-the-counter drugs were implicated in 60% of identified drug interactions.

• Only 41% of oncologists discussed alternative medicine use with patients, which Hennes attributed to “lack of familiarity with many alternative medicine products or insufficient training.”

To make things more complicated, “We sometimes don’t know the full pharmacokinetic and pharmacodynamic profile of an investigational agent,” she said. 

Naming and Labeling May Not Be Standard

Investigational products may not have genetic names and instead have an alphanumeric identifier such as INV54826 that can be quite similar to other products, she said. Investigational drugs may even go through name changes, forcing pharmacists to be alerted to protect patients. 

In addition, labeling may not be standardized. Drugs may arrive unlabeled, with the wrong volume and size, and lack of barcoding. In some cases, pharmacists choose to put new, patient-friendly labels on these products, Hennes said. 

Information Distribution is Key

“Something that comes up in our practice quite a bit is that there’s no standard drug reference regarding investigational drugs,” Hennes said. “Finding ways to get key information to staff at the point of care is really critical to make sure we’re able to safely treat our patients.”

Precautions May Be Needed to Maintain Blinding Protocols 

Hennes explained that pharmacists must use opaque brown bag covers to maintain blinding when parenteral products have distinctive colors. Lines may have to be covered too, which can create challenges during administration. 

“Pumps aren’t meant to run lines that are covered,” she said, which can lead to jams. “If you don’t do education with your point of care staff, it can cause a lot of confusion.” 

It’s also important for blinding purposes to keep an eye on how long it takes to prepare a treatment, she said. A study’s integrity, for example, could be violated if a complex investigational product takes an hour to equilibrate to room temperature and 20-30 minutes to prepare, while a placebo only requires “drawing a few mils of saline out of a bag and labeling it.”

Education for Patients Can Be Useful 

Hennes urged colleagues to remind patients to save investigational medication at the end of each cycle and return it to the clinic site for accountability.

She also suggested creating treatment calendars/reminders for patients and discussing adherence strategies with them. 

Hennes reported no disclosures. 

PHOENIX – Medications used in oncology clinical trials pose unique challenges in areas such as labeling, packaging, and administration, a US Department of Veterans Affairs (VA) pharmacist cautioned colleagues, and placebos have special needs too.

Even basic safety protections can be lacking when a drug is investigational, said Emily Hennes, PharmD, BCOP, clinical pharmacy specialist for research at William S. Middleton Memorial Veterans Hospital in Shorewood Hills, Wisconsin, in a presentation at the annual meeting of the Association of VA Hematology/Oncology.

“All of the safety features that we have come to know and love in dispensing commercial drugs are absent. There’s no Tall Man lettering, there's no color differentiation, and there's no barcoding, because these are not registered drugs," she said.

A 2017 report found that 81% of pharmacists surveyed indicated some level of concern regarding the safety risk in using  investigational drugs. At the same time, Hennes noted, the Joint Commission has mandated that pharmacists must control the storage, dispensing, labeling, and distribution of investigational medications.

Here are things to know about the use of investigational cancer drugs:

Drug Interactions Are Common

Hennes highlighted a 2023 study of medication reconciliation of 501 patients in 79 clinical trials that found alarming levels of drug interactions: 

• 360 clinically relevant drug-drug interactions were identified among 189 patients, including 158 therapies that were prohibited by protocols. Of these, 57.7% involved cytochrome P450 enzymes, which are involved in metabolism. 

• Reconciliation revealed that 35.2% of medications were not otherwise known or documented.

• A median of 2 previously unknown therapies per patient was discovered in 74% of patients.

• Alternative medicine products such as supplements and over-the-counter drugs were implicated in 60% of identified drug interactions.

• Only 41% of oncologists discussed alternative medicine use with patients, which Hennes attributed to “lack of familiarity with many alternative medicine products or insufficient training.”

To make things more complicated, “We sometimes don’t know the full pharmacokinetic and pharmacodynamic profile of an investigational agent,” she said. 

Naming and Labeling May Not Be Standard

Investigational products may not have genetic names and instead have an alphanumeric identifier such as INV54826 that can be quite similar to other products, she said. Investigational drugs may even go through name changes, forcing pharmacists to be alerted to protect patients. 

In addition, labeling may not be standardized. Drugs may arrive unlabeled, with the wrong volume and size, and lack of barcoding. In some cases, pharmacists choose to put new, patient-friendly labels on these products, Hennes said. 

Information Distribution is Key

“Something that comes up in our practice quite a bit is that there’s no standard drug reference regarding investigational drugs,” Hennes said. “Finding ways to get key information to staff at the point of care is really critical to make sure we’re able to safely treat our patients.”

Precautions May Be Needed to Maintain Blinding Protocols 

Hennes explained that pharmacists must use opaque brown bag covers to maintain blinding when parenteral products have distinctive colors. Lines may have to be covered too, which can create challenges during administration. 

“Pumps aren’t meant to run lines that are covered,” she said, which can lead to jams. “If you don’t do education with your point of care staff, it can cause a lot of confusion.” 

It’s also important for blinding purposes to keep an eye on how long it takes to prepare a treatment, she said. A study’s integrity, for example, could be violated if a complex investigational product takes an hour to equilibrate to room temperature and 20-30 minutes to prepare, while a placebo only requires “drawing a few mils of saline out of a bag and labeling it.”

Education for Patients Can Be Useful 

Hennes urged colleagues to remind patients to save investigational medication at the end of each cycle and return it to the clinic site for accountability.

She also suggested creating treatment calendars/reminders for patients and discussing adherence strategies with them. 

Hennes reported no disclosures. 

PHOENIX – Medications used in oncology clinical trials pose unique challenges in areas such as labeling, packaging, and administration, a US Department of Veterans Affairs (VA) pharmacist cautioned colleagues, and placebos have special needs too.

Even basic safety protections can be lacking when a drug is investigational, said Emily Hennes, PharmD, BCOP, clinical pharmacy specialist for research at William S. Middleton Memorial Veterans Hospital in Shorewood Hills, Wisconsin, in a presentation at the annual meeting of the Association of VA Hematology/Oncology.

“All of the safety features that we have come to know and love in dispensing commercial drugs are absent. There’s no Tall Man lettering, there's no color differentiation, and there's no barcoding, because these are not registered drugs," she said.

A 2017 report found that 81% of pharmacists surveyed indicated some level of concern regarding the safety risk in using  investigational drugs. At the same time, Hennes noted, the Joint Commission has mandated that pharmacists must control the storage, dispensing, labeling, and distribution of investigational medications.

Here are things to know about the use of investigational cancer drugs:

Drug Interactions Are Common

Hennes highlighted a 2023 study of medication reconciliation of 501 patients in 79 clinical trials that found alarming levels of drug interactions: 

• 360 clinically relevant drug-drug interactions were identified among 189 patients, including 158 therapies that were prohibited by protocols. Of these, 57.7% involved cytochrome P450 enzymes, which are involved in metabolism. 

• Reconciliation revealed that 35.2% of medications were not otherwise known or documented.

• A median of 2 previously unknown therapies per patient was discovered in 74% of patients.

• Alternative medicine products such as supplements and over-the-counter drugs were implicated in 60% of identified drug interactions.

• Only 41% of oncologists discussed alternative medicine use with patients, which Hennes attributed to “lack of familiarity with many alternative medicine products or insufficient training.”

To make things more complicated, “We sometimes don’t know the full pharmacokinetic and pharmacodynamic profile of an investigational agent,” she said. 

Naming and Labeling May Not Be Standard

Investigational products may not have genetic names and instead have an alphanumeric identifier such as INV54826 that can be quite similar to other products, she said. Investigational drugs may even go through name changes, forcing pharmacists to be alerted to protect patients. 

In addition, labeling may not be standardized. Drugs may arrive unlabeled, with the wrong volume and size, and lack of barcoding. In some cases, pharmacists choose to put new, patient-friendly labels on these products, Hennes said. 

Information Distribution is Key

“Something that comes up in our practice quite a bit is that there’s no standard drug reference regarding investigational drugs,” Hennes said. “Finding ways to get key information to staff at the point of care is really critical to make sure we’re able to safely treat our patients.”

Precautions May Be Needed to Maintain Blinding Protocols 

Hennes explained that pharmacists must use opaque brown bag covers to maintain blinding when parenteral products have distinctive colors. Lines may have to be covered too, which can create challenges during administration. 

“Pumps aren’t meant to run lines that are covered,” she said, which can lead to jams. “If you don’t do education with your point of care staff, it can cause a lot of confusion.” 

It’s also important for blinding purposes to keep an eye on how long it takes to prepare a treatment, she said. A study’s integrity, for example, could be violated if a complex investigational product takes an hour to equilibrate to room temperature and 20-30 minutes to prepare, while a placebo only requires “drawing a few mils of saline out of a bag and labeling it.”

Education for Patients Can Be Useful 

Hennes urged colleagues to remind patients to save investigational medication at the end of each cycle and return it to the clinic site for accountability.

She also suggested creating treatment calendars/reminders for patients and discussing adherence strategies with them. 

Hennes reported no disclosures. 

TOPLINE:

High-risk medications defined by the National Comprehensive Cancer Network (NCCN) and captured by the Geriatric Oncology Potentially Inappropriate Medication (GO-PIM) scale were prevalent in > one-third of veterans with solid and hematologic malignancies. Each additional GO-PIM was independently associated with higher risks for frailty at diagnosis, unplanned hospitalizations during follow-up, and death.

METHODOLOGY:

• Patients with cancer often use multiple chronic medications, raising risks for adverse events. Although several tools that identify PIMs have been developed that correlate with adverse cancer outcomes, their use is limited in busy oncology clinics. To improve implementation, researchers developed the GO-PIM scale using the NCCN’s list of high-risk medications.
• Researchers conducted a retrospective cohort study using data from the national Veterans Affairs Cancer Registry and electronic health records, which included 388,113 veterans newly diagnosed with solid or hematologic malignancies (median age, 69.3 years; 97.9% men; 76.1% non-Hispanic White and 17.3% Black individuals) between 2000 and 2022.
• They identified GO-PIMs using outpatient pharmacy records in the 90 days preceding cancer diagnosis. Each prescription for a specific GO-PIM was counted as one, including both individual drugs and drug classes listed in the GO-PIM scale.
• Study outcomes were frailty, hospitalizations, and overall survival. Baseline frailty at diagnosis was measured using the Veterans Affairs Frailty Index. The score ranged from 0 to 1, and higher scores indicated greater frailty. Patients were classified as nonfrail (score, ≤ 0.2), mildly frail (score, > 0.2 to 0.3), or moderate-to-severely frail (score, > 0.3).
• Lung (23.7%), prostate (21.5%), and gastrointestinal (20.5%) cancers were the most common, and the most frequent stages were IV (25.4%) and II (24.4%).

TAKEAWAY:

• Overall, 38.0% of veterans were prescribed ≥ 1 GO-PIMs at the time of cancer diagnosis, and the proportion increased to 56.1% among those with moderate-to-severe frailty.
• The most commonly prescribed classes of PIMs were selective serotonin reuptake inhibitors (SSRIs; 12.0%), opioids (10.4%), benzodiazepines (9.2%), and corticosteroids (9.2%). Among individual drugs, sertraline was the most common SSRI (4.3%), tramadol the most common opioid (5.3%), lorazepam the most common benzodiazepine (2.5%), and prednisone the most common corticosteroid (4.9%). Trends over time showed a steady increase in opioid prescriptions, peaking in 2014, followed by a subsequent decline, while prescriptions of benzodiazepines declined during the later years.
• After adjusting for age, cancer type and stage, and other covariates, each additional GO-PIM was associated with a 66% higher odds of mild or moderate-to-severe frailty at diagnosis (adjusted odds ratio, 1.66).
• After adjusting for frailty and covariates, each additional GO-PIM at diagnosis was associated with increased risks for unplanned hospitalizations and death (adjusted hazard ratios, 1.08 and 1.07, respectively). These associations remained stable in sensitivity analyses that restricted GO-PIMs to scheduled medications only, focused on patients who had initiated cancer treatment, and included only those aged ≥ 65 years.

IN PRACTICE:

“Whether prescribed for supportive oncology care or for coexisting medical conditions, high-risk medications identified as PIMs should be reviewed and optimized in patients with cancer,” the authors of the study wrote.

“GO-PIMs offers a streamlined, oncology-specific approach to identifying high-risk prescribing, and complements existing efforts to improve supportive care, especially for older, frail patients,” remarked Mostafa R. Mohamed, MBBCH, PhD, MSc, and Erika E. Ramsdale, MD, University of Rochester Medical Center, Rochester, New York in an invited commentary. “The next step lies in integrating tools such as GO-PIMs into everyday practice not only to flag high risk medications but also to support actionable changes in treatment planning and patient management, such as deprescribing,” they concluded.

SOURCE:

This study, led by Jennifer La, PhD, Harvard Medical School, Boston, was published online in Journal of the National Comprehensive Cancer Network.

LIMITATIONS:

Prescription chronicity before or after follow-up was not measured and actual medication adherence could not be confirmed. Residual confounding by comorbidity could have existed, and the cross-sectional nature of linking GO-PIMs with frailty might have limited causal inference. Additionally, prescriptions were measured within Veterans Affairs pharmacy data, potentially underestimating GO-PIM prevalence, and the predominantly male population limited generalizability to gynecologic cancers.

DISCLOSURES:

This study was supported by grants and rewards from the Veterans Affairs Office of Research and Development, Cooperative Studies Program, National Institutes of Health, and American Heart Association. Some authors declared serving as consultants or receiving grants and having other ties with various sources. Additional disclosures are noted in the original article.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

A version of this article first appeared on Medscape.com.

TOPLINE:

High-risk medications defined by the National Comprehensive Cancer Network (NCCN) and captured by the Geriatric Oncology Potentially Inappropriate Medication (GO-PIM) scale were prevalent in > one-third of veterans with solid and hematologic malignancies. Each additional GO-PIM was independently associated with higher risks for frailty at diagnosis, unplanned hospitalizations during follow-up, and death.

METHODOLOGY:

• Patients with cancer often use multiple chronic medications, raising risks for adverse events. Although several tools that identify PIMs have been developed that correlate with adverse cancer outcomes, their use is limited in busy oncology clinics. To improve implementation, researchers developed the GO-PIM scale using the NCCN’s list of high-risk medications.
• Researchers conducted a retrospective cohort study using data from the national Veterans Affairs Cancer Registry and electronic health records, which included 388,113 veterans newly diagnosed with solid or hematologic malignancies (median age, 69.3 years; 97.9% men; 76.1% non-Hispanic White and 17.3% Black individuals) between 2000 and 2022.
• They identified GO-PIMs using outpatient pharmacy records in the 90 days preceding cancer diagnosis. Each prescription for a specific GO-PIM was counted as one, including both individual drugs and drug classes listed in the GO-PIM scale.
• Study outcomes were frailty, hospitalizations, and overall survival. Baseline frailty at diagnosis was measured using the Veterans Affairs Frailty Index. The score ranged from 0 to 1, and higher scores indicated greater frailty. Patients were classified as nonfrail (score, ≤ 0.2), mildly frail (score, > 0.2 to 0.3), or moderate-to-severely frail (score, > 0.3).
• Lung (23.7%), prostate (21.5%), and gastrointestinal (20.5%) cancers were the most common, and the most frequent stages were IV (25.4%) and II (24.4%).

TAKEAWAY:

• Overall, 38.0% of veterans were prescribed ≥ 1 GO-PIMs at the time of cancer diagnosis, and the proportion increased to 56.1% among those with moderate-to-severe frailty.
• The most commonly prescribed classes of PIMs were selective serotonin reuptake inhibitors (SSRIs; 12.0%), opioids (10.4%), benzodiazepines (9.2%), and corticosteroids (9.2%). Among individual drugs, sertraline was the most common SSRI (4.3%), tramadol the most common opioid (5.3%), lorazepam the most common benzodiazepine (2.5%), and prednisone the most common corticosteroid (4.9%). Trends over time showed a steady increase in opioid prescriptions, peaking in 2014, followed by a subsequent decline, while prescriptions of benzodiazepines declined during the later years.
• After adjusting for age, cancer type and stage, and other covariates, each additional GO-PIM was associated with a 66% higher odds of mild or moderate-to-severe frailty at diagnosis (adjusted odds ratio, 1.66).
• After adjusting for frailty and covariates, each additional GO-PIM at diagnosis was associated with increased risks for unplanned hospitalizations and death (adjusted hazard ratios, 1.08 and 1.07, respectively). These associations remained stable in sensitivity analyses that restricted GO-PIMs to scheduled medications only, focused on patients who had initiated cancer treatment, and included only those aged ≥ 65 years.

IN PRACTICE:

“Whether prescribed for supportive oncology care or for coexisting medical conditions, high-risk medications identified as PIMs should be reviewed and optimized in patients with cancer,” the authors of the study wrote.

“GO-PIMs offers a streamlined, oncology-specific approach to identifying high-risk prescribing, and complements existing efforts to improve supportive care, especially for older, frail patients,” remarked Mostafa R. Mohamed, MBBCH, PhD, MSc, and Erika E. Ramsdale, MD, University of Rochester Medical Center, Rochester, New York in an invited commentary. “The next step lies in integrating tools such as GO-PIMs into everyday practice not only to flag high risk medications but also to support actionable changes in treatment planning and patient management, such as deprescribing,” they concluded.

SOURCE:

This study, led by Jennifer La, PhD, Harvard Medical School, Boston, was published online in Journal of the National Comprehensive Cancer Network.

LIMITATIONS:

Prescription chronicity before or after follow-up was not measured and actual medication adherence could not be confirmed. Residual confounding by comorbidity could have existed, and the cross-sectional nature of linking GO-PIMs with frailty might have limited causal inference. Additionally, prescriptions were measured within Veterans Affairs pharmacy data, potentially underestimating GO-PIM prevalence, and the predominantly male population limited generalizability to gynecologic cancers.

DISCLOSURES:

This study was supported by grants and rewards from the Veterans Affairs Office of Research and Development, Cooperative Studies Program, National Institutes of Health, and American Heart Association. Some authors declared serving as consultants or receiving grants and having other ties with various sources. Additional disclosures are noted in the original article.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

A version of this article first appeared on Medscape.com.

TOPLINE:

High-risk medications defined by the National Comprehensive Cancer Network (NCCN) and captured by the Geriatric Oncology Potentially Inappropriate Medication (GO-PIM) scale were prevalent in > one-third of veterans with solid and hematologic malignancies. Each additional GO-PIM was independently associated with higher risks for frailty at diagnosis, unplanned hospitalizations during follow-up, and death.

METHODOLOGY:

• Patients with cancer often use multiple chronic medications, raising risks for adverse events. Although several tools that identify PIMs have been developed that correlate with adverse cancer outcomes, their use is limited in busy oncology clinics. To improve implementation, researchers developed the GO-PIM scale using the NCCN’s list of high-risk medications.
• Researchers conducted a retrospective cohort study using data from the national Veterans Affairs Cancer Registry and electronic health records, which included 388,113 veterans newly diagnosed with solid or hematologic malignancies (median age, 69.3 years; 97.9% men; 76.1% non-Hispanic White and 17.3% Black individuals) between 2000 and 2022.
• They identified GO-PIMs using outpatient pharmacy records in the 90 days preceding cancer diagnosis. Each prescription for a specific GO-PIM was counted as one, including both individual drugs and drug classes listed in the GO-PIM scale.
• Study outcomes were frailty, hospitalizations, and overall survival. Baseline frailty at diagnosis was measured using the Veterans Affairs Frailty Index. The score ranged from 0 to 1, and higher scores indicated greater frailty. Patients were classified as nonfrail (score, ≤ 0.2), mildly frail (score, > 0.2 to 0.3), or moderate-to-severely frail (score, > 0.3).
• Lung (23.7%), prostate (21.5%), and gastrointestinal (20.5%) cancers were the most common, and the most frequent stages were IV (25.4%) and II (24.4%).

TAKEAWAY:

• Overall, 38.0% of veterans were prescribed ≥ 1 GO-PIMs at the time of cancer diagnosis, and the proportion increased to 56.1% among those with moderate-to-severe frailty.
• The most commonly prescribed classes of PIMs were selective serotonin reuptake inhibitors (SSRIs; 12.0%), opioids (10.4%), benzodiazepines (9.2%), and corticosteroids (9.2%). Among individual drugs, sertraline was the most common SSRI (4.3%), tramadol the most common opioid (5.3%), lorazepam the most common benzodiazepine (2.5%), and prednisone the most common corticosteroid (4.9%). Trends over time showed a steady increase in opioid prescriptions, peaking in 2014, followed by a subsequent decline, while prescriptions of benzodiazepines declined during the later years.
• After adjusting for age, cancer type and stage, and other covariates, each additional GO-PIM was associated with a 66% higher odds of mild or moderate-to-severe frailty at diagnosis (adjusted odds ratio, 1.66).
• After adjusting for frailty and covariates, each additional GO-PIM at diagnosis was associated with increased risks for unplanned hospitalizations and death (adjusted hazard ratios, 1.08 and 1.07, respectively). These associations remained stable in sensitivity analyses that restricted GO-PIMs to scheduled medications only, focused on patients who had initiated cancer treatment, and included only those aged ≥ 65 years.

IN PRACTICE:

“Whether prescribed for supportive oncology care or for coexisting medical conditions, high-risk medications identified as PIMs should be reviewed and optimized in patients with cancer,” the authors of the study wrote.

“GO-PIMs offers a streamlined, oncology-specific approach to identifying high-risk prescribing, and complements existing efforts to improve supportive care, especially for older, frail patients,” remarked Mostafa R. Mohamed, MBBCH, PhD, MSc, and Erika E. Ramsdale, MD, University of Rochester Medical Center, Rochester, New York in an invited commentary. “The next step lies in integrating tools such as GO-PIMs into everyday practice not only to flag high risk medications but also to support actionable changes in treatment planning and patient management, such as deprescribing,” they concluded.

SOURCE:

This study, led by Jennifer La, PhD, Harvard Medical School, Boston, was published online in Journal of the National Comprehensive Cancer Network.

LIMITATIONS:

Prescription chronicity before or after follow-up was not measured and actual medication adherence could not be confirmed. Residual confounding by comorbidity could have existed, and the cross-sectional nature of linking GO-PIMs with frailty might have limited causal inference. Additionally, prescriptions were measured within Veterans Affairs pharmacy data, potentially underestimating GO-PIM prevalence, and the predominantly male population limited generalizability to gynecologic cancers.

DISCLOSURES:

This study was supported by grants and rewards from the Veterans Affairs Office of Research and Development, Cooperative Studies Program, National Institutes of Health, and American Heart Association. Some authors declared serving as consultants or receiving grants and having other ties with various sources. Additional disclosures are noted in the original article.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

A version of this article first appeared on Medscape.com.

TOPLINE:

About 1 in 10 veterans with early-stage cancer developed new persistent opioid use after curative‐intent surgery, though < 1% were diagnosed with opioid use disorder.

METHODOLOGY:

Although effective pain control during cancer treatment is vital, prescribing opioids in this context may contribute to unsafe, long-term use and related adverse outcomes. Veterans, who have higher-than-average rates of mental health and substance use disorders, may be at particular risk for adverse events from opioid use related to cancer treatment.

Researchers conducted a national retrospective cohort study of 9213 US veterans (98% men) with stage 0-III cancer who were opioid-naive and underwent curative-intent surgery at Veterans Affairs medical centers between 2015 and 2016. Prostate (n = 2594; 28%), colorectal (n = 2393; 26%), bladder (n = 2302; 25%), and lung (n = 1252; 14%) cancers were the most common.

Primary outcomes were the number of days of co-prescription of benzodiazepines and opioids (an indicator of unsafe opioid prescribing) and new persistent opioid use, defined as receiving ≥ 1 opioid prescription at 90-180 days postsurgery. Opioid‐related adverse effects, including opioid use disorder and opioid overdose, were also reported.

Overall, 6970 (76%) of the participants were prescribed opioids at some point during the baseline treatment period (30 days before through 14 days after surgery). The mean morphine milligram equivalent (MME) was 172.5.

 

TAKEAWAY:

Overall, 4% of patients received co-prescriptions of benzodiazepines and opioids. The mean number of days of coprescription rose in tandem with opioid doses during the treatment period: from 0.48 days in the lowest MME quartile to 2.1 days in the highest quartile (P < .0001).

Over 1 in 10 patients (10.6%) developed new persistent opioid use. Those in the highest MME quartile had a 1.6-fold greater risk of developing new persistent opioid use than those with no opioid exposure during the treatment period (hazard ratio [HR], 1.6; P < .001). The percentage of patients with opioid prescriptions did decline over the 13-month follow-up, but among those who continued on opioids, the daily MME remained stable (median, 20 for month 1 and 30 for month 12).

Treatment with adjuvant chemotherapy increased the risk for new persistent opioid use (HR, 1.5; 95% CI, 1.2-1.8; P < .001). Additional risk factors included having bladder, colorectal, lung, or other types of cancer (vs prostate cancer); stage I-III disease (vs stage 0); age 45-64 years (vs older); lower socioeconomic status; preoperative use of nonopioid pain medication; and a baseline history of anxiety, depression, or posttraumatic stress disorder.

Over 13 months, 72 patients (0.78%) developed opioid use disorder, 3 (0.03%) experienced nonoverdose adverse events, and no opioid overdose occurred.

 

IN PRACTICE:

“Although a cancer diagnosis, treatment, and associated pain syndromes will require specific pain management strategies,” the authors wrote, “efforts should be taken to mitigate long‐term opioid use and its potential adverse effects in this population. They added that “both system‐level changes that involve preoperative evaluation planning as well as increased knowledge, awareness, and education among providers and patients about the risk of long‐term opioid use can guide strategies for effective and safe pain management.”

SOURCE:

The study, led by Marilyn M. Schapira, MD, MPH, Center for Healthcare Evaluation, Research, and Promotion, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, was published online in Cancer.

LIMITATIONS:

Opioid prescriptions outside the Veterans Affairs system were not captured. The study was based on filled opioid prescriptions, and actual patient consumption was unknown. Outpatient methadone prescriptions were not included. The study also excluded patients with breast cancer, limiting generalizability.

DISCLOSURES:

The study was funded by grant from the Department of Veterans Affairs. One author reported consulting for Moderna and TriNetX. Another author reported consulting for Genetic Chemistry, Thyme Care, Biofourmis, Onc.Al, Credit Suisse, Main Street Health, ConcertAI, Medscape, and G1 Therapeutics. The other authors declared having no conflicts of interest.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.

TOPLINE:

About 1 in 10 veterans with early-stage cancer developed new persistent opioid use after curative‐intent surgery, though < 1% were diagnosed with opioid use disorder.

METHODOLOGY:

Although effective pain control during cancer treatment is vital, prescribing opioids in this context may contribute to unsafe, long-term use and related adverse outcomes. Veterans, who have higher-than-average rates of mental health and substance use disorders, may be at particular risk for adverse events from opioid use related to cancer treatment.

Researchers conducted a national retrospective cohort study of 9213 US veterans (98% men) with stage 0-III cancer who were opioid-naive and underwent curative-intent surgery at Veterans Affairs medical centers between 2015 and 2016. Prostate (n = 2594; 28%), colorectal (n = 2393; 26%), bladder (n = 2302; 25%), and lung (n = 1252; 14%) cancers were the most common.

Primary outcomes were the number of days of co-prescription of benzodiazepines and opioids (an indicator of unsafe opioid prescribing) and new persistent opioid use, defined as receiving ≥ 1 opioid prescription at 90-180 days postsurgery. Opioid‐related adverse effects, including opioid use disorder and opioid overdose, were also reported.

Overall, 6970 (76%) of the participants were prescribed opioids at some point during the baseline treatment period (30 days before through 14 days after surgery). The mean morphine milligram equivalent (MME) was 172.5.

 

TAKEAWAY:

Overall, 4% of patients received co-prescriptions of benzodiazepines and opioids. The mean number of days of coprescription rose in tandem with opioid doses during the treatment period: from 0.48 days in the lowest MME quartile to 2.1 days in the highest quartile (P < .0001).

Over 1 in 10 patients (10.6%) developed new persistent opioid use. Those in the highest MME quartile had a 1.6-fold greater risk of developing new persistent opioid use than those with no opioid exposure during the treatment period (hazard ratio [HR], 1.6; P < .001). The percentage of patients with opioid prescriptions did decline over the 13-month follow-up, but among those who continued on opioids, the daily MME remained stable (median, 20 for month 1 and 30 for month 12).

Treatment with adjuvant chemotherapy increased the risk for new persistent opioid use (HR, 1.5; 95% CI, 1.2-1.8; P < .001). Additional risk factors included having bladder, colorectal, lung, or other types of cancer (vs prostate cancer); stage I-III disease (vs stage 0); age 45-64 years (vs older); lower socioeconomic status; preoperative use of nonopioid pain medication; and a baseline history of anxiety, depression, or posttraumatic stress disorder.

Over 13 months, 72 patients (0.78%) developed opioid use disorder, 3 (0.03%) experienced nonoverdose adverse events, and no opioid overdose occurred.

 

IN PRACTICE:

“Although a cancer diagnosis, treatment, and associated pain syndromes will require specific pain management strategies,” the authors wrote, “efforts should be taken to mitigate long‐term opioid use and its potential adverse effects in this population. They added that “both system‐level changes that involve preoperative evaluation planning as well as increased knowledge, awareness, and education among providers and patients about the risk of long‐term opioid use can guide strategies for effective and safe pain management.”

SOURCE:

The study, led by Marilyn M. Schapira, MD, MPH, Center for Healthcare Evaluation, Research, and Promotion, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, was published online in Cancer.

LIMITATIONS:

Opioid prescriptions outside the Veterans Affairs system were not captured. The study was based on filled opioid prescriptions, and actual patient consumption was unknown. Outpatient methadone prescriptions were not included. The study also excluded patients with breast cancer, limiting generalizability.

DISCLOSURES:

The study was funded by grant from the Department of Veterans Affairs. One author reported consulting for Moderna and TriNetX. Another author reported consulting for Genetic Chemistry, Thyme Care, Biofourmis, Onc.Al, Credit Suisse, Main Street Health, ConcertAI, Medscape, and G1 Therapeutics. The other authors declared having no conflicts of interest.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.

TOPLINE:

About 1 in 10 veterans with early-stage cancer developed new persistent opioid use after curative‐intent surgery, though < 1% were diagnosed with opioid use disorder.

METHODOLOGY:

Although effective pain control during cancer treatment is vital, prescribing opioids in this context may contribute to unsafe, long-term use and related adverse outcomes. Veterans, who have higher-than-average rates of mental health and substance use disorders, may be at particular risk for adverse events from opioid use related to cancer treatment.

Researchers conducted a national retrospective cohort study of 9213 US veterans (98% men) with stage 0-III cancer who were opioid-naive and underwent curative-intent surgery at Veterans Affairs medical centers between 2015 and 2016. Prostate (n = 2594; 28%), colorectal (n = 2393; 26%), bladder (n = 2302; 25%), and lung (n = 1252; 14%) cancers were the most common.

Primary outcomes were the number of days of co-prescription of benzodiazepines and opioids (an indicator of unsafe opioid prescribing) and new persistent opioid use, defined as receiving ≥ 1 opioid prescription at 90-180 days postsurgery. Opioid‐related adverse effects, including opioid use disorder and opioid overdose, were also reported.

Overall, 6970 (76%) of the participants were prescribed opioids at some point during the baseline treatment period (30 days before through 14 days after surgery). The mean morphine milligram equivalent (MME) was 172.5.

 

TAKEAWAY:

Overall, 4% of patients received co-prescriptions of benzodiazepines and opioids. The mean number of days of coprescription rose in tandem with opioid doses during the treatment period: from 0.48 days in the lowest MME quartile to 2.1 days in the highest quartile (P < .0001).

Over 1 in 10 patients (10.6%) developed new persistent opioid use. Those in the highest MME quartile had a 1.6-fold greater risk of developing new persistent opioid use than those with no opioid exposure during the treatment period (hazard ratio [HR], 1.6; P < .001). The percentage of patients with opioid prescriptions did decline over the 13-month follow-up, but among those who continued on opioids, the daily MME remained stable (median, 20 for month 1 and 30 for month 12).

Treatment with adjuvant chemotherapy increased the risk for new persistent opioid use (HR, 1.5; 95% CI, 1.2-1.8; P < .001). Additional risk factors included having bladder, colorectal, lung, or other types of cancer (vs prostate cancer); stage I-III disease (vs stage 0); age 45-64 years (vs older); lower socioeconomic status; preoperative use of nonopioid pain medication; and a baseline history of anxiety, depression, or posttraumatic stress disorder.

Over 13 months, 72 patients (0.78%) developed opioid use disorder, 3 (0.03%) experienced nonoverdose adverse events, and no opioid overdose occurred.

 

IN PRACTICE:

“Although a cancer diagnosis, treatment, and associated pain syndromes will require specific pain management strategies,” the authors wrote, “efforts should be taken to mitigate long‐term opioid use and its potential adverse effects in this population. They added that “both system‐level changes that involve preoperative evaluation planning as well as increased knowledge, awareness, and education among providers and patients about the risk of long‐term opioid use can guide strategies for effective and safe pain management.”

SOURCE:

The study, led by Marilyn M. Schapira, MD, MPH, Center for Healthcare Evaluation, Research, and Promotion, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, was published online in Cancer.

LIMITATIONS:

Opioid prescriptions outside the Veterans Affairs system were not captured. The study was based on filled opioid prescriptions, and actual patient consumption was unknown. Outpatient methadone prescriptions were not included. The study also excluded patients with breast cancer, limiting generalizability.

DISCLOSURES:

The study was funded by grant from the Department of Veterans Affairs. One author reported consulting for Moderna and TriNetX. Another author reported consulting for Genetic Chemistry, Thyme Care, Biofourmis, Onc.Al, Credit Suisse, Main Street Health, ConcertAI, Medscape, and G1 Therapeutics. The other authors declared having no conflicts of interest.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.

TOPLINE:

Compared with inactive patterns, weekend warrior (moderate-to-vigorous physical activity [MVPA] condensed into 1-2 days per week) and regular physical activity patterns were found to be equally effective at reducing the risk for lung cancer. Neither pattern showed significant associations with the overall risk for cancer or specific risks for prostate, breast, and colorectal cancers.

METHODOLOGY:

• This analysis included 80,896 participants (mean age, 55.5 years; 56% women) with valid accelerometer data collected between June 2013 and December 2015.
• Participants were classified into three groups: 32,213 active weekend warriors (≥ 150 minutes of weekly MVPA with ≥ 50% achieved in 1-2 days), 22,162 active regular participants (≥ 150 minutes of MVPA but not meeting a weekend warrior pattern), and 26,521 inactive participants (< 150 minutes of MVPA).
• Researchers tracked associations between physical activity patterns and incident cases of all types of cancer plus specific cases of prostate, breast, colorectal, and lung cancer over a median follow-up duration of 6 years.

TAKEAWAY:

• Compared with inactive patterns, active weekend warrior patterns showed a significant inverse association with the risk for lung cancer (hazard ratio [HR], 0.77; 95% CI, 0.61-0.98).
• Active regular activity patterns demonstrated similar protective effects against lung cancer as inactive patterns (HR, 0.73; 95% CI, 0.56-0.96).
• Neither of the physical activity patterns showed any significant association with the overall risk for cancer or specific risks for prostate, breast, and colorectal cancers.

IN PRACTICE:

"Physical activity condensed into one to two days per week compared with a more balanced weekly distribution was associated with similar risk reductions of incident lung cancer, while neither pattern was associated with reduced overall, prostate, breast, and colorectal cancers," the authors of the study wrote.

SOURCE:

This study was led by Rubén López-Bueno, Department of Physical Medicine and Nursing, University of Zaragoza, Zaragoza, Spain. It was published online on September 06, 2025, in Annals of Medicine.

A version of this article first appeared on Medscape.com.

TOPLINE:

Compared with inactive patterns, weekend warrior (moderate-to-vigorous physical activity [MVPA] condensed into 1-2 days per week) and regular physical activity patterns were found to be equally effective at reducing the risk for lung cancer. Neither pattern showed significant associations with the overall risk for cancer or specific risks for prostate, breast, and colorectal cancers.

METHODOLOGY:

• This analysis included 80,896 participants (mean age, 55.5 years; 56% women) with valid accelerometer data collected between June 2013 and December 2015.
• Participants were classified into three groups: 32,213 active weekend warriors (≥ 150 minutes of weekly MVPA with ≥ 50% achieved in 1-2 days), 22,162 active regular participants (≥ 150 minutes of MVPA but not meeting a weekend warrior pattern), and 26,521 inactive participants (< 150 minutes of MVPA).
• Researchers tracked associations between physical activity patterns and incident cases of all types of cancer plus specific cases of prostate, breast, colorectal, and lung cancer over a median follow-up duration of 6 years.

TAKEAWAY:

• Compared with inactive patterns, active weekend warrior patterns showed a significant inverse association with the risk for lung cancer (hazard ratio [HR], 0.77; 95% CI, 0.61-0.98).
• Active regular activity patterns demonstrated similar protective effects against lung cancer as inactive patterns (HR, 0.73; 95% CI, 0.56-0.96).
• Neither of the physical activity patterns showed any significant association with the overall risk for cancer or specific risks for prostate, breast, and colorectal cancers.

IN PRACTICE:

"Physical activity condensed into one to two days per week compared with a more balanced weekly distribution was associated with similar risk reductions of incident lung cancer, while neither pattern was associated with reduced overall, prostate, breast, and colorectal cancers," the authors of the study wrote.

SOURCE:

This study was led by Rubén López-Bueno, Department of Physical Medicine and Nursing, University of Zaragoza, Zaragoza, Spain. It was published online on September 06, 2025, in Annals of Medicine.

A version of this article first appeared on Medscape.com.

TOPLINE:

Compared with inactive patterns, weekend warrior (moderate-to-vigorous physical activity [MVPA] condensed into 1-2 days per week) and regular physical activity patterns were found to be equally effective at reducing the risk for lung cancer. Neither pattern showed significant associations with the overall risk for cancer or specific risks for prostate, breast, and colorectal cancers.

METHODOLOGY:

• This analysis included 80,896 participants (mean age, 55.5 years; 56% women) with valid accelerometer data collected between June 2013 and December 2015.
• Participants were classified into three groups: 32,213 active weekend warriors (≥ 150 minutes of weekly MVPA with ≥ 50% achieved in 1-2 days), 22,162 active regular participants (≥ 150 minutes of MVPA but not meeting a weekend warrior pattern), and 26,521 inactive participants (< 150 minutes of MVPA).
• Researchers tracked associations between physical activity patterns and incident cases of all types of cancer plus specific cases of prostate, breast, colorectal, and lung cancer over a median follow-up duration of 6 years.

TAKEAWAY:

• Compared with inactive patterns, active weekend warrior patterns showed a significant inverse association with the risk for lung cancer (hazard ratio [HR], 0.77; 95% CI, 0.61-0.98).
• Active regular activity patterns demonstrated similar protective effects against lung cancer as inactive patterns (HR, 0.73; 95% CI, 0.56-0.96).
• Neither of the physical activity patterns showed any significant association with the overall risk for cancer or specific risks for prostate, breast, and colorectal cancers.

IN PRACTICE:

"Physical activity condensed into one to two days per week compared with a more balanced weekly distribution was associated with similar risk reductions of incident lung cancer, while neither pattern was associated with reduced overall, prostate, breast, and colorectal cancers," the authors of the study wrote.

SOURCE:

This study was led by Rubén López-Bueno, Department of Physical Medicine and Nursing, University of Zaragoza, Zaragoza, Spain. It was published online on September 06, 2025, in Annals of Medicine.

A version of this article first appeared on Medscape.com.

Background

Urothelial carcinoma (UC) is among the top 10 frequently diagnosed cancers in the world. Mutations in FGFR3, ARID1A, and TP53 are well documented as being some of the most frequent mutations found in UC. Despite advances in treatment, survival outcomes remain poor, especially in advanced stages. To promote future pharmacotherapeutic development, the molecular understanding of UC needs to be continually updated using more recently available databases.

Methods

This study utilizes the AACR Project GENIE database from the American Association for Cancer Research to explore the mutational profiles of patients with UC. Gene mutation frequencies were calculated, and two Kaplan-Meier curves were drawn for each gene, showing one curve for patients with the mutation and one for those without. Log-Rank tests were calculated with subsequent FDR (Benjamini–Hochberg) correction applied to account for multiple hypothesis testing. Data was analyzed using R 4.4.2 and statistical significance was set at α = 0.05.

Results

In this study, 4525 patients had histology consistent with UC. The 5 most common mutations were TERT (n = 1714, 37.9%), TP53 (n = 1689, 37.3%), KDM6A (n = 1091, 24.1%), ARID1A (n = 872, 19.3%), and FGFR3 (n = 762, 16.8%). Mutations associated with differential survival outcomes included ERCC2 (mutated n = 387, wild type n = 3751, p < 0.0001), KDM6A (mutated n = 1091, wild type n = 3047, p < 0.0001), TERT (mutated n = 1714, wild type n = 2424), and TP53 (mutated n = 1689, wild type n = 2449, p < 0.0001).

Conclusions

Interestingly, while mutations in TP53 and ERCC2 were associated with shorter median survival, mutations in KDM6A and TERT were associated with longer median survival.

Background

Urothelial carcinoma (UC) is among the top 10 frequently diagnosed cancers in the world. Mutations in FGFR3, ARID1A, and TP53 are well documented as being some of the most frequent mutations found in UC. Despite advances in treatment, survival outcomes remain poor, especially in advanced stages. To promote future pharmacotherapeutic development, the molecular understanding of UC needs to be continually updated using more recently available databases.

Methods

This study utilizes the AACR Project GENIE database from the American Association for Cancer Research to explore the mutational profiles of patients with UC. Gene mutation frequencies were calculated, and two Kaplan-Meier curves were drawn for each gene, showing one curve for patients with the mutation and one for those without. Log-Rank tests were calculated with subsequent FDR (Benjamini–Hochberg) correction applied to account for multiple hypothesis testing. Data was analyzed using R 4.4.2 and statistical significance was set at α = 0.05.

Results

In this study, 4525 patients had histology consistent with UC. The 5 most common mutations were TERT (n = 1714, 37.9%), TP53 (n = 1689, 37.3%), KDM6A (n = 1091, 24.1%), ARID1A (n = 872, 19.3%), and FGFR3 (n = 762, 16.8%). Mutations associated with differential survival outcomes included ERCC2 (mutated n = 387, wild type n = 3751, p < 0.0001), KDM6A (mutated n = 1091, wild type n = 3047, p < 0.0001), TERT (mutated n = 1714, wild type n = 2424), and TP53 (mutated n = 1689, wild type n = 2449, p < 0.0001).

Conclusions

Interestingly, while mutations in TP53 and ERCC2 were associated with shorter median survival, mutations in KDM6A and TERT were associated with longer median survival.

Background

Urothelial carcinoma (UC) is among the top 10 frequently diagnosed cancers in the world. Mutations in FGFR3, ARID1A, and TP53 are well documented as being some of the most frequent mutations found in UC. Despite advances in treatment, survival outcomes remain poor, especially in advanced stages. To promote future pharmacotherapeutic development, the molecular understanding of UC needs to be continually updated using more recently available databases.

Methods

This study utilizes the AACR Project GENIE database from the American Association for Cancer Research to explore the mutational profiles of patients with UC. Gene mutation frequencies were calculated, and two Kaplan-Meier curves were drawn for each gene, showing one curve for patients with the mutation and one for those without. Log-Rank tests were calculated with subsequent FDR (Benjamini–Hochberg) correction applied to account for multiple hypothesis testing. Data was analyzed using R 4.4.2 and statistical significance was set at α = 0.05.

Results

In this study, 4525 patients had histology consistent with UC. The 5 most common mutations were TERT (n = 1714, 37.9%), TP53 (n = 1689, 37.3%), KDM6A (n = 1091, 24.1%), ARID1A (n = 872, 19.3%), and FGFR3 (n = 762, 16.8%). Mutations associated with differential survival outcomes included ERCC2 (mutated n = 387, wild type n = 3751, p < 0.0001), KDM6A (mutated n = 1091, wild type n = 3047, p < 0.0001), TERT (mutated n = 1714, wild type n = 2424), and TP53 (mutated n = 1689, wild type n = 2449, p < 0.0001).

Conclusions

Interestingly, while mutations in TP53 and ERCC2 were associated with shorter median survival, mutations in KDM6A and TERT were associated with longer median survival.

Background

We examined characteristics of Veterans receiving care through NTO and their CM (e.g., telephone only [T], video only [V], or both [TV]). Relevant background: In-person VA cancer care can be challenging for many Veterans due to rurality, transportation, finances, and distance to subspecialists. Such factors may impact care modality preferences.

Methods

We linked a list of all Veterans who received NTO care with Corporate Data Warehouse data to confirm an ICD-10 diagnostic code for malignancy, and to define the number of NTO interactions, latency of days between diagnosis and first NTO interaction, and demographics. The Office of Rural Health categories for rurality and NIH categories for race were used.

Data analysis

We report descriptive statistics for CM. To compare differences between Veterans by CM, we report chi-squared tests for categorical variables and ANOVAs for continuous variables.

Results

Among 13,902 NTO Veterans with CM data, most were V (9,998, 72%), few were T 2% (n= 295), and some were TV 26% (n= 3,609). There were statistically significant differences between CM in number of interactions, latency between diagnosis and first NTO interaction, age at first NTO interaction, sex, race, rurality, and cancer type. Veterans diagnosed with lung cancer were more likely to exclusively use T. Veterans with breast cancer were more likely to exclusively use V. Specifically, T were oldest (mean age = 74.3), followed by TV (69.0) and V (61.6; p < .001). Women were most represented in V (28.3%) and Rural or highly rural residence was most common among T users (54.6%), compared to V (36.8%) and TV (43.0%; p < .001). Urban users were more prevalent in the TV group (61.9%) than in the T only group (45.4%).

Implications

We identified differences in communication modality based on Veteran characteristics. This could suggest differences in Veteran or provider preference, feasibility, or acceptability, based on CM.

Significance

While V communications appear to be achievable for many Veterans, more work is needed to determine preference, feasibility, and acceptability among Veterans and their care teams regarding V and T only cancer care.

Background

We examined characteristics of Veterans receiving care through NTO and their CM (e.g., telephone only [T], video only [V], or both [TV]). Relevant background: In-person VA cancer care can be challenging for many Veterans due to rurality, transportation, finances, and distance to subspecialists. Such factors may impact care modality preferences.

Methods

We linked a list of all Veterans who received NTO care with Corporate Data Warehouse data to confirm an ICD-10 diagnostic code for malignancy, and to define the number of NTO interactions, latency of days between diagnosis and first NTO interaction, and demographics. The Office of Rural Health categories for rurality and NIH categories for race were used.

Data analysis

We report descriptive statistics for CM. To compare differences between Veterans by CM, we report chi-squared tests for categorical variables and ANOVAs for continuous variables.

Results

Among 13,902 NTO Veterans with CM data, most were V (9,998, 72%), few were T 2% (n= 295), and some were TV 26% (n= 3,609). There were statistically significant differences between CM in number of interactions, latency between diagnosis and first NTO interaction, age at first NTO interaction, sex, race, rurality, and cancer type. Veterans diagnosed with lung cancer were more likely to exclusively use T. Veterans with breast cancer were more likely to exclusively use V. Specifically, T were oldest (mean age = 74.3), followed by TV (69.0) and V (61.6; p < .001). Women were most represented in V (28.3%) and Rural or highly rural residence was most common among T users (54.6%), compared to V (36.8%) and TV (43.0%; p < .001). Urban users were more prevalent in the TV group (61.9%) than in the T only group (45.4%).

Implications

We identified differences in communication modality based on Veteran characteristics. This could suggest differences in Veteran or provider preference, feasibility, or acceptability, based on CM.

Significance

While V communications appear to be achievable for many Veterans, more work is needed to determine preference, feasibility, and acceptability among Veterans and their care teams regarding V and T only cancer care.

Background

We examined characteristics of Veterans receiving care through NTO and their CM (e.g., telephone only [T], video only [V], or both [TV]). Relevant background: In-person VA cancer care can be challenging for many Veterans due to rurality, transportation, finances, and distance to subspecialists. Such factors may impact care modality preferences.

Methods

We linked a list of all Veterans who received NTO care with Corporate Data Warehouse data to confirm an ICD-10 diagnostic code for malignancy, and to define the number of NTO interactions, latency of days between diagnosis and first NTO interaction, and demographics. The Office of Rural Health categories for rurality and NIH categories for race were used.

Data analysis

We report descriptive statistics for CM. To compare differences between Veterans by CM, we report chi-squared tests for categorical variables and ANOVAs for continuous variables.

Results

Among 13,902 NTO Veterans with CM data, most were V (9,998, 72%), few were T 2% (n= 295), and some were TV 26% (n= 3,609). There were statistically significant differences between CM in number of interactions, latency between diagnosis and first NTO interaction, age at first NTO interaction, sex, race, rurality, and cancer type. Veterans diagnosed with lung cancer were more likely to exclusively use T. Veterans with breast cancer were more likely to exclusively use V. Specifically, T were oldest (mean age = 74.3), followed by TV (69.0) and V (61.6; p < .001). Women were most represented in V (28.3%) and Rural or highly rural residence was most common among T users (54.6%), compared to V (36.8%) and TV (43.0%; p < .001). Urban users were more prevalent in the TV group (61.9%) than in the T only group (45.4%).

Implications

We identified differences in communication modality based on Veteran characteristics. This could suggest differences in Veteran or provider preference, feasibility, or acceptability, based on CM.

Significance

While V communications appear to be achievable for many Veterans, more work is needed to determine preference, feasibility, and acceptability among Veterans and their care teams regarding V and T only cancer care.