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Investigating Real-World Tolerance and Dose Reductions of Oncology Multikinase Inhibitors in a VA Population
Investigating Real-World Tolerance and Dose Reductions of Oncology Multikinase Inhibitors in a VA Population
The US Department of Veterans Affairs (VA) annually treats around 450,000 veterans with cancer and diagnoses an additional 56,000.1,2 Oral multikinase inhibitors (MKIs) are widely used as targeted therapies for many different malignancies. Despite the ease of oral administration, these agents are often accompanied by significant adverse effects (AEs) and drug-drug interactions.3,4 Common AEs include hypertension, cutaneous reactions, gastrointestinal disturbances, proteinuria, and fatigue. Some serious outcomes that may occur are myocardial infarction, thrombosis, nephrotic syndrome, hemorrhage, hepatotoxicity, and gastrointestinal events.5,6 Due to poor tolerability of these AEs, dose reductions, frequent therapy holds, and discontinuation of therapy may occur.
The US Food and Drug Administration recognizes dosing challenges with novel therapies and has created the Oncology Center of Excellence (OCE) Project Optimus initiative to reform dose optimization in oncology drug development. The initiative aims to shift the focus from establishing dose regimens based on the maximum tolerated doses of cytotoxic chemotherapeutics to an emphasis on maximum efficacy, safety, and tolerability, which better reflect real-world dosing.7,8
MKIs can be challenging to manage because of the frequent toxicity-related dose reductions, interruptions, and discontinuations. In a multicenter retrospective study, Schnadig et al investigated dosing characteristics of first-line sunitinib for advanced renal cell carcinoma (RCC) and found that, among 114 patients who experienced AEs while taking sunitinib, 39.5% had dose reductions, 5.3% delayed therapy, 18.4% required additional supportive medications, and 22.8% discontinued sunitinib.9 Overall survival and median progression-free survival of these patients were lower than reported by Motzer et al in a phase 3 clinical trial.10 Schnadig et al concluded that patients treated with sunitinib for RCC in the community setting required more frequent dose reductions and had less time on therapy compared with patients in clinical trials, which ultimately impacted clinical outcomes.9
At the VA North Texas Health Care System (VANTHCS), patients with cancer have difficulty tolerating MKIs and often require dose alterations and/or discontinuation because of drug intolerance rather than discontinuation due to progression. Frequent dose adjustments for toxicity management can place more strain on patients and health care resources because of additional appointments, clinician time, and emergency department visits. Escalating drug costs can also cause concern when prescription doses are unused or changed frequently.
To capture and quantify prescribing practices and dose adjustments, this study evaluated the tolerability of MKIs at VANTHCS. This analysis may also guide clinicians in the selection of starting doses as well as dose titration expectations to optimize MKI therapy.
METHODS
This single-center, retrospective chart review analyzed patients receiving oral oncology MKIs for various malignancies at VANTHCS between January 1, 2014, and October 31, 2024. Participants included adults aged ≥ 18 years with a prescription for axitinib, cabozantinib, lenvatinib, pazopanib, regorafenib, sorafenib, or sunitinib initiated by the hematology/oncology service at VANTHCS. Patients were included if they had follow-up documentation with the hematology/oncology service and/or other VANTHCS clinicians outlining their course of therapy after MKI initiation. Patients were excluded if they did not have sufficient follow-up documentation (eg, transferred care to a non-VA health care practitioner [HCP], moved to another VA health care system), were enrolled in clinical trials, or were prescribed an MKI from a Care in the Community (CITC) prescriber. Electronic health record review and data collection were performed using the VA Computerized Patient Record System and Research Electronic Data Capture. Data were collected from the time of initiation to cessation of therapy and included information regarding therapy changes, progressive disease, and date of death, when available. Data collected included age, sex, race, comorbidities, date of death, type of malignancy and subtypes, cancer stage, MKI used (ie, drug, dose, frequency, schedule, and indication), dates of medication changes (ie, start, adjustment, hold, discontinuation), concurrent antineoplastic treatments, and AEs documented at times of dose change or interruption.
The primary outcome was MKI tolerance determined using relative dose intensity (RDI) and mean and median time on therapy. Two methods are used to calculate RDI that vary in how they approach time on therapy as outlined in Hawn et al.11 This study used method 2, which accounts for holds in therapy by comparing the actual duration of treatment with the duration expected according to treatment protocol. Method 1 compares the prescribed dose with the administered dose and does not adjust for holds.11 Using method 2, the RDI in this study was calculated by dividing the total actual dose given by the total indicated dose for the malignancy being treated, which accounts for duration of treatment.

The total actual dose was the strength, frequency, and days on therapy for each time frame of treatment multiplied together. This method accounted for all dose adjustments and time periods of treatment holds, including patient self-adjustments, prescriber-directed adjustments, and nonadherence determined by HCP documentation and/or prescription data. Similarly, the indicated total dose was calculated by multiplying the indicated strength, frequency, and all days that treatment should have occurred (time from start to finish). Indicated doses were derived from the prescribing information for each malignancy with the exception of sunitinib, for which the off-label dose of 37.5 mg daily was considered a full dose.12,13 The total indicated dose for axitinib was calculated by considering the dose escalation schedule from the prescribing information.
Patients who required dose reductions due to renal/hepatic impairments or drug-drug interactions had their total indicated dose calculated using dose adjustments listed in the prescribing information. The mean RDI for each MKI agent was calculated by averaging the RDI for each prescription. The overall combined mean RDI included the means of all the MKIs reviewed to avoid skewing the results toward an MKI with more prescriptions. RDIs were also calculated for each cancer type for each agent. Additional descriptive secondary outcomes included rates of AEs and adjustments in doses.
RESULTS
Electronic data extraction identified 278 patients with 366 MKI prescriptions, of which 108 veterans with 158 MKI prescriptions were excluded. The top reason for exclusion was patients managed through CITC. Ultimately, 170 veterans with 208 MKI prescriptions managed by the VANTHCS hematology/oncology clinic were included (Table 1). Among patients receiving MKIs, the mean age was 72.7 years, 98% were male, and 99% had metastatic disease.

The overall combined mean MKI RDI was 67.5% using method 2 and ranged from 85.5% for sunitinib to 49.0% for sorafenib (Figure 1). Additional information regarding mean and median RDIs using method 2 is shown in Figure 1 and further subdivided by cancer type in Table 2. Median RDIs overall were similar to mean RDIs for most agents. Figure 2 indicates the mean and median time on therapy, reflecting time on therapy excluding days therapy was held. The overall combined mean and median days on therapy for all MKIs were 155 days and 95 days, respectively. Mean time on therapy depended on the agent used and ranged from 35 days (regorafenib) to 237 days (cabozantinib).

Of 208 MKI prescriptions, 127 (61.1%) were initiated at a reduced dose due to baseline concerns for tolerance such as performance status, frailty, and prior intolerance of other treatments. Eighty-one prescriptions (38.9%) were initiated at their indicated doses. Ninety prescriptions (43.3%) required dose reductions during treatment. Some MKI prescriptions had multiple dose increases and decreases, which is why RDI more accurately reflects dose adjustments. A total of 376 AEs that contributed to a dose adjustment, hold, or discontinuation occurred across all MKI prescriptions. The most common AEs were 82 failure-to-thrive events (21.8%) (fatigue, malaise, loss of appetite, reduced mobility, global decline), 79 gastrointestinal events (21.0%) (nausea, vomiting, diarrhea, abdominal pain), 62 dermatologic events (16.5%) (rash, hand-foot skin reactions, allergic response), 61 hepatic dysfunction events (16.2%) (liver enzyme elevations, hyperbilirubinemia), 40 cardiovascular events (10.6%) (hypertension, heart failure exacerbations, edema), and 33 renal dysfunction events (8.8%) (acute kidney injury, proteinuria) (Appendix 1).

DISCUSSION
The mean RDI of MKI prescriptions used in the veteran population at VANTHCS was about two-thirds of the indicated dose. These results indicate that most veterans required dose reductions and/or holds due to concerns over initial tolerance/performance status, worsening clinical condition, and/or intolerable AEs attributed to treatment. A retrospective study conducted by Denduluri et al suggested that an RDI of < 85% is a clinically meaningful reduction for traditional chemotherapy based on previous literature.14 However, it is less clear what RDI should be expected specifically for MKIs in real-world populations. The MKI phase 3 approval trials in RCC for axitinib, lenvatinib, and sunitinib found median RDIs of 89.4%, 69.6% to 70.4%, and 83.9%, respectively. Each trial cited dose reductions most commonly as the result of treatment-related AEs.15,16
Studies on the impact of RDIs on survival outcomes found that higher RDIs may improve overall and progression-free survival. Retrospective studies inspecting lenvatinib in hepatocellular carcinoma (HCC) indicated that an RDI > 70% in the initial 4 weeks resulted in favorable survival outcomes.17 Similarly, a retrospective study investigating sunitinib in RCC found that an RDI > 60% conferred favorable survival outcomes.18 Alghamdi et al noted that patients taking sorafenib for HCC who had RDI > 50% had a favorable trend in survival characteristics. Interestingly, the study found an RDI of 50% to 75% appeared to have better survival than an RDI > 75%.19 The authors of these studies hypothesized that additional dose reductions allowed for longer total time on therapy due to improved tolerability.17-19
This analysis found that the RDIs for most MKI agents at VANTHCS were < 85% and lower than the RDIs found in other review articles and phase 3 trials, with the exceptions of pazopanib in thyroid cancer and sunitinib in gastrointestinal stromal tumor (GIST), thyroid cancer, and neuroendocrine cancer. The reasons for the lower RDIs in this study are likely multifactorial, reflecting patient population characteristics, off-label dosing practices, and HCP experiences with these agents. Many veterans have chronic comorbidities that could contribute to reduced performance status and ability to tolerate these therapies. Despite attempts to preemptively reduce doses for patients and account for potential impaired tolerance, there were patients who required further dose reductions in our study.
Failure to thrive was the most common AE leading to dose adjustment or discontinuation, which illustrates the extensive effects these agents have on patient functioning in a real-world population. Notably though, the RDI for sunitinib was higher in this population because about half of patients were dosed using the off-label recommendation, whereas the prescribing information recommends a more intensive 6-week dosing cycle for certain cancer types.12,13,20 Sorafenib was also often dose-adjusted based on a pharmacokinetic study of sorafenib in renal/hepatic dysfunction, and the RDI likely reflects the off-label prescribing pattern.21
Patients with thyroid cancer were found to have higher RDIs compared with those receiving the same agents for other cancer types. Improved tolerability of MKIs in thyroid cancer may be due to a generally more tolerable disease course. Thyroid cancer is the most common cancer in individuals aged < 40 years, a population that is often more robust with fewer comorbidities. Moreover, the 5-year relative survival rate for thyroid cancer remains > 98%.22 This rate is in contrast to those for other cancer types such as HCC, with a 5-year relative survival rate of only 15%.23
It is challenging to compare the mean and median times on therapy found in this study with those in current literature, as this review included multiple different cancer types for each agent. However, the numbers are generally lower than durations of therapy found across the different disease states and further emphasize the difficulty in tolerating MKIs in the VANTHCS population. Regorafenib had a short duration of time on therapy, which highlights the importance of trials like ReDOS and initiatives such as OCE Project Optimus in helping improve tolerance.7,8,24
Comparing our results with other studies proved challenging because the RDI calculation methods were not specified. Calculating RDIs in this study using method 1, which does not account for holds, resulted in higher RDIs (Appendix 2). Using method 1, all MKIs had RDIs < 85%, except for pazopanib in thyroid cancer (100%) and RCC (87.9%), and sunitinib in GIST (93.6%), thyroid cancer (100%), and neuroendocrine cancer (93.7%). Notably, using method 1 increased the RDI for pazopanib in neuroendocrine cancer from 5.4% to 50.0%. The low RDI was attributed to a single veteran with a long hold duration, which demonstrates the discrepancy that can occur between the 2 methods.

Limitations
The retrospective design, lack of survival outcomes, and difficulty comparing results with other literature were limitations of this study. Because survival outcomes were not evaluated, future research should seek to investigate how RDIs and dose adjustments made among MKIs can affect survival outcomes in real-world populations. This veteran population with cancer often had multiple chronic comorbidities, which may have contributed to difficulty tolerating MKIs and could have impacted results. Disease-related factors may have influenced the poor tolerance of the MKIs and were not specifically accounted for. Adjustment for comorbidities was not possible because of discrepancies and/or incomplete diagnosis codes and Eastern Cooperative Oncology Group performance status scores documented in patient charts. Therefore, we decided not to report these findings due to potential inaccuracies.
CONCLUSIONS
Results of this study demonstrate that oncology MKI agents used at VANTHCS were difficult for patients to tolerate, leading to suboptimal dosing compared with indicated doses established in clinical trials and prescribing information. Clinicians may use these data to help guide clinical decision-making whenever initiating and managing MKI agents in this population. These findings reinforce that MKI agents are often difficult to tolerate in real-world practice, and indicated doses are often not achieved. Further studies should aim to investigate the effect that various RDIs have on overall survival. Further investigation into different dosing schemes for MKIs to improve tolerability and longer-term use may also prove beneficial.
This analysis may help guide clinicians to carefully approach dosing MKI agents in the veteran population. Given the RDI and AEs, more clinicians may consider starting at lower than indicated doses with the goal to titrate up as tolerated. Additionally, the results highlight the importance of considering palliative care consults and ensuring appropriate supportive care agents are preemptively engaged and adjusted as needed. Approaching dosing and titrations cautiously may help reduce the burden of management on the health care system.
- Frequently asked questions. VA National Oncology Program. 2025. Accessed December 15, 2025. https://www.cancer.va.gov/CANCER/faqs.html
- Torez L. Reigniting the cancer moonshot to beat cancer. VA News. April 20, 2023. Accessed April 6, 2026. https://news.va.gov/118378/reigniting-the-cancer-moonshot-to-beat-cancer
- Shah NN, Casella E, Capozzi D, et al. Improving the safety of oral chemotherapy at an academic medical center. J Oncol Pract. 2016;12:e71-e76. doi:10.1200/JOP.2015.007260
- Hussaarts KGAM, Veerman GDM, Jansman FGA, et al. Clinically relevant drug interactions with multikinase inhibitors: a review. Ther Adv Med Oncol. 2019;11:1758835918818347. doi:10.1177/1758835918818347
- Shyam Sunder S, Sharma UC, Pokharel S. Adverse effects of tyrosine kinase inhibitors in cancer therapy: pathophysiology, mechanisms and clinical management. Signal Transduct Target Ther. 2023;8:262. doi:10.1038/s41392-023-01469-6
- Thomson RJ, Moshirfar M, Ronquillo Y. Tyrosine kinase inhibitors. In: StatPearls [Internet]. StatPearls Publishing; updated July 18, 2023. Accessed December 15, 2025. https://www.ncbi.nlm.nih.gov/books/NBK563322/
- Project Optimus. US Food and Drug Administration. Updated December 6, 2024. Accessed December 15, 2025. https://www.fda.gov/about-fda/oncology-center-excellence/project-optimus
- Optimizing the dosage of human prescription drugs and biological products for the treatment of oncologic diseases: Guidance for Industry. Docket number FDA-2022-D-2827. US Food and Drug Administration. August 2024. Accessed December 15, 2025. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/optimizing-dosage-human-prescription-drugs-and-biological-products-treatment-oncologic-diseases
- Schnadig ID, Hutson TE, Chung H, et al. Dosing patterns, toxicity, and outcomes in patients treated with first-line sunitinib for advanced renal cell carcinoma in community-based practices. Clin Genitourin Cancer. 2014;12:413-421. doi:10.1016/j.clgc.2014.06.015
- Motzer RJ, Hutson TE, Tomczak P, et al. Sunitinib versus interferon alfa in metastatic renal-cell carcinoma. N Engl J Med. 2007;356:115-124. doi:10.1056/nejmoa065044
- Hawn C, Bansal D. Relative dose intensity in oncology trials: a discussion of two approaches. PharmaSUG. 2024. Accessed April 6, 2026. https://pharmasug.org/proceedings/2024/ST/PharmaSUG-2024-ST-297.pdf
- George S, Merriam P, Maki RG, et al. Multicenter phase II trial of sunitinib in the treatment of nongastrointestinal stromal tumor sarcomas. J Clin Oncol. 2009;27:3154-3160. doi:10.1200/jco.2008.20.9890
- George S, Blay JY, Casali PG, et al. Clinical evaluation of continuous daily dosing of sunitinib malate in patients with advanced gastrointestinal stromal tumour after imatinib failure. Eur J Cancer. 2009;45:1959-1968. doi:10.1016/j.ejca.2009.02.011
- Denduluri N, Patt DA, Wang Y, et al. Dose delays, dose reductions, and relative dose intensity in patients with cancer who received adjuvant or neoadjuvant chemotherapy in community oncology practices. J Natl Compr Canc Netw. 2015;13:1383-1393. doi:10.6004/jnccn.2015.0166
- Motzer RJ, Penkov K, Haanen J, et al. Avelumab plus axitinib versus sunitinib for advanced renal-cell carcinoma. N Engl J Med. 2019;380:1103-1115. doi:10.1056/nejmoa1816047
- Motzer R, Alekseev B, Rha SY, et al. Lenvatinib plus pembrolizumab or everolimus for advanced renal cell carcinoma. N Engl J Med. 2021;384:1289-1300. doi:10.1056/nejmoa2035716
- Kirino S, Tsuchiya K, Kurosaki M, et al. Relative dose intensity over the first four weeks of lenvatinib therapy is a factor of favorable response and overall survival in patients with unresectable hepatocellular carcinoma. PloS One. 2020;15:e0231828. doi:10.1371/journal.pone.0231828
- Ishihara H, Takagi T, Kondo T, et al. Decreased relative dose intensity during the early phase of treatment impacts the therapeutic efficacy of sunitinib in metastatic renal cell carcinoma. Jpn J Clin Oncol. 2018;48:667-672. doi:10.1093/jjco/hyy078
- Alghamdi MA, Amaro CP, Lee-Ying R, et al. Effect of sorafenib starting dose and dose intensity on survival in patients with hepatocellular carcinoma: results from a Canadian Multicenter Database. Cancer Med. 2020;9:4918-4928. doi:10.1002/cam4.3228
- Motzer RJ, Rini BI, Bukowski RM, et al. Sunitinib in patients with metastatic renal cell carcinoma. JAMA. 2006;295:2516-2524. doi:10.1001/jama.295.21.2516
- Miller AA, Murry DJ, Owzar K, et al. Phase I and pharmacokinetic study of sorafenib in patients with hepatic or renal dysfunction: CALGB 60301. J Clin Oncol. 2009;27:1800-1805. doi:10.1200/jco.2008.20.0931
- Boucai L, Zafereo M, Cabanillas ME. Thyroid cancer: a review. JAMA. 2024;331:425-435. doi:10.1001/jama.2023.26348
- Amin N, Anwar J, Sulaiman A, et al. Hepatocellular carcinoma: a comprehensive review. Diseases. 2025;13:207. doi:10.3390/diseases13070207
- Bekaii-Saab TS, Ou FS, Ahn DH, et al. Regorafenib dose-optimisation in patients with refractory metastatic colorectal cancer (ReDOS): a randomised, multicentre, open-label, phase 2 study. Lancet Oncol. 2019;20:1070-1082. doi:10.1016/s1470-2045(19)30272-4
The US Department of Veterans Affairs (VA) annually treats around 450,000 veterans with cancer and diagnoses an additional 56,000.1,2 Oral multikinase inhibitors (MKIs) are widely used as targeted therapies for many different malignancies. Despite the ease of oral administration, these agents are often accompanied by significant adverse effects (AEs) and drug-drug interactions.3,4 Common AEs include hypertension, cutaneous reactions, gastrointestinal disturbances, proteinuria, and fatigue. Some serious outcomes that may occur are myocardial infarction, thrombosis, nephrotic syndrome, hemorrhage, hepatotoxicity, and gastrointestinal events.5,6 Due to poor tolerability of these AEs, dose reductions, frequent therapy holds, and discontinuation of therapy may occur.
The US Food and Drug Administration recognizes dosing challenges with novel therapies and has created the Oncology Center of Excellence (OCE) Project Optimus initiative to reform dose optimization in oncology drug development. The initiative aims to shift the focus from establishing dose regimens based on the maximum tolerated doses of cytotoxic chemotherapeutics to an emphasis on maximum efficacy, safety, and tolerability, which better reflect real-world dosing.7,8
MKIs can be challenging to manage because of the frequent toxicity-related dose reductions, interruptions, and discontinuations. In a multicenter retrospective study, Schnadig et al investigated dosing characteristics of first-line sunitinib for advanced renal cell carcinoma (RCC) and found that, among 114 patients who experienced AEs while taking sunitinib, 39.5% had dose reductions, 5.3% delayed therapy, 18.4% required additional supportive medications, and 22.8% discontinued sunitinib.9 Overall survival and median progression-free survival of these patients were lower than reported by Motzer et al in a phase 3 clinical trial.10 Schnadig et al concluded that patients treated with sunitinib for RCC in the community setting required more frequent dose reductions and had less time on therapy compared with patients in clinical trials, which ultimately impacted clinical outcomes.9
At the VA North Texas Health Care System (VANTHCS), patients with cancer have difficulty tolerating MKIs and often require dose alterations and/or discontinuation because of drug intolerance rather than discontinuation due to progression. Frequent dose adjustments for toxicity management can place more strain on patients and health care resources because of additional appointments, clinician time, and emergency department visits. Escalating drug costs can also cause concern when prescription doses are unused or changed frequently.
To capture and quantify prescribing practices and dose adjustments, this study evaluated the tolerability of MKIs at VANTHCS. This analysis may also guide clinicians in the selection of starting doses as well as dose titration expectations to optimize MKI therapy.
METHODS
This single-center, retrospective chart review analyzed patients receiving oral oncology MKIs for various malignancies at VANTHCS between January 1, 2014, and October 31, 2024. Participants included adults aged ≥ 18 years with a prescription for axitinib, cabozantinib, lenvatinib, pazopanib, regorafenib, sorafenib, or sunitinib initiated by the hematology/oncology service at VANTHCS. Patients were included if they had follow-up documentation with the hematology/oncology service and/or other VANTHCS clinicians outlining their course of therapy after MKI initiation. Patients were excluded if they did not have sufficient follow-up documentation (eg, transferred care to a non-VA health care practitioner [HCP], moved to another VA health care system), were enrolled in clinical trials, or were prescribed an MKI from a Care in the Community (CITC) prescriber. Electronic health record review and data collection were performed using the VA Computerized Patient Record System and Research Electronic Data Capture. Data were collected from the time of initiation to cessation of therapy and included information regarding therapy changes, progressive disease, and date of death, when available. Data collected included age, sex, race, comorbidities, date of death, type of malignancy and subtypes, cancer stage, MKI used (ie, drug, dose, frequency, schedule, and indication), dates of medication changes (ie, start, adjustment, hold, discontinuation), concurrent antineoplastic treatments, and AEs documented at times of dose change or interruption.
The primary outcome was MKI tolerance determined using relative dose intensity (RDI) and mean and median time on therapy. Two methods are used to calculate RDI that vary in how they approach time on therapy as outlined in Hawn et al.11 This study used method 2, which accounts for holds in therapy by comparing the actual duration of treatment with the duration expected according to treatment protocol. Method 1 compares the prescribed dose with the administered dose and does not adjust for holds.11 Using method 2, the RDI in this study was calculated by dividing the total actual dose given by the total indicated dose for the malignancy being treated, which accounts for duration of treatment.

The total actual dose was the strength, frequency, and days on therapy for each time frame of treatment multiplied together. This method accounted for all dose adjustments and time periods of treatment holds, including patient self-adjustments, prescriber-directed adjustments, and nonadherence determined by HCP documentation and/or prescription data. Similarly, the indicated total dose was calculated by multiplying the indicated strength, frequency, and all days that treatment should have occurred (time from start to finish). Indicated doses were derived from the prescribing information for each malignancy with the exception of sunitinib, for which the off-label dose of 37.5 mg daily was considered a full dose.12,13 The total indicated dose for axitinib was calculated by considering the dose escalation schedule from the prescribing information.
Patients who required dose reductions due to renal/hepatic impairments or drug-drug interactions had their total indicated dose calculated using dose adjustments listed in the prescribing information. The mean RDI for each MKI agent was calculated by averaging the RDI for each prescription. The overall combined mean RDI included the means of all the MKIs reviewed to avoid skewing the results toward an MKI with more prescriptions. RDIs were also calculated for each cancer type for each agent. Additional descriptive secondary outcomes included rates of AEs and adjustments in doses.
RESULTS
Electronic data extraction identified 278 patients with 366 MKI prescriptions, of which 108 veterans with 158 MKI prescriptions were excluded. The top reason for exclusion was patients managed through CITC. Ultimately, 170 veterans with 208 MKI prescriptions managed by the VANTHCS hematology/oncology clinic were included (Table 1). Among patients receiving MKIs, the mean age was 72.7 years, 98% were male, and 99% had metastatic disease.

The overall combined mean MKI RDI was 67.5% using method 2 and ranged from 85.5% for sunitinib to 49.0% for sorafenib (Figure 1). Additional information regarding mean and median RDIs using method 2 is shown in Figure 1 and further subdivided by cancer type in Table 2. Median RDIs overall were similar to mean RDIs for most agents. Figure 2 indicates the mean and median time on therapy, reflecting time on therapy excluding days therapy was held. The overall combined mean and median days on therapy for all MKIs were 155 days and 95 days, respectively. Mean time on therapy depended on the agent used and ranged from 35 days (regorafenib) to 237 days (cabozantinib).

Of 208 MKI prescriptions, 127 (61.1%) were initiated at a reduced dose due to baseline concerns for tolerance such as performance status, frailty, and prior intolerance of other treatments. Eighty-one prescriptions (38.9%) were initiated at their indicated doses. Ninety prescriptions (43.3%) required dose reductions during treatment. Some MKI prescriptions had multiple dose increases and decreases, which is why RDI more accurately reflects dose adjustments. A total of 376 AEs that contributed to a dose adjustment, hold, or discontinuation occurred across all MKI prescriptions. The most common AEs were 82 failure-to-thrive events (21.8%) (fatigue, malaise, loss of appetite, reduced mobility, global decline), 79 gastrointestinal events (21.0%) (nausea, vomiting, diarrhea, abdominal pain), 62 dermatologic events (16.5%) (rash, hand-foot skin reactions, allergic response), 61 hepatic dysfunction events (16.2%) (liver enzyme elevations, hyperbilirubinemia), 40 cardiovascular events (10.6%) (hypertension, heart failure exacerbations, edema), and 33 renal dysfunction events (8.8%) (acute kidney injury, proteinuria) (Appendix 1).

DISCUSSION
The mean RDI of MKI prescriptions used in the veteran population at VANTHCS was about two-thirds of the indicated dose. These results indicate that most veterans required dose reductions and/or holds due to concerns over initial tolerance/performance status, worsening clinical condition, and/or intolerable AEs attributed to treatment. A retrospective study conducted by Denduluri et al suggested that an RDI of < 85% is a clinically meaningful reduction for traditional chemotherapy based on previous literature.14 However, it is less clear what RDI should be expected specifically for MKIs in real-world populations. The MKI phase 3 approval trials in RCC for axitinib, lenvatinib, and sunitinib found median RDIs of 89.4%, 69.6% to 70.4%, and 83.9%, respectively. Each trial cited dose reductions most commonly as the result of treatment-related AEs.15,16
Studies on the impact of RDIs on survival outcomes found that higher RDIs may improve overall and progression-free survival. Retrospective studies inspecting lenvatinib in hepatocellular carcinoma (HCC) indicated that an RDI > 70% in the initial 4 weeks resulted in favorable survival outcomes.17 Similarly, a retrospective study investigating sunitinib in RCC found that an RDI > 60% conferred favorable survival outcomes.18 Alghamdi et al noted that patients taking sorafenib for HCC who had RDI > 50% had a favorable trend in survival characteristics. Interestingly, the study found an RDI of 50% to 75% appeared to have better survival than an RDI > 75%.19 The authors of these studies hypothesized that additional dose reductions allowed for longer total time on therapy due to improved tolerability.17-19
This analysis found that the RDIs for most MKI agents at VANTHCS were < 85% and lower than the RDIs found in other review articles and phase 3 trials, with the exceptions of pazopanib in thyroid cancer and sunitinib in gastrointestinal stromal tumor (GIST), thyroid cancer, and neuroendocrine cancer. The reasons for the lower RDIs in this study are likely multifactorial, reflecting patient population characteristics, off-label dosing practices, and HCP experiences with these agents. Many veterans have chronic comorbidities that could contribute to reduced performance status and ability to tolerate these therapies. Despite attempts to preemptively reduce doses for patients and account for potential impaired tolerance, there were patients who required further dose reductions in our study.
Failure to thrive was the most common AE leading to dose adjustment or discontinuation, which illustrates the extensive effects these agents have on patient functioning in a real-world population. Notably though, the RDI for sunitinib was higher in this population because about half of patients were dosed using the off-label recommendation, whereas the prescribing information recommends a more intensive 6-week dosing cycle for certain cancer types.12,13,20 Sorafenib was also often dose-adjusted based on a pharmacokinetic study of sorafenib in renal/hepatic dysfunction, and the RDI likely reflects the off-label prescribing pattern.21
Patients with thyroid cancer were found to have higher RDIs compared with those receiving the same agents for other cancer types. Improved tolerability of MKIs in thyroid cancer may be due to a generally more tolerable disease course. Thyroid cancer is the most common cancer in individuals aged < 40 years, a population that is often more robust with fewer comorbidities. Moreover, the 5-year relative survival rate for thyroid cancer remains > 98%.22 This rate is in contrast to those for other cancer types such as HCC, with a 5-year relative survival rate of only 15%.23
It is challenging to compare the mean and median times on therapy found in this study with those in current literature, as this review included multiple different cancer types for each agent. However, the numbers are generally lower than durations of therapy found across the different disease states and further emphasize the difficulty in tolerating MKIs in the VANTHCS population. Regorafenib had a short duration of time on therapy, which highlights the importance of trials like ReDOS and initiatives such as OCE Project Optimus in helping improve tolerance.7,8,24
Comparing our results with other studies proved challenging because the RDI calculation methods were not specified. Calculating RDIs in this study using method 1, which does not account for holds, resulted in higher RDIs (Appendix 2). Using method 1, all MKIs had RDIs < 85%, except for pazopanib in thyroid cancer (100%) and RCC (87.9%), and sunitinib in GIST (93.6%), thyroid cancer (100%), and neuroendocrine cancer (93.7%). Notably, using method 1 increased the RDI for pazopanib in neuroendocrine cancer from 5.4% to 50.0%. The low RDI was attributed to a single veteran with a long hold duration, which demonstrates the discrepancy that can occur between the 2 methods.

Limitations
The retrospective design, lack of survival outcomes, and difficulty comparing results with other literature were limitations of this study. Because survival outcomes were not evaluated, future research should seek to investigate how RDIs and dose adjustments made among MKIs can affect survival outcomes in real-world populations. This veteran population with cancer often had multiple chronic comorbidities, which may have contributed to difficulty tolerating MKIs and could have impacted results. Disease-related factors may have influenced the poor tolerance of the MKIs and were not specifically accounted for. Adjustment for comorbidities was not possible because of discrepancies and/or incomplete diagnosis codes and Eastern Cooperative Oncology Group performance status scores documented in patient charts. Therefore, we decided not to report these findings due to potential inaccuracies.
CONCLUSIONS
Results of this study demonstrate that oncology MKI agents used at VANTHCS were difficult for patients to tolerate, leading to suboptimal dosing compared with indicated doses established in clinical trials and prescribing information. Clinicians may use these data to help guide clinical decision-making whenever initiating and managing MKI agents in this population. These findings reinforce that MKI agents are often difficult to tolerate in real-world practice, and indicated doses are often not achieved. Further studies should aim to investigate the effect that various RDIs have on overall survival. Further investigation into different dosing schemes for MKIs to improve tolerability and longer-term use may also prove beneficial.
This analysis may help guide clinicians to carefully approach dosing MKI agents in the veteran population. Given the RDI and AEs, more clinicians may consider starting at lower than indicated doses with the goal to titrate up as tolerated. Additionally, the results highlight the importance of considering palliative care consults and ensuring appropriate supportive care agents are preemptively engaged and adjusted as needed. Approaching dosing and titrations cautiously may help reduce the burden of management on the health care system.
The US Department of Veterans Affairs (VA) annually treats around 450,000 veterans with cancer and diagnoses an additional 56,000.1,2 Oral multikinase inhibitors (MKIs) are widely used as targeted therapies for many different malignancies. Despite the ease of oral administration, these agents are often accompanied by significant adverse effects (AEs) and drug-drug interactions.3,4 Common AEs include hypertension, cutaneous reactions, gastrointestinal disturbances, proteinuria, and fatigue. Some serious outcomes that may occur are myocardial infarction, thrombosis, nephrotic syndrome, hemorrhage, hepatotoxicity, and gastrointestinal events.5,6 Due to poor tolerability of these AEs, dose reductions, frequent therapy holds, and discontinuation of therapy may occur.
The US Food and Drug Administration recognizes dosing challenges with novel therapies and has created the Oncology Center of Excellence (OCE) Project Optimus initiative to reform dose optimization in oncology drug development. The initiative aims to shift the focus from establishing dose regimens based on the maximum tolerated doses of cytotoxic chemotherapeutics to an emphasis on maximum efficacy, safety, and tolerability, which better reflect real-world dosing.7,8
MKIs can be challenging to manage because of the frequent toxicity-related dose reductions, interruptions, and discontinuations. In a multicenter retrospective study, Schnadig et al investigated dosing characteristics of first-line sunitinib for advanced renal cell carcinoma (RCC) and found that, among 114 patients who experienced AEs while taking sunitinib, 39.5% had dose reductions, 5.3% delayed therapy, 18.4% required additional supportive medications, and 22.8% discontinued sunitinib.9 Overall survival and median progression-free survival of these patients were lower than reported by Motzer et al in a phase 3 clinical trial.10 Schnadig et al concluded that patients treated with sunitinib for RCC in the community setting required more frequent dose reductions and had less time on therapy compared with patients in clinical trials, which ultimately impacted clinical outcomes.9
At the VA North Texas Health Care System (VANTHCS), patients with cancer have difficulty tolerating MKIs and often require dose alterations and/or discontinuation because of drug intolerance rather than discontinuation due to progression. Frequent dose adjustments for toxicity management can place more strain on patients and health care resources because of additional appointments, clinician time, and emergency department visits. Escalating drug costs can also cause concern when prescription doses are unused or changed frequently.
To capture and quantify prescribing practices and dose adjustments, this study evaluated the tolerability of MKIs at VANTHCS. This analysis may also guide clinicians in the selection of starting doses as well as dose titration expectations to optimize MKI therapy.
METHODS
This single-center, retrospective chart review analyzed patients receiving oral oncology MKIs for various malignancies at VANTHCS between January 1, 2014, and October 31, 2024. Participants included adults aged ≥ 18 years with a prescription for axitinib, cabozantinib, lenvatinib, pazopanib, regorafenib, sorafenib, or sunitinib initiated by the hematology/oncology service at VANTHCS. Patients were included if they had follow-up documentation with the hematology/oncology service and/or other VANTHCS clinicians outlining their course of therapy after MKI initiation. Patients were excluded if they did not have sufficient follow-up documentation (eg, transferred care to a non-VA health care practitioner [HCP], moved to another VA health care system), were enrolled in clinical trials, or were prescribed an MKI from a Care in the Community (CITC) prescriber. Electronic health record review and data collection were performed using the VA Computerized Patient Record System and Research Electronic Data Capture. Data were collected from the time of initiation to cessation of therapy and included information regarding therapy changes, progressive disease, and date of death, when available. Data collected included age, sex, race, comorbidities, date of death, type of malignancy and subtypes, cancer stage, MKI used (ie, drug, dose, frequency, schedule, and indication), dates of medication changes (ie, start, adjustment, hold, discontinuation), concurrent antineoplastic treatments, and AEs documented at times of dose change or interruption.
The primary outcome was MKI tolerance determined using relative dose intensity (RDI) and mean and median time on therapy. Two methods are used to calculate RDI that vary in how they approach time on therapy as outlined in Hawn et al.11 This study used method 2, which accounts for holds in therapy by comparing the actual duration of treatment with the duration expected according to treatment protocol. Method 1 compares the prescribed dose with the administered dose and does not adjust for holds.11 Using method 2, the RDI in this study was calculated by dividing the total actual dose given by the total indicated dose for the malignancy being treated, which accounts for duration of treatment.

The total actual dose was the strength, frequency, and days on therapy for each time frame of treatment multiplied together. This method accounted for all dose adjustments and time periods of treatment holds, including patient self-adjustments, prescriber-directed adjustments, and nonadherence determined by HCP documentation and/or prescription data. Similarly, the indicated total dose was calculated by multiplying the indicated strength, frequency, and all days that treatment should have occurred (time from start to finish). Indicated doses were derived from the prescribing information for each malignancy with the exception of sunitinib, for which the off-label dose of 37.5 mg daily was considered a full dose.12,13 The total indicated dose for axitinib was calculated by considering the dose escalation schedule from the prescribing information.
Patients who required dose reductions due to renal/hepatic impairments or drug-drug interactions had their total indicated dose calculated using dose adjustments listed in the prescribing information. The mean RDI for each MKI agent was calculated by averaging the RDI for each prescription. The overall combined mean RDI included the means of all the MKIs reviewed to avoid skewing the results toward an MKI with more prescriptions. RDIs were also calculated for each cancer type for each agent. Additional descriptive secondary outcomes included rates of AEs and adjustments in doses.
RESULTS
Electronic data extraction identified 278 patients with 366 MKI prescriptions, of which 108 veterans with 158 MKI prescriptions were excluded. The top reason for exclusion was patients managed through CITC. Ultimately, 170 veterans with 208 MKI prescriptions managed by the VANTHCS hematology/oncology clinic were included (Table 1). Among patients receiving MKIs, the mean age was 72.7 years, 98% were male, and 99% had metastatic disease.

The overall combined mean MKI RDI was 67.5% using method 2 and ranged from 85.5% for sunitinib to 49.0% for sorafenib (Figure 1). Additional information regarding mean and median RDIs using method 2 is shown in Figure 1 and further subdivided by cancer type in Table 2. Median RDIs overall were similar to mean RDIs for most agents. Figure 2 indicates the mean and median time on therapy, reflecting time on therapy excluding days therapy was held. The overall combined mean and median days on therapy for all MKIs were 155 days and 95 days, respectively. Mean time on therapy depended on the agent used and ranged from 35 days (regorafenib) to 237 days (cabozantinib).

Of 208 MKI prescriptions, 127 (61.1%) were initiated at a reduced dose due to baseline concerns for tolerance such as performance status, frailty, and prior intolerance of other treatments. Eighty-one prescriptions (38.9%) were initiated at their indicated doses. Ninety prescriptions (43.3%) required dose reductions during treatment. Some MKI prescriptions had multiple dose increases and decreases, which is why RDI more accurately reflects dose adjustments. A total of 376 AEs that contributed to a dose adjustment, hold, or discontinuation occurred across all MKI prescriptions. The most common AEs were 82 failure-to-thrive events (21.8%) (fatigue, malaise, loss of appetite, reduced mobility, global decline), 79 gastrointestinal events (21.0%) (nausea, vomiting, diarrhea, abdominal pain), 62 dermatologic events (16.5%) (rash, hand-foot skin reactions, allergic response), 61 hepatic dysfunction events (16.2%) (liver enzyme elevations, hyperbilirubinemia), 40 cardiovascular events (10.6%) (hypertension, heart failure exacerbations, edema), and 33 renal dysfunction events (8.8%) (acute kidney injury, proteinuria) (Appendix 1).

DISCUSSION
The mean RDI of MKI prescriptions used in the veteran population at VANTHCS was about two-thirds of the indicated dose. These results indicate that most veterans required dose reductions and/or holds due to concerns over initial tolerance/performance status, worsening clinical condition, and/or intolerable AEs attributed to treatment. A retrospective study conducted by Denduluri et al suggested that an RDI of < 85% is a clinically meaningful reduction for traditional chemotherapy based on previous literature.14 However, it is less clear what RDI should be expected specifically for MKIs in real-world populations. The MKI phase 3 approval trials in RCC for axitinib, lenvatinib, and sunitinib found median RDIs of 89.4%, 69.6% to 70.4%, and 83.9%, respectively. Each trial cited dose reductions most commonly as the result of treatment-related AEs.15,16
Studies on the impact of RDIs on survival outcomes found that higher RDIs may improve overall and progression-free survival. Retrospective studies inspecting lenvatinib in hepatocellular carcinoma (HCC) indicated that an RDI > 70% in the initial 4 weeks resulted in favorable survival outcomes.17 Similarly, a retrospective study investigating sunitinib in RCC found that an RDI > 60% conferred favorable survival outcomes.18 Alghamdi et al noted that patients taking sorafenib for HCC who had RDI > 50% had a favorable trend in survival characteristics. Interestingly, the study found an RDI of 50% to 75% appeared to have better survival than an RDI > 75%.19 The authors of these studies hypothesized that additional dose reductions allowed for longer total time on therapy due to improved tolerability.17-19
This analysis found that the RDIs for most MKI agents at VANTHCS were < 85% and lower than the RDIs found in other review articles and phase 3 trials, with the exceptions of pazopanib in thyroid cancer and sunitinib in gastrointestinal stromal tumor (GIST), thyroid cancer, and neuroendocrine cancer. The reasons for the lower RDIs in this study are likely multifactorial, reflecting patient population characteristics, off-label dosing practices, and HCP experiences with these agents. Many veterans have chronic comorbidities that could contribute to reduced performance status and ability to tolerate these therapies. Despite attempts to preemptively reduce doses for patients and account for potential impaired tolerance, there were patients who required further dose reductions in our study.
Failure to thrive was the most common AE leading to dose adjustment or discontinuation, which illustrates the extensive effects these agents have on patient functioning in a real-world population. Notably though, the RDI for sunitinib was higher in this population because about half of patients were dosed using the off-label recommendation, whereas the prescribing information recommends a more intensive 6-week dosing cycle for certain cancer types.12,13,20 Sorafenib was also often dose-adjusted based on a pharmacokinetic study of sorafenib in renal/hepatic dysfunction, and the RDI likely reflects the off-label prescribing pattern.21
Patients with thyroid cancer were found to have higher RDIs compared with those receiving the same agents for other cancer types. Improved tolerability of MKIs in thyroid cancer may be due to a generally more tolerable disease course. Thyroid cancer is the most common cancer in individuals aged < 40 years, a population that is often more robust with fewer comorbidities. Moreover, the 5-year relative survival rate for thyroid cancer remains > 98%.22 This rate is in contrast to those for other cancer types such as HCC, with a 5-year relative survival rate of only 15%.23
It is challenging to compare the mean and median times on therapy found in this study with those in current literature, as this review included multiple different cancer types for each agent. However, the numbers are generally lower than durations of therapy found across the different disease states and further emphasize the difficulty in tolerating MKIs in the VANTHCS population. Regorafenib had a short duration of time on therapy, which highlights the importance of trials like ReDOS and initiatives such as OCE Project Optimus in helping improve tolerance.7,8,24
Comparing our results with other studies proved challenging because the RDI calculation methods were not specified. Calculating RDIs in this study using method 1, which does not account for holds, resulted in higher RDIs (Appendix 2). Using method 1, all MKIs had RDIs < 85%, except for pazopanib in thyroid cancer (100%) and RCC (87.9%), and sunitinib in GIST (93.6%), thyroid cancer (100%), and neuroendocrine cancer (93.7%). Notably, using method 1 increased the RDI for pazopanib in neuroendocrine cancer from 5.4% to 50.0%. The low RDI was attributed to a single veteran with a long hold duration, which demonstrates the discrepancy that can occur between the 2 methods.

Limitations
The retrospective design, lack of survival outcomes, and difficulty comparing results with other literature were limitations of this study. Because survival outcomes were not evaluated, future research should seek to investigate how RDIs and dose adjustments made among MKIs can affect survival outcomes in real-world populations. This veteran population with cancer often had multiple chronic comorbidities, which may have contributed to difficulty tolerating MKIs and could have impacted results. Disease-related factors may have influenced the poor tolerance of the MKIs and were not specifically accounted for. Adjustment for comorbidities was not possible because of discrepancies and/or incomplete diagnosis codes and Eastern Cooperative Oncology Group performance status scores documented in patient charts. Therefore, we decided not to report these findings due to potential inaccuracies.
CONCLUSIONS
Results of this study demonstrate that oncology MKI agents used at VANTHCS were difficult for patients to tolerate, leading to suboptimal dosing compared with indicated doses established in clinical trials and prescribing information. Clinicians may use these data to help guide clinical decision-making whenever initiating and managing MKI agents in this population. These findings reinforce that MKI agents are often difficult to tolerate in real-world practice, and indicated doses are often not achieved. Further studies should aim to investigate the effect that various RDIs have on overall survival. Further investigation into different dosing schemes for MKIs to improve tolerability and longer-term use may also prove beneficial.
This analysis may help guide clinicians to carefully approach dosing MKI agents in the veteran population. Given the RDI and AEs, more clinicians may consider starting at lower than indicated doses with the goal to titrate up as tolerated. Additionally, the results highlight the importance of considering palliative care consults and ensuring appropriate supportive care agents are preemptively engaged and adjusted as needed. Approaching dosing and titrations cautiously may help reduce the burden of management on the health care system.
- Frequently asked questions. VA National Oncology Program. 2025. Accessed December 15, 2025. https://www.cancer.va.gov/CANCER/faqs.html
- Torez L. Reigniting the cancer moonshot to beat cancer. VA News. April 20, 2023. Accessed April 6, 2026. https://news.va.gov/118378/reigniting-the-cancer-moonshot-to-beat-cancer
- Shah NN, Casella E, Capozzi D, et al. Improving the safety of oral chemotherapy at an academic medical center. J Oncol Pract. 2016;12:e71-e76. doi:10.1200/JOP.2015.007260
- Hussaarts KGAM, Veerman GDM, Jansman FGA, et al. Clinically relevant drug interactions with multikinase inhibitors: a review. Ther Adv Med Oncol. 2019;11:1758835918818347. doi:10.1177/1758835918818347
- Shyam Sunder S, Sharma UC, Pokharel S. Adverse effects of tyrosine kinase inhibitors in cancer therapy: pathophysiology, mechanisms and clinical management. Signal Transduct Target Ther. 2023;8:262. doi:10.1038/s41392-023-01469-6
- Thomson RJ, Moshirfar M, Ronquillo Y. Tyrosine kinase inhibitors. In: StatPearls [Internet]. StatPearls Publishing; updated July 18, 2023. Accessed December 15, 2025. https://www.ncbi.nlm.nih.gov/books/NBK563322/
- Project Optimus. US Food and Drug Administration. Updated December 6, 2024. Accessed December 15, 2025. https://www.fda.gov/about-fda/oncology-center-excellence/project-optimus
- Optimizing the dosage of human prescription drugs and biological products for the treatment of oncologic diseases: Guidance for Industry. Docket number FDA-2022-D-2827. US Food and Drug Administration. August 2024. Accessed December 15, 2025. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/optimizing-dosage-human-prescription-drugs-and-biological-products-treatment-oncologic-diseases
- Schnadig ID, Hutson TE, Chung H, et al. Dosing patterns, toxicity, and outcomes in patients treated with first-line sunitinib for advanced renal cell carcinoma in community-based practices. Clin Genitourin Cancer. 2014;12:413-421. doi:10.1016/j.clgc.2014.06.015
- Motzer RJ, Hutson TE, Tomczak P, et al. Sunitinib versus interferon alfa in metastatic renal-cell carcinoma. N Engl J Med. 2007;356:115-124. doi:10.1056/nejmoa065044
- Hawn C, Bansal D. Relative dose intensity in oncology trials: a discussion of two approaches. PharmaSUG. 2024. Accessed April 6, 2026. https://pharmasug.org/proceedings/2024/ST/PharmaSUG-2024-ST-297.pdf
- George S, Merriam P, Maki RG, et al. Multicenter phase II trial of sunitinib in the treatment of nongastrointestinal stromal tumor sarcomas. J Clin Oncol. 2009;27:3154-3160. doi:10.1200/jco.2008.20.9890
- George S, Blay JY, Casali PG, et al. Clinical evaluation of continuous daily dosing of sunitinib malate in patients with advanced gastrointestinal stromal tumour after imatinib failure. Eur J Cancer. 2009;45:1959-1968. doi:10.1016/j.ejca.2009.02.011
- Denduluri N, Patt DA, Wang Y, et al. Dose delays, dose reductions, and relative dose intensity in patients with cancer who received adjuvant or neoadjuvant chemotherapy in community oncology practices. J Natl Compr Canc Netw. 2015;13:1383-1393. doi:10.6004/jnccn.2015.0166
- Motzer RJ, Penkov K, Haanen J, et al. Avelumab plus axitinib versus sunitinib for advanced renal-cell carcinoma. N Engl J Med. 2019;380:1103-1115. doi:10.1056/nejmoa1816047
- Motzer R, Alekseev B, Rha SY, et al. Lenvatinib plus pembrolizumab or everolimus for advanced renal cell carcinoma. N Engl J Med. 2021;384:1289-1300. doi:10.1056/nejmoa2035716
- Kirino S, Tsuchiya K, Kurosaki M, et al. Relative dose intensity over the first four weeks of lenvatinib therapy is a factor of favorable response and overall survival in patients with unresectable hepatocellular carcinoma. PloS One. 2020;15:e0231828. doi:10.1371/journal.pone.0231828
- Ishihara H, Takagi T, Kondo T, et al. Decreased relative dose intensity during the early phase of treatment impacts the therapeutic efficacy of sunitinib in metastatic renal cell carcinoma. Jpn J Clin Oncol. 2018;48:667-672. doi:10.1093/jjco/hyy078
- Alghamdi MA, Amaro CP, Lee-Ying R, et al. Effect of sorafenib starting dose and dose intensity on survival in patients with hepatocellular carcinoma: results from a Canadian Multicenter Database. Cancer Med. 2020;9:4918-4928. doi:10.1002/cam4.3228
- Motzer RJ, Rini BI, Bukowski RM, et al. Sunitinib in patients with metastatic renal cell carcinoma. JAMA. 2006;295:2516-2524. doi:10.1001/jama.295.21.2516
- Miller AA, Murry DJ, Owzar K, et al. Phase I and pharmacokinetic study of sorafenib in patients with hepatic or renal dysfunction: CALGB 60301. J Clin Oncol. 2009;27:1800-1805. doi:10.1200/jco.2008.20.0931
- Boucai L, Zafereo M, Cabanillas ME. Thyroid cancer: a review. JAMA. 2024;331:425-435. doi:10.1001/jama.2023.26348
- Amin N, Anwar J, Sulaiman A, et al. Hepatocellular carcinoma: a comprehensive review. Diseases. 2025;13:207. doi:10.3390/diseases13070207
- Bekaii-Saab TS, Ou FS, Ahn DH, et al. Regorafenib dose-optimisation in patients with refractory metastatic colorectal cancer (ReDOS): a randomised, multicentre, open-label, phase 2 study. Lancet Oncol. 2019;20:1070-1082. doi:10.1016/s1470-2045(19)30272-4
- Frequently asked questions. VA National Oncology Program. 2025. Accessed December 15, 2025. https://www.cancer.va.gov/CANCER/faqs.html
- Torez L. Reigniting the cancer moonshot to beat cancer. VA News. April 20, 2023. Accessed April 6, 2026. https://news.va.gov/118378/reigniting-the-cancer-moonshot-to-beat-cancer
- Shah NN, Casella E, Capozzi D, et al. Improving the safety of oral chemotherapy at an academic medical center. J Oncol Pract. 2016;12:e71-e76. doi:10.1200/JOP.2015.007260
- Hussaarts KGAM, Veerman GDM, Jansman FGA, et al. Clinically relevant drug interactions with multikinase inhibitors: a review. Ther Adv Med Oncol. 2019;11:1758835918818347. doi:10.1177/1758835918818347
- Shyam Sunder S, Sharma UC, Pokharel S. Adverse effects of tyrosine kinase inhibitors in cancer therapy: pathophysiology, mechanisms and clinical management. Signal Transduct Target Ther. 2023;8:262. doi:10.1038/s41392-023-01469-6
- Thomson RJ, Moshirfar M, Ronquillo Y. Tyrosine kinase inhibitors. In: StatPearls [Internet]. StatPearls Publishing; updated July 18, 2023. Accessed December 15, 2025. https://www.ncbi.nlm.nih.gov/books/NBK563322/
- Project Optimus. US Food and Drug Administration. Updated December 6, 2024. Accessed December 15, 2025. https://www.fda.gov/about-fda/oncology-center-excellence/project-optimus
- Optimizing the dosage of human prescription drugs and biological products for the treatment of oncologic diseases: Guidance for Industry. Docket number FDA-2022-D-2827. US Food and Drug Administration. August 2024. Accessed December 15, 2025. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/optimizing-dosage-human-prescription-drugs-and-biological-products-treatment-oncologic-diseases
- Schnadig ID, Hutson TE, Chung H, et al. Dosing patterns, toxicity, and outcomes in patients treated with first-line sunitinib for advanced renal cell carcinoma in community-based practices. Clin Genitourin Cancer. 2014;12:413-421. doi:10.1016/j.clgc.2014.06.015
- Motzer RJ, Hutson TE, Tomczak P, et al. Sunitinib versus interferon alfa in metastatic renal-cell carcinoma. N Engl J Med. 2007;356:115-124. doi:10.1056/nejmoa065044
- Hawn C, Bansal D. Relative dose intensity in oncology trials: a discussion of two approaches. PharmaSUG. 2024. Accessed April 6, 2026. https://pharmasug.org/proceedings/2024/ST/PharmaSUG-2024-ST-297.pdf
- George S, Merriam P, Maki RG, et al. Multicenter phase II trial of sunitinib in the treatment of nongastrointestinal stromal tumor sarcomas. J Clin Oncol. 2009;27:3154-3160. doi:10.1200/jco.2008.20.9890
- George S, Blay JY, Casali PG, et al. Clinical evaluation of continuous daily dosing of sunitinib malate in patients with advanced gastrointestinal stromal tumour after imatinib failure. Eur J Cancer. 2009;45:1959-1968. doi:10.1016/j.ejca.2009.02.011
- Denduluri N, Patt DA, Wang Y, et al. Dose delays, dose reductions, and relative dose intensity in patients with cancer who received adjuvant or neoadjuvant chemotherapy in community oncology practices. J Natl Compr Canc Netw. 2015;13:1383-1393. doi:10.6004/jnccn.2015.0166
- Motzer RJ, Penkov K, Haanen J, et al. Avelumab plus axitinib versus sunitinib for advanced renal-cell carcinoma. N Engl J Med. 2019;380:1103-1115. doi:10.1056/nejmoa1816047
- Motzer R, Alekseev B, Rha SY, et al. Lenvatinib plus pembrolizumab or everolimus for advanced renal cell carcinoma. N Engl J Med. 2021;384:1289-1300. doi:10.1056/nejmoa2035716
- Kirino S, Tsuchiya K, Kurosaki M, et al. Relative dose intensity over the first four weeks of lenvatinib therapy is a factor of favorable response and overall survival in patients with unresectable hepatocellular carcinoma. PloS One. 2020;15:e0231828. doi:10.1371/journal.pone.0231828
- Ishihara H, Takagi T, Kondo T, et al. Decreased relative dose intensity during the early phase of treatment impacts the therapeutic efficacy of sunitinib in metastatic renal cell carcinoma. Jpn J Clin Oncol. 2018;48:667-672. doi:10.1093/jjco/hyy078
- Alghamdi MA, Amaro CP, Lee-Ying R, et al. Effect of sorafenib starting dose and dose intensity on survival in patients with hepatocellular carcinoma: results from a Canadian Multicenter Database. Cancer Med. 2020;9:4918-4928. doi:10.1002/cam4.3228
- Motzer RJ, Rini BI, Bukowski RM, et al. Sunitinib in patients with metastatic renal cell carcinoma. JAMA. 2006;295:2516-2524. doi:10.1001/jama.295.21.2516
- Miller AA, Murry DJ, Owzar K, et al. Phase I and pharmacokinetic study of sorafenib in patients with hepatic or renal dysfunction: CALGB 60301. J Clin Oncol. 2009;27:1800-1805. doi:10.1200/jco.2008.20.0931
- Boucai L, Zafereo M, Cabanillas ME. Thyroid cancer: a review. JAMA. 2024;331:425-435. doi:10.1001/jama.2023.26348
- Amin N, Anwar J, Sulaiman A, et al. Hepatocellular carcinoma: a comprehensive review. Diseases. 2025;13:207. doi:10.3390/diseases13070207
- Bekaii-Saab TS, Ou FS, Ahn DH, et al. Regorafenib dose-optimisation in patients with refractory metastatic colorectal cancer (ReDOS): a randomised, multicentre, open-label, phase 2 study. Lancet Oncol. 2019;20:1070-1082. doi:10.1016/s1470-2045(19)30272-4
Investigating Real-World Tolerance and Dose Reductions of Oncology Multikinase Inhibitors in a VA Population
Investigating Real-World Tolerance and Dose Reductions of Oncology Multikinase Inhibitors in a VA Population
Potential Tyrosine Kinase Inhibitor Therapy Discontinuation for Patients With Chronic Myeloid Leukemia in a VA Regional Network
Potential Tyrosine Kinase Inhibitor Therapy Discontinuation for Patients With Chronic Myeloid Leukemia in a VA Regional Network
Chronic myeloid leukemia (CML) is a hematologic malignancy resulting from an acquired mutation. The mutation results in a reciprocal translocation between the long arms of chromosomes 9 and 22 and is known as the Philadelphia chromosome (Ph), or Ph-positive (Ph+) when present. The translocation results in the formation of a BCR-ABL fusion oncogene, which leads to continuous cell cycling and proliferation, altered differentiation, and a loss of apoptosis.1,2
Until the 1980s, CML was considered fatal.3 The mainstay of treatment consisted of 2 oral chemotherapeutic agents, busulfan and hydroxyurea. These medications did not prevent blast crisis, a fatal form of leukemia.4,5 The introduction of tyrosine kinase inhibitors (TKIs) transformed CML management and improved 10-year overall survival from about 20% to > 80% by delaying the transition to blast crisis. Now, the risk of death from general health conditions or comorbidities is higher than that of CML.6
TKIs target the root cause of CML through inhibition of the BCR-ABL oncoprotein.1,2 For CML, the goals of treatment include maintaining hematologic, cytogenetic, and molecular remission; preventing progression to accelerated phase or blast crisis; minimizing toxicity; and enabling potential cessation of therapy in carefully selected patients.7,8
Small cohort studies suggest that dose reduction of TKIs in patients who achieve optimal responses may reduce the risk of long-term adverse effects (AEs). However, optimal dose-reduction and minimum effective dose of each agent are unknown.7 The ability to maintain undetectable minimal residual disease or disease detectable at a stable low level after TKI discontinuation has been called treatment-free remission. Studies suggest that about 40% to 50% of patients who have achieved a stable deep molecular response remain in treatment-free remission after stopping first-line treatment.9,10 Of the patients who relapse following TKI discontinuation, 80% relapse within the first 6 months of treatment cessation. Molecular response is regained in almost all patients when treatment is resumed with the same TKI.11
The National Comprehensive Cancer Network (NCCN) recommends considering discontinuation of TKI therapy only outside the setting of a clinical trial and only in patients who consent to discontinuation after a thorough discussion of the potential risks and benefits. The NCCN criteria for patients who may be eligible for discontinuation are listed in Table 1. The Life After Stopping TKIs study reported that 80% of patients with well-controlled chronic phase CML who discontinued TKIs had a clinically meaningful improvement in fatigue. Patients also reported clinically meaningful improvements in depression, diarrhea, sleep disturbance, and pain interference. These symptoms worsened after restarting TKI therapy.12

TKI DISCONTINUATION
Electronic health record data were extracted using structured query language from the US Department of Veterans Affairs (VA) Corporate Data Warehouse (CDW). To be eligible for discontinuation, veterans had to be aged > 18 years, receive oncology care within a Veterans Integrated Services Network (VISN) 21 health care system (HCS) (VA Sierra Nevada HCS, VA Southern Nevada HCS, VA Central California HCS, VA Palo Alto HCS, VA Northern California HCS, and VA San Francisco HCS) or be a veteran referred to a community-based oncology practitioner. Patients had to have a documented diagnosis of chronic phase CML, have an active order for a TKI, be on TKI therapy for ≥ 3 years, and have a stable molecular response (BCR-ABL1 ≤ 0.01% on the International Scale for ≥ 2 years with ≥ 4 tests done ≥ 3 months apart) as of October 1, 2024. Veterans were excluded if they had a history of advanced accelerated phase CML, previous TKI discontinuation trials, nonadherence to the TKI, or if they did not want to consider TKI discontinuation.
This analysis evaluated the potential cost avoidance associated with TKI discontinuation. Cost avoidance was calculated using the average wholesale price of each TKI. Secondary objectives evaluated health outcomes of TKI discontinuation including CML relapse, reported AEs, long-term remission, and TKI withdrawal syndrome. Health outcomes were determined through chart review of AEs and clinic notes documented in the electronic health record during the study time frame.
Baseline information for eligible patients was collected, including age, sex, and race, and chart reviews were completed to evaluate reported AEs associated with therapy. Oncology clinical pharmacy practitioners (CPPs) at each VISN 21 facility were notified of eligible patients to facilitate discussion with oncologists and establish monitoring if therapy was discontinued. Following TKI discontinuation, health outcomes were evaluated, including CML relapse, changes in reported AEs, long-term remission, and TKI withdrawal syndrome. Descriptive statistics were used to analyze the baseline characteristics. Cost avoidance was calculated using the average wholesale price for each TKI. The number of tablets required to reach each patient’s individual dose was taken into consideration when determining the cost avoidance. A dashboard was created using the query from the CDW and was developed in Microsoft Power BI.
Preliminary Results
In FY 2024, VISN 21 had 3819 oncology patients. Twenty-four patients had taken a TKI for ≥ 3 years, 20 had a stable molecular response, and 15 had not previously attempted to discontinue their TKI (Figure 1). Fifteen veterans were eligible for therapy discontinuation for a total potential annual cost avoidance of $1.2 million (Figure 2). Most of the cost avoidance, $935,057 (78%), was attributed to 3 patients on nilotinib. The mean age of the population was 74 years. All patients were male, and 12 (80%) were White. (Table 2). At baseline, 11 patients (73%) were taking imatinib. One patient received oncology care from a community care clinician. All 15 patients decided to remain on therapy.
Abbreviations: CML, chronic myeloid leukemia; TKI, tyrosine kinase inhibitor;
VISN, Veterans Integrated Service Network.
for 15 patients at Veterans Integrated Services Network 21.

DISCUSSION
As a multisite quality improvement initiative, this project raised awareness of TKI therapy discontinuation in select patients with CML. It also sparked collaboration among oncology CPPs and clinicians and stimulated conversations about CML treatment. The development of the TKI discontinuation dashboard provides a population health management tool for CPPs and clinicians to identify eligible patients in the future.
Adherence to TKIs is crucial for disease control and survival in patients with CML. Patients are counseled that poor adherence to therapy may contribute to worsening disease or suboptimal response, the development of resistance, and greater health care costs.13 Therefore, it was a challenge for patients to understand and accept that they could stop TKI therapy after achieving a stable deep molecular response. Discussions with patients about the goal of therapy—suppressing the BCR-ABL oncogene, which they have achieved—could encourage patients to trial therapy discontinuation.
Only small cohort studies have been completed to evaluate the outcomes of therapy discontinuation. Much remains unknown regarding the optimal dose-reduction strategy and the minimum effective dose of each agent. Additionally, understanding the qualities of a good candidate for TKI discontinuation remains a barrier. A similar project was conducted in VISN 17. Five patients were counseled on TKI discontinuation; however, only 1 discontinued TKI therapy. Unfortunately, soon after discontinuing treatment, the patient had to restart therapy. Additional literature will enhance understanding of therapy discontinuation.
An unexpected finding of TKI discontinuation trials has been a reversible phenomenon known as TKI withdrawal syndrome.9 It can occur regardless of the TKI used and results in pruritus and new or worsening musculoskeletal pain within several weeks of TKI discontinuation in about 30% of patients. Symptoms may last several months and may require acetaminophen or nonsteroidal anti-inflammatory drugs for pain control.9,10,14
The potential cost avoidance of $1.2 million is an underestimation because VA contracts allow for greater cost savings. However, that information is confidential and therefore average wholesale price had to be used for this project. Most of the cost avoidance was due to 4 patients who could not tolerate imatinib and used nilotinib, which is more expensive.
Limitations
The small sample size presented some limitations. Of the 3819 oncology patients within VISN 21 in FY 2024, 186 received a TKI and only 15 were eligible for discontinuation. Additionally, challenges emerged when discussing discontinuation with community care clinicians and patients. Community care clinicians were difficult to contact, making it challenging to discuss the project with them. CPPs noted hesitancy among VA clinicians and patients to discontinue a medication for which adherence was continually emphasized.
Conclusions
Discussions about CML TKI discontinuation led to collaboration with the oncology care team and could lead to significant cost avoidance. Barriers to TKI discontinuation included patients’ concern for relapse, risk of discontinuation syndrome, the requirement for close monitoring, and clinician buy-in. Outcome studies are needed to gain a greater understanding of the benefits and risks of therapy discontinuation. In the future, evaluation of possible clinical and biological predictors of successful TKI discontinuation may be beneficial.
- Schiffer CA. BCR-ABL tyrosine kinase inhibitors for chronic myelogenous leukemia. N Engl J Med. 2007;357:258-265. doi:10.1056/NEJMct071828
- Hehlmann R, Hochhaus A, Baccarani M; European LeukemiaNet. Chronic myeloid leukaemia. Lancet. 2007;370:342-350. doi:10.1016/S0140-6736(07)61165-9
- Goldman JM, Melo JV. Chronic myeloid leukemia--advances in biology and new approaches to treatment. N Engl J Med. 2003;349:1451-1464. doi:10.1056/NEJMra020777
- Pasic I, Lipton JH. Current approach to the treatment of chronic myeloid leukaemia. Leuk Res. 2017;55:65-78. doi:10.1016/j.leukres.2017.01.005
- Rao KV, Iannucci A, Jabbour E. Current and future clinical strategies in the management of chronic myeloid leukemia. Pharmacotherapy. 2010;30:77S-101S. doi:10.1592/phco.30.pt2.77S
- Cortes J, Pavlovsky C, Saußele S. Chronic myeloid leukaemia. Lancet. 2021;398:1914-1926. doi:10.1016/S0140-6736(21)01204-6
- National Comprehensive Cancer Network (NCCN). NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®). Chronic myeloid leukemia. Version 1.2026. July 16, 2025. Accessed February 8, 2026. https://www.nccn.org /guidelines/guidelines-detail?id=1427
- Hochhaus A, Baccarani M, Silver RT, et al. European LeukemiaNet 2020 recommendations for treating chronic myeloid leukemia. Leukemia. 2020;34:966-984. doi:10.1038/s41375-020-0776-2
- Saußele S, Richter J, Hochhaus A, Mahon F-X. The concept of treatment-free remission in chronic myeloid leukemia. Leukemia. 2016;30:1638-1647. doi:10.1038/leu.2016.115
- Atallah E, Sweet K. Treatment-free remission: the new goal in CML therapy. Curr Hematol Malig Rep. 2021;16:433-439. doi:10.1007/s11899-021-00653-1
- Hehlmann R. The new ELN recommendations for treating CML. J Clin Med. 2020;9:3671. doi:10.3390/jcm9113671
- Atallah E, Schiffer CA, Radich JP , et al. Assessment of outcomes after stopping tyrosine kinase inhibitors among patients with chronic myeloid leukemia: a non-randomized clinical trial. JAMA Oncol. 2021;7:42-50. doi:10.1001/jamaoncol.2020.5774
- Breccia M, Efficace F, Alimena G. Imatinib treatment in chronic myelogenous leukemia: what have we learned so far? Cancer Lett. 2011;300:115-121. doi:10.1016/j.canlet.2010.10.018
- Berman E. How I treat chronic-phase chronic myelogenous leukemia. Blood. 2022;139:3138-3147. doi:10.1182/blood.2021011722
Chronic myeloid leukemia (CML) is a hematologic malignancy resulting from an acquired mutation. The mutation results in a reciprocal translocation between the long arms of chromosomes 9 and 22 and is known as the Philadelphia chromosome (Ph), or Ph-positive (Ph+) when present. The translocation results in the formation of a BCR-ABL fusion oncogene, which leads to continuous cell cycling and proliferation, altered differentiation, and a loss of apoptosis.1,2
Until the 1980s, CML was considered fatal.3 The mainstay of treatment consisted of 2 oral chemotherapeutic agents, busulfan and hydroxyurea. These medications did not prevent blast crisis, a fatal form of leukemia.4,5 The introduction of tyrosine kinase inhibitors (TKIs) transformed CML management and improved 10-year overall survival from about 20% to > 80% by delaying the transition to blast crisis. Now, the risk of death from general health conditions or comorbidities is higher than that of CML.6
TKIs target the root cause of CML through inhibition of the BCR-ABL oncoprotein.1,2 For CML, the goals of treatment include maintaining hematologic, cytogenetic, and molecular remission; preventing progression to accelerated phase or blast crisis; minimizing toxicity; and enabling potential cessation of therapy in carefully selected patients.7,8
Small cohort studies suggest that dose reduction of TKIs in patients who achieve optimal responses may reduce the risk of long-term adverse effects (AEs). However, optimal dose-reduction and minimum effective dose of each agent are unknown.7 The ability to maintain undetectable minimal residual disease or disease detectable at a stable low level after TKI discontinuation has been called treatment-free remission. Studies suggest that about 40% to 50% of patients who have achieved a stable deep molecular response remain in treatment-free remission after stopping first-line treatment.9,10 Of the patients who relapse following TKI discontinuation, 80% relapse within the first 6 months of treatment cessation. Molecular response is regained in almost all patients when treatment is resumed with the same TKI.11
The National Comprehensive Cancer Network (NCCN) recommends considering discontinuation of TKI therapy only outside the setting of a clinical trial and only in patients who consent to discontinuation after a thorough discussion of the potential risks and benefits. The NCCN criteria for patients who may be eligible for discontinuation are listed in Table 1. The Life After Stopping TKIs study reported that 80% of patients with well-controlled chronic phase CML who discontinued TKIs had a clinically meaningful improvement in fatigue. Patients also reported clinically meaningful improvements in depression, diarrhea, sleep disturbance, and pain interference. These symptoms worsened after restarting TKI therapy.12

TKI DISCONTINUATION
Electronic health record data were extracted using structured query language from the US Department of Veterans Affairs (VA) Corporate Data Warehouse (CDW). To be eligible for discontinuation, veterans had to be aged > 18 years, receive oncology care within a Veterans Integrated Services Network (VISN) 21 health care system (HCS) (VA Sierra Nevada HCS, VA Southern Nevada HCS, VA Central California HCS, VA Palo Alto HCS, VA Northern California HCS, and VA San Francisco HCS) or be a veteran referred to a community-based oncology practitioner. Patients had to have a documented diagnosis of chronic phase CML, have an active order for a TKI, be on TKI therapy for ≥ 3 years, and have a stable molecular response (BCR-ABL1 ≤ 0.01% on the International Scale for ≥ 2 years with ≥ 4 tests done ≥ 3 months apart) as of October 1, 2024. Veterans were excluded if they had a history of advanced accelerated phase CML, previous TKI discontinuation trials, nonadherence to the TKI, or if they did not want to consider TKI discontinuation.
This analysis evaluated the potential cost avoidance associated with TKI discontinuation. Cost avoidance was calculated using the average wholesale price of each TKI. Secondary objectives evaluated health outcomes of TKI discontinuation including CML relapse, reported AEs, long-term remission, and TKI withdrawal syndrome. Health outcomes were determined through chart review of AEs and clinic notes documented in the electronic health record during the study time frame.
Baseline information for eligible patients was collected, including age, sex, and race, and chart reviews were completed to evaluate reported AEs associated with therapy. Oncology clinical pharmacy practitioners (CPPs) at each VISN 21 facility were notified of eligible patients to facilitate discussion with oncologists and establish monitoring if therapy was discontinued. Following TKI discontinuation, health outcomes were evaluated, including CML relapse, changes in reported AEs, long-term remission, and TKI withdrawal syndrome. Descriptive statistics were used to analyze the baseline characteristics. Cost avoidance was calculated using the average wholesale price for each TKI. The number of tablets required to reach each patient’s individual dose was taken into consideration when determining the cost avoidance. A dashboard was created using the query from the CDW and was developed in Microsoft Power BI.
Preliminary Results
In FY 2024, VISN 21 had 3819 oncology patients. Twenty-four patients had taken a TKI for ≥ 3 years, 20 had a stable molecular response, and 15 had not previously attempted to discontinue their TKI (Figure 1). Fifteen veterans were eligible for therapy discontinuation for a total potential annual cost avoidance of $1.2 million (Figure 2). Most of the cost avoidance, $935,057 (78%), was attributed to 3 patients on nilotinib. The mean age of the population was 74 years. All patients were male, and 12 (80%) were White. (Table 2). At baseline, 11 patients (73%) were taking imatinib. One patient received oncology care from a community care clinician. All 15 patients decided to remain on therapy.
Abbreviations: CML, chronic myeloid leukemia; TKI, tyrosine kinase inhibitor;
VISN, Veterans Integrated Service Network.
for 15 patients at Veterans Integrated Services Network 21.

DISCUSSION
As a multisite quality improvement initiative, this project raised awareness of TKI therapy discontinuation in select patients with CML. It also sparked collaboration among oncology CPPs and clinicians and stimulated conversations about CML treatment. The development of the TKI discontinuation dashboard provides a population health management tool for CPPs and clinicians to identify eligible patients in the future.
Adherence to TKIs is crucial for disease control and survival in patients with CML. Patients are counseled that poor adherence to therapy may contribute to worsening disease or suboptimal response, the development of resistance, and greater health care costs.13 Therefore, it was a challenge for patients to understand and accept that they could stop TKI therapy after achieving a stable deep molecular response. Discussions with patients about the goal of therapy—suppressing the BCR-ABL oncogene, which they have achieved—could encourage patients to trial therapy discontinuation.
Only small cohort studies have been completed to evaluate the outcomes of therapy discontinuation. Much remains unknown regarding the optimal dose-reduction strategy and the minimum effective dose of each agent. Additionally, understanding the qualities of a good candidate for TKI discontinuation remains a barrier. A similar project was conducted in VISN 17. Five patients were counseled on TKI discontinuation; however, only 1 discontinued TKI therapy. Unfortunately, soon after discontinuing treatment, the patient had to restart therapy. Additional literature will enhance understanding of therapy discontinuation.
An unexpected finding of TKI discontinuation trials has been a reversible phenomenon known as TKI withdrawal syndrome.9 It can occur regardless of the TKI used and results in pruritus and new or worsening musculoskeletal pain within several weeks of TKI discontinuation in about 30% of patients. Symptoms may last several months and may require acetaminophen or nonsteroidal anti-inflammatory drugs for pain control.9,10,14
The potential cost avoidance of $1.2 million is an underestimation because VA contracts allow for greater cost savings. However, that information is confidential and therefore average wholesale price had to be used for this project. Most of the cost avoidance was due to 4 patients who could not tolerate imatinib and used nilotinib, which is more expensive.
Limitations
The small sample size presented some limitations. Of the 3819 oncology patients within VISN 21 in FY 2024, 186 received a TKI and only 15 were eligible for discontinuation. Additionally, challenges emerged when discussing discontinuation with community care clinicians and patients. Community care clinicians were difficult to contact, making it challenging to discuss the project with them. CPPs noted hesitancy among VA clinicians and patients to discontinue a medication for which adherence was continually emphasized.
Conclusions
Discussions about CML TKI discontinuation led to collaboration with the oncology care team and could lead to significant cost avoidance. Barriers to TKI discontinuation included patients’ concern for relapse, risk of discontinuation syndrome, the requirement for close monitoring, and clinician buy-in. Outcome studies are needed to gain a greater understanding of the benefits and risks of therapy discontinuation. In the future, evaluation of possible clinical and biological predictors of successful TKI discontinuation may be beneficial.
Chronic myeloid leukemia (CML) is a hematologic malignancy resulting from an acquired mutation. The mutation results in a reciprocal translocation between the long arms of chromosomes 9 and 22 and is known as the Philadelphia chromosome (Ph), or Ph-positive (Ph+) when present. The translocation results in the formation of a BCR-ABL fusion oncogene, which leads to continuous cell cycling and proliferation, altered differentiation, and a loss of apoptosis.1,2
Until the 1980s, CML was considered fatal.3 The mainstay of treatment consisted of 2 oral chemotherapeutic agents, busulfan and hydroxyurea. These medications did not prevent blast crisis, a fatal form of leukemia.4,5 The introduction of tyrosine kinase inhibitors (TKIs) transformed CML management and improved 10-year overall survival from about 20% to > 80% by delaying the transition to blast crisis. Now, the risk of death from general health conditions or comorbidities is higher than that of CML.6
TKIs target the root cause of CML through inhibition of the BCR-ABL oncoprotein.1,2 For CML, the goals of treatment include maintaining hematologic, cytogenetic, and molecular remission; preventing progression to accelerated phase or blast crisis; minimizing toxicity; and enabling potential cessation of therapy in carefully selected patients.7,8
Small cohort studies suggest that dose reduction of TKIs in patients who achieve optimal responses may reduce the risk of long-term adverse effects (AEs). However, optimal dose-reduction and minimum effective dose of each agent are unknown.7 The ability to maintain undetectable minimal residual disease or disease detectable at a stable low level after TKI discontinuation has been called treatment-free remission. Studies suggest that about 40% to 50% of patients who have achieved a stable deep molecular response remain in treatment-free remission after stopping first-line treatment.9,10 Of the patients who relapse following TKI discontinuation, 80% relapse within the first 6 months of treatment cessation. Molecular response is regained in almost all patients when treatment is resumed with the same TKI.11
The National Comprehensive Cancer Network (NCCN) recommends considering discontinuation of TKI therapy only outside the setting of a clinical trial and only in patients who consent to discontinuation after a thorough discussion of the potential risks and benefits. The NCCN criteria for patients who may be eligible for discontinuation are listed in Table 1. The Life After Stopping TKIs study reported that 80% of patients with well-controlled chronic phase CML who discontinued TKIs had a clinically meaningful improvement in fatigue. Patients also reported clinically meaningful improvements in depression, diarrhea, sleep disturbance, and pain interference. These symptoms worsened after restarting TKI therapy.12

TKI DISCONTINUATION
Electronic health record data were extracted using structured query language from the US Department of Veterans Affairs (VA) Corporate Data Warehouse (CDW). To be eligible for discontinuation, veterans had to be aged > 18 years, receive oncology care within a Veterans Integrated Services Network (VISN) 21 health care system (HCS) (VA Sierra Nevada HCS, VA Southern Nevada HCS, VA Central California HCS, VA Palo Alto HCS, VA Northern California HCS, and VA San Francisco HCS) or be a veteran referred to a community-based oncology practitioner. Patients had to have a documented diagnosis of chronic phase CML, have an active order for a TKI, be on TKI therapy for ≥ 3 years, and have a stable molecular response (BCR-ABL1 ≤ 0.01% on the International Scale for ≥ 2 years with ≥ 4 tests done ≥ 3 months apart) as of October 1, 2024. Veterans were excluded if they had a history of advanced accelerated phase CML, previous TKI discontinuation trials, nonadherence to the TKI, or if they did not want to consider TKI discontinuation.
This analysis evaluated the potential cost avoidance associated with TKI discontinuation. Cost avoidance was calculated using the average wholesale price of each TKI. Secondary objectives evaluated health outcomes of TKI discontinuation including CML relapse, reported AEs, long-term remission, and TKI withdrawal syndrome. Health outcomes were determined through chart review of AEs and clinic notes documented in the electronic health record during the study time frame.
Baseline information for eligible patients was collected, including age, sex, and race, and chart reviews were completed to evaluate reported AEs associated with therapy. Oncology clinical pharmacy practitioners (CPPs) at each VISN 21 facility were notified of eligible patients to facilitate discussion with oncologists and establish monitoring if therapy was discontinued. Following TKI discontinuation, health outcomes were evaluated, including CML relapse, changes in reported AEs, long-term remission, and TKI withdrawal syndrome. Descriptive statistics were used to analyze the baseline characteristics. Cost avoidance was calculated using the average wholesale price for each TKI. The number of tablets required to reach each patient’s individual dose was taken into consideration when determining the cost avoidance. A dashboard was created using the query from the CDW and was developed in Microsoft Power BI.
Preliminary Results
In FY 2024, VISN 21 had 3819 oncology patients. Twenty-four patients had taken a TKI for ≥ 3 years, 20 had a stable molecular response, and 15 had not previously attempted to discontinue their TKI (Figure 1). Fifteen veterans were eligible for therapy discontinuation for a total potential annual cost avoidance of $1.2 million (Figure 2). Most of the cost avoidance, $935,057 (78%), was attributed to 3 patients on nilotinib. The mean age of the population was 74 years. All patients were male, and 12 (80%) were White. (Table 2). At baseline, 11 patients (73%) were taking imatinib. One patient received oncology care from a community care clinician. All 15 patients decided to remain on therapy.
Abbreviations: CML, chronic myeloid leukemia; TKI, tyrosine kinase inhibitor;
VISN, Veterans Integrated Service Network.
for 15 patients at Veterans Integrated Services Network 21.

DISCUSSION
As a multisite quality improvement initiative, this project raised awareness of TKI therapy discontinuation in select patients with CML. It also sparked collaboration among oncology CPPs and clinicians and stimulated conversations about CML treatment. The development of the TKI discontinuation dashboard provides a population health management tool for CPPs and clinicians to identify eligible patients in the future.
Adherence to TKIs is crucial for disease control and survival in patients with CML. Patients are counseled that poor adherence to therapy may contribute to worsening disease or suboptimal response, the development of resistance, and greater health care costs.13 Therefore, it was a challenge for patients to understand and accept that they could stop TKI therapy after achieving a stable deep molecular response. Discussions with patients about the goal of therapy—suppressing the BCR-ABL oncogene, which they have achieved—could encourage patients to trial therapy discontinuation.
Only small cohort studies have been completed to evaluate the outcomes of therapy discontinuation. Much remains unknown regarding the optimal dose-reduction strategy and the minimum effective dose of each agent. Additionally, understanding the qualities of a good candidate for TKI discontinuation remains a barrier. A similar project was conducted in VISN 17. Five patients were counseled on TKI discontinuation; however, only 1 discontinued TKI therapy. Unfortunately, soon after discontinuing treatment, the patient had to restart therapy. Additional literature will enhance understanding of therapy discontinuation.
An unexpected finding of TKI discontinuation trials has been a reversible phenomenon known as TKI withdrawal syndrome.9 It can occur regardless of the TKI used and results in pruritus and new or worsening musculoskeletal pain within several weeks of TKI discontinuation in about 30% of patients. Symptoms may last several months and may require acetaminophen or nonsteroidal anti-inflammatory drugs for pain control.9,10,14
The potential cost avoidance of $1.2 million is an underestimation because VA contracts allow for greater cost savings. However, that information is confidential and therefore average wholesale price had to be used for this project. Most of the cost avoidance was due to 4 patients who could not tolerate imatinib and used nilotinib, which is more expensive.
Limitations
The small sample size presented some limitations. Of the 3819 oncology patients within VISN 21 in FY 2024, 186 received a TKI and only 15 were eligible for discontinuation. Additionally, challenges emerged when discussing discontinuation with community care clinicians and patients. Community care clinicians were difficult to contact, making it challenging to discuss the project with them. CPPs noted hesitancy among VA clinicians and patients to discontinue a medication for which adherence was continually emphasized.
Conclusions
Discussions about CML TKI discontinuation led to collaboration with the oncology care team and could lead to significant cost avoidance. Barriers to TKI discontinuation included patients’ concern for relapse, risk of discontinuation syndrome, the requirement for close monitoring, and clinician buy-in. Outcome studies are needed to gain a greater understanding of the benefits and risks of therapy discontinuation. In the future, evaluation of possible clinical and biological predictors of successful TKI discontinuation may be beneficial.
- Schiffer CA. BCR-ABL tyrosine kinase inhibitors for chronic myelogenous leukemia. N Engl J Med. 2007;357:258-265. doi:10.1056/NEJMct071828
- Hehlmann R, Hochhaus A, Baccarani M; European LeukemiaNet. Chronic myeloid leukaemia. Lancet. 2007;370:342-350. doi:10.1016/S0140-6736(07)61165-9
- Goldman JM, Melo JV. Chronic myeloid leukemia--advances in biology and new approaches to treatment. N Engl J Med. 2003;349:1451-1464. doi:10.1056/NEJMra020777
- Pasic I, Lipton JH. Current approach to the treatment of chronic myeloid leukaemia. Leuk Res. 2017;55:65-78. doi:10.1016/j.leukres.2017.01.005
- Rao KV, Iannucci A, Jabbour E. Current and future clinical strategies in the management of chronic myeloid leukemia. Pharmacotherapy. 2010;30:77S-101S. doi:10.1592/phco.30.pt2.77S
- Cortes J, Pavlovsky C, Saußele S. Chronic myeloid leukaemia. Lancet. 2021;398:1914-1926. doi:10.1016/S0140-6736(21)01204-6
- National Comprehensive Cancer Network (NCCN). NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®). Chronic myeloid leukemia. Version 1.2026. July 16, 2025. Accessed February 8, 2026. https://www.nccn.org /guidelines/guidelines-detail?id=1427
- Hochhaus A, Baccarani M, Silver RT, et al. European LeukemiaNet 2020 recommendations for treating chronic myeloid leukemia. Leukemia. 2020;34:966-984. doi:10.1038/s41375-020-0776-2
- Saußele S, Richter J, Hochhaus A, Mahon F-X. The concept of treatment-free remission in chronic myeloid leukemia. Leukemia. 2016;30:1638-1647. doi:10.1038/leu.2016.115
- Atallah E, Sweet K. Treatment-free remission: the new goal in CML therapy. Curr Hematol Malig Rep. 2021;16:433-439. doi:10.1007/s11899-021-00653-1
- Hehlmann R. The new ELN recommendations for treating CML. J Clin Med. 2020;9:3671. doi:10.3390/jcm9113671
- Atallah E, Schiffer CA, Radich JP , et al. Assessment of outcomes after stopping tyrosine kinase inhibitors among patients with chronic myeloid leukemia: a non-randomized clinical trial. JAMA Oncol. 2021;7:42-50. doi:10.1001/jamaoncol.2020.5774
- Breccia M, Efficace F, Alimena G. Imatinib treatment in chronic myelogenous leukemia: what have we learned so far? Cancer Lett. 2011;300:115-121. doi:10.1016/j.canlet.2010.10.018
- Berman E. How I treat chronic-phase chronic myelogenous leukemia. Blood. 2022;139:3138-3147. doi:10.1182/blood.2021011722
- Schiffer CA. BCR-ABL tyrosine kinase inhibitors for chronic myelogenous leukemia. N Engl J Med. 2007;357:258-265. doi:10.1056/NEJMct071828
- Hehlmann R, Hochhaus A, Baccarani M; European LeukemiaNet. Chronic myeloid leukaemia. Lancet. 2007;370:342-350. doi:10.1016/S0140-6736(07)61165-9
- Goldman JM, Melo JV. Chronic myeloid leukemia--advances in biology and new approaches to treatment. N Engl J Med. 2003;349:1451-1464. doi:10.1056/NEJMra020777
- Pasic I, Lipton JH. Current approach to the treatment of chronic myeloid leukaemia. Leuk Res. 2017;55:65-78. doi:10.1016/j.leukres.2017.01.005
- Rao KV, Iannucci A, Jabbour E. Current and future clinical strategies in the management of chronic myeloid leukemia. Pharmacotherapy. 2010;30:77S-101S. doi:10.1592/phco.30.pt2.77S
- Cortes J, Pavlovsky C, Saußele S. Chronic myeloid leukaemia. Lancet. 2021;398:1914-1926. doi:10.1016/S0140-6736(21)01204-6
- National Comprehensive Cancer Network (NCCN). NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®). Chronic myeloid leukemia. Version 1.2026. July 16, 2025. Accessed February 8, 2026. https://www.nccn.org /guidelines/guidelines-detail?id=1427
- Hochhaus A, Baccarani M, Silver RT, et al. European LeukemiaNet 2020 recommendations for treating chronic myeloid leukemia. Leukemia. 2020;34:966-984. doi:10.1038/s41375-020-0776-2
- Saußele S, Richter J, Hochhaus A, Mahon F-X. The concept of treatment-free remission in chronic myeloid leukemia. Leukemia. 2016;30:1638-1647. doi:10.1038/leu.2016.115
- Atallah E, Sweet K. Treatment-free remission: the new goal in CML therapy. Curr Hematol Malig Rep. 2021;16:433-439. doi:10.1007/s11899-021-00653-1
- Hehlmann R. The new ELN recommendations for treating CML. J Clin Med. 2020;9:3671. doi:10.3390/jcm9113671
- Atallah E, Schiffer CA, Radich JP , et al. Assessment of outcomes after stopping tyrosine kinase inhibitors among patients with chronic myeloid leukemia: a non-randomized clinical trial. JAMA Oncol. 2021;7:42-50. doi:10.1001/jamaoncol.2020.5774
- Breccia M, Efficace F, Alimena G. Imatinib treatment in chronic myelogenous leukemia: what have we learned so far? Cancer Lett. 2011;300:115-121. doi:10.1016/j.canlet.2010.10.018
- Berman E. How I treat chronic-phase chronic myelogenous leukemia. Blood. 2022;139:3138-3147. doi:10.1182/blood.2021011722
Potential Tyrosine Kinase Inhibitor Therapy Discontinuation for Patients With Chronic Myeloid Leukemia in a VA Regional Network
Potential Tyrosine Kinase Inhibitor Therapy Discontinuation for Patients With Chronic Myeloid Leukemia in a VA Regional Network
Military Women Survive Ovarian Cancer at Higher Rates
Military Women Survive Ovarian Cancer at Higher Rates
Women with epithelial ovarian cancer treated in the US Department of Defense (DoD) universal health care system demonstrate better 5-year survival compared with similar patients from the national population. The survival advantage persists across multiple age groups and disease stages, with particularly notable improvements in patients aged 35-49 years and those with stage III disease.
METHODOLOGY:
- Researchers compared 1504 patients with invasive stage I-IV epithelial ovarian carcinoma from the Automated Center Tumor Registry (ACTUR) for the DoD with 6016 matched patients from the 18-region Surveillance, Epidemiology, and End Results (SEER) program between 1987 and 2013.
- Patients from ACTUR were matched in a 1:4 ratio with SEER patients stratified for age, race, year of diagnosis, and histology, including serous carcinoma, clear cell carcinoma, mucinous carcinoma, and endometrioid carcinoma with adenocarcinoma subtypes.
- Five-year overall survival was evaluated using the Kaplan-Meier method and compared using log-rank test, with median follow-up time of 46 months in ACTUR and 44 months in SEER.
- Adjusted hazard ratio (AHR) and 95% CI for all-cause mortality were estimated from multivariable Cox proportional regression modeling controlling for age, race, year of diagnosis, region of diagnosis, stage, histology, and grade.
TAKEAWAY:
- Overall survival differs between registries: 5-year survival of 53.2% in ACTUR vs 47.7% in matched SEER cohort (log-rank P = .001).
- In the primary adjusted model, ACTUR is associated with a lower risk for all-cause mortality vs SEER (AHR, 0.83; 95% CI, 0.76-0.91; P < .0001).
- Subset results retain lower adjusted risk for death for ACTUR vs SEER among ages 35-49 years (AHR, 0.66; 95% CI, 0.52-0.83; P = .0005), ages ≥ 65 years (AHR, 0.82; 95% CI, 0.70-0.96; P = .016), and stage III cancer (AHR, 0.79; 95% CI, 0.69-0.91; P = .0015).
- Histology-stratified findings show lower adjusted risk for death in ACTUR vs SEER for clear cell carcinoma (AHR, 0.63; 95% CI, 0.43-0.93; P =.02) and for endometrioid and other adenocarcinomas (AHR, 0.68; 95% CI, 0.56-0.81; P < .0001).
IN PRACTICE:
"This study is envisioned to be a stepping stone to further investigations of survival and other cancer health outcomes starting with patients diagnosed between 2014 and 2024 with epithelial carcinoma of the ovary, fallopian tube, or primary peritoneum in the DoD Healthcare System versus the national population or other Healthcare Systems,” wrote the authors of the study. “Dedicated funding and support in the [Military Health System] are needed to invest in infrastructure, technology, security, education, and research.”
SOURCE:
The study was led by Kathleen M. Darcy, PhD, and Christopher M. Tarney, MD, from the Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery & Obstetrics, Uniformed Services University, Walter Reed National Military Medical Center in Bethesda, Maryland. It was published online in Military Medicine.
LIMITATIONS:
The retrospective cohort study design limits causal inference. Although groups were balanced by age, race, year, and region of diagnosis, other demographic factors and socioeconomic variables such as patient comorbidities, educational attainment, household income, and health insurance status were not available and may have affected results. The databases fundamentally differ in how data are acquired, with ACTUR following hospital-based Facility Oncology Registry Data Standards and SEER being a national population-based registry, potentially affecting data quality, consistency, and reliability of survival outcome comparisons. The inclusion of patients diagnosed only through 2013 represents a limitation as it does not allow for contemporary evaluation of survival outcomes, particularly given advances over the past decade including maximal cytoreductive effort to no residual disease, increased adoption of neoadjuvant chemotherapy, and introduction of targeted maintenance agents. The study could not incorporate details regarding residual disease status or control for specifics regarding surgical and medical management, including primary vs interval debulking surgery or the type and timing of agents utilized in first-line, maintenance, and recurrent disease settings. Data regarding circulating biomarkers including CA125, molecular subtypes or alterations, and stratification by homologous recombination deficiency vs proficiency status were not available. Epithelial carcinomas of the fallopian tube and primary peritoneum were excluded from this study, which now are commonly incorporated with ovarian carcinomas. Results may not be generalizable to other populations given the unique characteristics of the Military Health System beneficiary population.
DISCLOSURES:
This research received funding from the Uniformed Services University from the Defense Health Program to the Henry M. Jackson Foundation for the Advancement of Military Medicine Inc., including award HU0001-18-2-0032 to the Murtha Cancer Center Research Program and awards HU0001-19-2-0031 and HU0001-24-2-0047 to the Gynecologic Cancer Center of Excellence Program. All coauthors disclosed 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.
Women with epithelial ovarian cancer treated in the US Department of Defense (DoD) universal health care system demonstrate better 5-year survival compared with similar patients from the national population. The survival advantage persists across multiple age groups and disease stages, with particularly notable improvements in patients aged 35-49 years and those with stage III disease.
METHODOLOGY:
- Researchers compared 1504 patients with invasive stage I-IV epithelial ovarian carcinoma from the Automated Center Tumor Registry (ACTUR) for the DoD with 6016 matched patients from the 18-region Surveillance, Epidemiology, and End Results (SEER) program between 1987 and 2013.
- Patients from ACTUR were matched in a 1:4 ratio with SEER patients stratified for age, race, year of diagnosis, and histology, including serous carcinoma, clear cell carcinoma, mucinous carcinoma, and endometrioid carcinoma with adenocarcinoma subtypes.
- Five-year overall survival was evaluated using the Kaplan-Meier method and compared using log-rank test, with median follow-up time of 46 months in ACTUR and 44 months in SEER.
- Adjusted hazard ratio (AHR) and 95% CI for all-cause mortality were estimated from multivariable Cox proportional regression modeling controlling for age, race, year of diagnosis, region of diagnosis, stage, histology, and grade.
TAKEAWAY:
- Overall survival differs between registries: 5-year survival of 53.2% in ACTUR vs 47.7% in matched SEER cohort (log-rank P = .001).
- In the primary adjusted model, ACTUR is associated with a lower risk for all-cause mortality vs SEER (AHR, 0.83; 95% CI, 0.76-0.91; P < .0001).
- Subset results retain lower adjusted risk for death for ACTUR vs SEER among ages 35-49 years (AHR, 0.66; 95% CI, 0.52-0.83; P = .0005), ages ≥ 65 years (AHR, 0.82; 95% CI, 0.70-0.96; P = .016), and stage III cancer (AHR, 0.79; 95% CI, 0.69-0.91; P = .0015).
- Histology-stratified findings show lower adjusted risk for death in ACTUR vs SEER for clear cell carcinoma (AHR, 0.63; 95% CI, 0.43-0.93; P =.02) and for endometrioid and other adenocarcinomas (AHR, 0.68; 95% CI, 0.56-0.81; P < .0001).
IN PRACTICE:
"This study is envisioned to be a stepping stone to further investigations of survival and other cancer health outcomes starting with patients diagnosed between 2014 and 2024 with epithelial carcinoma of the ovary, fallopian tube, or primary peritoneum in the DoD Healthcare System versus the national population or other Healthcare Systems,” wrote the authors of the study. “Dedicated funding and support in the [Military Health System] are needed to invest in infrastructure, technology, security, education, and research.”
SOURCE:
The study was led by Kathleen M. Darcy, PhD, and Christopher M. Tarney, MD, from the Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery & Obstetrics, Uniformed Services University, Walter Reed National Military Medical Center in Bethesda, Maryland. It was published online in Military Medicine.
LIMITATIONS:
The retrospective cohort study design limits causal inference. Although groups were balanced by age, race, year, and region of diagnosis, other demographic factors and socioeconomic variables such as patient comorbidities, educational attainment, household income, and health insurance status were not available and may have affected results. The databases fundamentally differ in how data are acquired, with ACTUR following hospital-based Facility Oncology Registry Data Standards and SEER being a national population-based registry, potentially affecting data quality, consistency, and reliability of survival outcome comparisons. The inclusion of patients diagnosed only through 2013 represents a limitation as it does not allow for contemporary evaluation of survival outcomes, particularly given advances over the past decade including maximal cytoreductive effort to no residual disease, increased adoption of neoadjuvant chemotherapy, and introduction of targeted maintenance agents. The study could not incorporate details regarding residual disease status or control for specifics regarding surgical and medical management, including primary vs interval debulking surgery or the type and timing of agents utilized in first-line, maintenance, and recurrent disease settings. Data regarding circulating biomarkers including CA125, molecular subtypes or alterations, and stratification by homologous recombination deficiency vs proficiency status were not available. Epithelial carcinomas of the fallopian tube and primary peritoneum were excluded from this study, which now are commonly incorporated with ovarian carcinomas. Results may not be generalizable to other populations given the unique characteristics of the Military Health System beneficiary population.
DISCLOSURES:
This research received funding from the Uniformed Services University from the Defense Health Program to the Henry M. Jackson Foundation for the Advancement of Military Medicine Inc., including award HU0001-18-2-0032 to the Murtha Cancer Center Research Program and awards HU0001-19-2-0031 and HU0001-24-2-0047 to the Gynecologic Cancer Center of Excellence Program. All coauthors disclosed 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.
Women with epithelial ovarian cancer treated in the US Department of Defense (DoD) universal health care system demonstrate better 5-year survival compared with similar patients from the national population. The survival advantage persists across multiple age groups and disease stages, with particularly notable improvements in patients aged 35-49 years and those with stage III disease.
METHODOLOGY:
- Researchers compared 1504 patients with invasive stage I-IV epithelial ovarian carcinoma from the Automated Center Tumor Registry (ACTUR) for the DoD with 6016 matched patients from the 18-region Surveillance, Epidemiology, and End Results (SEER) program between 1987 and 2013.
- Patients from ACTUR were matched in a 1:4 ratio with SEER patients stratified for age, race, year of diagnosis, and histology, including serous carcinoma, clear cell carcinoma, mucinous carcinoma, and endometrioid carcinoma with adenocarcinoma subtypes.
- Five-year overall survival was evaluated using the Kaplan-Meier method and compared using log-rank test, with median follow-up time of 46 months in ACTUR and 44 months in SEER.
- Adjusted hazard ratio (AHR) and 95% CI for all-cause mortality were estimated from multivariable Cox proportional regression modeling controlling for age, race, year of diagnosis, region of diagnosis, stage, histology, and grade.
TAKEAWAY:
- Overall survival differs between registries: 5-year survival of 53.2% in ACTUR vs 47.7% in matched SEER cohort (log-rank P = .001).
- In the primary adjusted model, ACTUR is associated with a lower risk for all-cause mortality vs SEER (AHR, 0.83; 95% CI, 0.76-0.91; P < .0001).
- Subset results retain lower adjusted risk for death for ACTUR vs SEER among ages 35-49 years (AHR, 0.66; 95% CI, 0.52-0.83; P = .0005), ages ≥ 65 years (AHR, 0.82; 95% CI, 0.70-0.96; P = .016), and stage III cancer (AHR, 0.79; 95% CI, 0.69-0.91; P = .0015).
- Histology-stratified findings show lower adjusted risk for death in ACTUR vs SEER for clear cell carcinoma (AHR, 0.63; 95% CI, 0.43-0.93; P =.02) and for endometrioid and other adenocarcinomas (AHR, 0.68; 95% CI, 0.56-0.81; P < .0001).
IN PRACTICE:
"This study is envisioned to be a stepping stone to further investigations of survival and other cancer health outcomes starting with patients diagnosed between 2014 and 2024 with epithelial carcinoma of the ovary, fallopian tube, or primary peritoneum in the DoD Healthcare System versus the national population or other Healthcare Systems,” wrote the authors of the study. “Dedicated funding and support in the [Military Health System] are needed to invest in infrastructure, technology, security, education, and research.”
SOURCE:
The study was led by Kathleen M. Darcy, PhD, and Christopher M. Tarney, MD, from the Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery & Obstetrics, Uniformed Services University, Walter Reed National Military Medical Center in Bethesda, Maryland. It was published online in Military Medicine.
LIMITATIONS:
The retrospective cohort study design limits causal inference. Although groups were balanced by age, race, year, and region of diagnosis, other demographic factors and socioeconomic variables such as patient comorbidities, educational attainment, household income, and health insurance status were not available and may have affected results. The databases fundamentally differ in how data are acquired, with ACTUR following hospital-based Facility Oncology Registry Data Standards and SEER being a national population-based registry, potentially affecting data quality, consistency, and reliability of survival outcome comparisons. The inclusion of patients diagnosed only through 2013 represents a limitation as it does not allow for contemporary evaluation of survival outcomes, particularly given advances over the past decade including maximal cytoreductive effort to no residual disease, increased adoption of neoadjuvant chemotherapy, and introduction of targeted maintenance agents. The study could not incorporate details regarding residual disease status or control for specifics regarding surgical and medical management, including primary vs interval debulking surgery or the type and timing of agents utilized in first-line, maintenance, and recurrent disease settings. Data regarding circulating biomarkers including CA125, molecular subtypes or alterations, and stratification by homologous recombination deficiency vs proficiency status were not available. Epithelial carcinomas of the fallopian tube and primary peritoneum were excluded from this study, which now are commonly incorporated with ovarian carcinomas. Results may not be generalizable to other populations given the unique characteristics of the Military Health System beneficiary population.
DISCLOSURES:
This research received funding from the Uniformed Services University from the Defense Health Program to the Henry M. Jackson Foundation for the Advancement of Military Medicine Inc., including award HU0001-18-2-0032 to the Murtha Cancer Center Research Program and awards HU0001-19-2-0031 and HU0001-24-2-0047 to the Gynecologic Cancer Center of Excellence Program. All coauthors disclosed 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.
Military Women Survive Ovarian Cancer at Higher Rates
Military Women Survive Ovarian Cancer at Higher Rates
No Survival Gain With Adjuvant Therapy in Stage III Melanoma
Offering adjuvant therapy to patients with stage III melanoma offers no melanoma-specific or overall survival benefit, reveals extended follow-up from the first population-based national study to estimate the impact of the treatment.
Hildur Helgadottir, MD, PhD, presented the new findings at the 22nd European Association of Dermato-Oncology (EADO) Congress 2026 on April 24 and described the lead-up to the latest update on the study.
To investigate the impact of adjuvant treatment in patients with stage III melanoma, researchers initially conducted a study in which they used the Swedish Melanoma Registry (SweMR) to identify a precohort of those treated before the introduction of adjuvant therapy in 2018 and a postcohort of those treated subsequently, following both groups out to 2023, she explained.
The analysis revealed no significant difference in melanoma-specific survival between the two groups, at a hazard ratio of 0.92, nor in overall survival, at a hazard ratio of 0.93 (P = .60 for both). However, median follow-up differed between the groups, at 69 months vs 39 months for the precohort vs the postcohort.
Helgadottir, who is a senior research specialist at the Karolinska Comprehensive Cancer Center in Stockholm, Sweden, said that when the earlier results were presented at the European Society for Medical Oncology 2024, there was some criticism that the follow-up was not long enough and that there was no information on the actual adjuvant treatment received in the postcohort patients.
The researchers therefore extended their study out to 2024 to increase the median follow-up to 60 months vs 92 months in the postcohort group vs the precohort group.
They also focused patient selection on patients aged less than 75 years because exposure to adjuvant therapy in older patients was low and restricted the analysis to sentinel lymph node-positive stage IIIB-D cutaneous melanoma diagnosed between 2016 and 2020. This was because adjuvant exposure in stage IIIA disease was low, and patients with clinically detected stage III melanoma started to receive neoadjuvant therapy from 2022 onward.
The current analysis, which was recently published in the European Journal of Cancer, involved 287 patients in the precohort and 349 in the postcohort, who had a median age of 60.0 years and 61.0 years, respectively, and of whom 62.0% and 60.5%, respectively, were male. The groups were well balanced in terms of baseline disease characteristics.
Helgadottir explained that 73% of patients in the postcohort received some form of adjuvant treatment, with the majority treated with PD-1 inhibitors, and a smaller proportion given B-Raf serine-threonine kinase inhibitors. The main reasons for not giving adjuvant therapy were favorable tumor characteristics and the presence of comorbidities.
Five-year melanoma-specific survival rates in the precohorts and postcohorts were 71.4% vs 73.2%, at a hazard ratio adjusted for age, sex, and American Joint Committee on Cancer stage of 1.01 (P = .931). Five-year overall survival rates were 67.3% vs 70.1%, at an adjusted hazard ratio of 0.96 (P = .791).
Helgadottir showed that there were also no significant survival differences in any of the prespecified subgroups for neither melanoma-specific nor overall survival.
There were, again, no significant differences in survival outcomes between the two patient groups, she reported.
The latest results are similar to those from another study conducted in Netherlands and a Danish analysis, Helgadottir said.
Taken together, and “considering the side effects and the costs, it is possible that we will go back to closely following up our patients and treating only at relapse,” she said, “and optimally, of course, that will be already in the neoadjuvant setting.”
“And of course we will need biomarkers because there could be some patients that really need adjuvant treatment, but we need to identify these patients,” continued Helgadottir. Overall survival results from KEYNOTE-054, which compares pembrolizumab with placebo after resection of high-risk stage III melanoma, are awaited, she continued.
Helgadottir explained that adjuvant treatment for stage III melanoma was approved in Sweden in 2018, with treatments freely available to all Swedish residents.
The SweMR is a population-based national register that has near-complete and detailed data on primary cutaneous melanomas, including nodal status and satellite and in-transit disease, and is linked to the national Cause of Death Registry. Helgadottir noted, however, that the SweMR does not contain any information on relapses or the nature of the oncologic treatment received by patients with melanoma.
Following her presentation, she was challenged by an audience member as to whether, on the basis of her findings, she would go back to following up with patients and treating at relapses.
“Maybe we should do that and believe in our own data, and we do. But still, the gold standard must always be the randomized clinical trial,” Helgadottir responded. “So I think, although that we believe in this data, we also want to see the results of the randomized studies.”
The audience member commented that she can see in the data from her own institution that they treat fewer and fewer patients with melanoma with adjuvant therapy by discussing it more thoroughly and being stricter on who should receive it.
Helgadottir agreed, adding that “based on this experience, we did not introduce it to stage II patients because it’s always harder to go back” once a group of patients has started to receive a treatment.
The research was supported by Regional Cancer Centres in Sweden and with grants from the Swedish Cancer Society, Region Stockholm, and the Cancer Research Funds of Radiumhemmet. Helgadottir declared having relationships with Bristol Myers Squibb, Merck Sharp & Dohme, Pierre Fabre, and Novartis.
The trial was supported by SkinVision. The researchers declared having no relevant financial relationships.
This article was previously published by Medscape.
Offering adjuvant therapy to patients with stage III melanoma offers no melanoma-specific or overall survival benefit, reveals extended follow-up from the first population-based national study to estimate the impact of the treatment.
Hildur Helgadottir, MD, PhD, presented the new findings at the 22nd European Association of Dermato-Oncology (EADO) Congress 2026 on April 24 and described the lead-up to the latest update on the study.
To investigate the impact of adjuvant treatment in patients with stage III melanoma, researchers initially conducted a study in which they used the Swedish Melanoma Registry (SweMR) to identify a precohort of those treated before the introduction of adjuvant therapy in 2018 and a postcohort of those treated subsequently, following both groups out to 2023, she explained.
The analysis revealed no significant difference in melanoma-specific survival between the two groups, at a hazard ratio of 0.92, nor in overall survival, at a hazard ratio of 0.93 (P = .60 for both). However, median follow-up differed between the groups, at 69 months vs 39 months for the precohort vs the postcohort.
Helgadottir, who is a senior research specialist at the Karolinska Comprehensive Cancer Center in Stockholm, Sweden, said that when the earlier results were presented at the European Society for Medical Oncology 2024, there was some criticism that the follow-up was not long enough and that there was no information on the actual adjuvant treatment received in the postcohort patients.
The researchers therefore extended their study out to 2024 to increase the median follow-up to 60 months vs 92 months in the postcohort group vs the precohort group.
They also focused patient selection on patients aged less than 75 years because exposure to adjuvant therapy in older patients was low and restricted the analysis to sentinel lymph node-positive stage IIIB-D cutaneous melanoma diagnosed between 2016 and 2020. This was because adjuvant exposure in stage IIIA disease was low, and patients with clinically detected stage III melanoma started to receive neoadjuvant therapy from 2022 onward.
The current analysis, which was recently published in the European Journal of Cancer, involved 287 patients in the precohort and 349 in the postcohort, who had a median age of 60.0 years and 61.0 years, respectively, and of whom 62.0% and 60.5%, respectively, were male. The groups were well balanced in terms of baseline disease characteristics.
Helgadottir explained that 73% of patients in the postcohort received some form of adjuvant treatment, with the majority treated with PD-1 inhibitors, and a smaller proportion given B-Raf serine-threonine kinase inhibitors. The main reasons for not giving adjuvant therapy were favorable tumor characteristics and the presence of comorbidities.
Five-year melanoma-specific survival rates in the precohorts and postcohorts were 71.4% vs 73.2%, at a hazard ratio adjusted for age, sex, and American Joint Committee on Cancer stage of 1.01 (P = .931). Five-year overall survival rates were 67.3% vs 70.1%, at an adjusted hazard ratio of 0.96 (P = .791).
Helgadottir showed that there were also no significant survival differences in any of the prespecified subgroups for neither melanoma-specific nor overall survival.
There were, again, no significant differences in survival outcomes between the two patient groups, she reported.
The latest results are similar to those from another study conducted in Netherlands and a Danish analysis, Helgadottir said.
Taken together, and “considering the side effects and the costs, it is possible that we will go back to closely following up our patients and treating only at relapse,” she said, “and optimally, of course, that will be already in the neoadjuvant setting.”
“And of course we will need biomarkers because there could be some patients that really need adjuvant treatment, but we need to identify these patients,” continued Helgadottir. Overall survival results from KEYNOTE-054, which compares pembrolizumab with placebo after resection of high-risk stage III melanoma, are awaited, she continued.
Helgadottir explained that adjuvant treatment for stage III melanoma was approved in Sweden in 2018, with treatments freely available to all Swedish residents.
The SweMR is a population-based national register that has near-complete and detailed data on primary cutaneous melanomas, including nodal status and satellite and in-transit disease, and is linked to the national Cause of Death Registry. Helgadottir noted, however, that the SweMR does not contain any information on relapses or the nature of the oncologic treatment received by patients with melanoma.
Following her presentation, she was challenged by an audience member as to whether, on the basis of her findings, she would go back to following up with patients and treating at relapses.
“Maybe we should do that and believe in our own data, and we do. But still, the gold standard must always be the randomized clinical trial,” Helgadottir responded. “So I think, although that we believe in this data, we also want to see the results of the randomized studies.”
The audience member commented that she can see in the data from her own institution that they treat fewer and fewer patients with melanoma with adjuvant therapy by discussing it more thoroughly and being stricter on who should receive it.
Helgadottir agreed, adding that “based on this experience, we did not introduce it to stage II patients because it’s always harder to go back” once a group of patients has started to receive a treatment.
The research was supported by Regional Cancer Centres in Sweden and with grants from the Swedish Cancer Society, Region Stockholm, and the Cancer Research Funds of Radiumhemmet. Helgadottir declared having relationships with Bristol Myers Squibb, Merck Sharp & Dohme, Pierre Fabre, and Novartis.
The trial was supported by SkinVision. The researchers declared having no relevant financial relationships.
This article was previously published by Medscape.
Offering adjuvant therapy to patients with stage III melanoma offers no melanoma-specific or overall survival benefit, reveals extended follow-up from the first population-based national study to estimate the impact of the treatment.
Hildur Helgadottir, MD, PhD, presented the new findings at the 22nd European Association of Dermato-Oncology (EADO) Congress 2026 on April 24 and described the lead-up to the latest update on the study.
To investigate the impact of adjuvant treatment in patients with stage III melanoma, researchers initially conducted a study in which they used the Swedish Melanoma Registry (SweMR) to identify a precohort of those treated before the introduction of adjuvant therapy in 2018 and a postcohort of those treated subsequently, following both groups out to 2023, she explained.
The analysis revealed no significant difference in melanoma-specific survival between the two groups, at a hazard ratio of 0.92, nor in overall survival, at a hazard ratio of 0.93 (P = .60 for both). However, median follow-up differed between the groups, at 69 months vs 39 months for the precohort vs the postcohort.
Helgadottir, who is a senior research specialist at the Karolinska Comprehensive Cancer Center in Stockholm, Sweden, said that when the earlier results were presented at the European Society for Medical Oncology 2024, there was some criticism that the follow-up was not long enough and that there was no information on the actual adjuvant treatment received in the postcohort patients.
The researchers therefore extended their study out to 2024 to increase the median follow-up to 60 months vs 92 months in the postcohort group vs the precohort group.
They also focused patient selection on patients aged less than 75 years because exposure to adjuvant therapy in older patients was low and restricted the analysis to sentinel lymph node-positive stage IIIB-D cutaneous melanoma diagnosed between 2016 and 2020. This was because adjuvant exposure in stage IIIA disease was low, and patients with clinically detected stage III melanoma started to receive neoadjuvant therapy from 2022 onward.
The current analysis, which was recently published in the European Journal of Cancer, involved 287 patients in the precohort and 349 in the postcohort, who had a median age of 60.0 years and 61.0 years, respectively, and of whom 62.0% and 60.5%, respectively, were male. The groups were well balanced in terms of baseline disease characteristics.
Helgadottir explained that 73% of patients in the postcohort received some form of adjuvant treatment, with the majority treated with PD-1 inhibitors, and a smaller proportion given B-Raf serine-threonine kinase inhibitors. The main reasons for not giving adjuvant therapy were favorable tumor characteristics and the presence of comorbidities.
Five-year melanoma-specific survival rates in the precohorts and postcohorts were 71.4% vs 73.2%, at a hazard ratio adjusted for age, sex, and American Joint Committee on Cancer stage of 1.01 (P = .931). Five-year overall survival rates were 67.3% vs 70.1%, at an adjusted hazard ratio of 0.96 (P = .791).
Helgadottir showed that there were also no significant survival differences in any of the prespecified subgroups for neither melanoma-specific nor overall survival.
There were, again, no significant differences in survival outcomes between the two patient groups, she reported.
The latest results are similar to those from another study conducted in Netherlands and a Danish analysis, Helgadottir said.
Taken together, and “considering the side effects and the costs, it is possible that we will go back to closely following up our patients and treating only at relapse,” she said, “and optimally, of course, that will be already in the neoadjuvant setting.”
“And of course we will need biomarkers because there could be some patients that really need adjuvant treatment, but we need to identify these patients,” continued Helgadottir. Overall survival results from KEYNOTE-054, which compares pembrolizumab with placebo after resection of high-risk stage III melanoma, are awaited, she continued.
Helgadottir explained that adjuvant treatment for stage III melanoma was approved in Sweden in 2018, with treatments freely available to all Swedish residents.
The SweMR is a population-based national register that has near-complete and detailed data on primary cutaneous melanomas, including nodal status and satellite and in-transit disease, and is linked to the national Cause of Death Registry. Helgadottir noted, however, that the SweMR does not contain any information on relapses or the nature of the oncologic treatment received by patients with melanoma.
Following her presentation, she was challenged by an audience member as to whether, on the basis of her findings, she would go back to following up with patients and treating at relapses.
“Maybe we should do that and believe in our own data, and we do. But still, the gold standard must always be the randomized clinical trial,” Helgadottir responded. “So I think, although that we believe in this data, we also want to see the results of the randomized studies.”
The audience member commented that she can see in the data from her own institution that they treat fewer and fewer patients with melanoma with adjuvant therapy by discussing it more thoroughly and being stricter on who should receive it.
Helgadottir agreed, adding that “based on this experience, we did not introduce it to stage II patients because it’s always harder to go back” once a group of patients has started to receive a treatment.
The research was supported by Regional Cancer Centres in Sweden and with grants from the Swedish Cancer Society, Region Stockholm, and the Cancer Research Funds of Radiumhemmet. Helgadottir declared having relationships with Bristol Myers Squibb, Merck Sharp & Dohme, Pierre Fabre, and Novartis.
The trial was supported by SkinVision. The researchers declared having no relevant financial relationships.
This article was previously published by Medscape.
Wildfire Smoke Linked to Potential Risks for Some Cancers
Wildfire smoke exposure may be associated with increased risks for multiple types of cancer, suggests an analysis of prospective cohort data from over 90,000 individuals.
To determine how this widespread pollution might be affecting cancer risk, senior author Shuguang Leng, MBBS, PhD, and colleagues analyzed data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. That prospective national study enrolled approximately 154,000 participants between 1993 and 2001 and tracked cancer incidence through 2018. Of these, 91,460 participants had wildfire smoke exposure data and were included in the analysis.
During the 2006-2018 exposure period, the investigators identified incident cases of 242 ovarian, 800 colorectal, 896 bladder, 1696 hematopoietic, 1739 breast, and 1758 lung cancers, as well as 1127 melanoma cases. The median 36-month moving average for wildfire smoke PM2.5 (fine particulate matter) across the cohort was 0.37 µg/m3.
Wildfire smoke exposure was significantly associated with increased risks for lung, colorectal, breast, bladder, and hematopoietic cancer, according to the results of the study presented by Leng at American Association for Cancer Research (AACR) Annual Meeting 2026.
Each 1 µg/m3 increase in the 36-month moving average of wildfire smoke PM2.5 was associated with a 63% higher risk for hematopoietic cancer (HR, 1.63; 95% CI, 1.02-2.60), a nearly twofold higher risk for lung cancer (hazard ratio [HR], 1.92; 95% CI, 1.18-3.15), more than twofold higher risks for breast cancer (HR, 2.09; 95% CI, 1.34-3.26) and colorectal cancer (HR, 2.31; 95% CI, 1.11-4.81), and a more than threefold higher risk for bladder cancer (HR, 3.49; 95% CI, 1.66-7.34). No significant associations were observed for ovarian cancer or melanoma.
The investigators quantified wildfire smoke exposure at each participant’s residence on a monthly basis using three measures: near-ground wildfire smoke PM2.5, wildfire smoke black carbon, and satellite-derived wildfire smoke plume-day counts, with measurements available from 2006 until first cancer diagnosis or last contact.
Given evidence that 3 years of air pollution exposure can influence the development of epidermal growth factor receptor-positive lung adenocarcinoma, the team modeled exposure as a time-varying variable using 36-month moving averages preceding each month. HRs were estimated using Cox proportional hazards models stratified by study center, with restricted cubic splines applied to evaluate dose-response relationships. Models were adjusted for age, sex, race and ethnicity, education, smoking history, BMI, and trial arm.
All five cancer types linked with wildfire smoke exposure showed linear dose-response relationships, Leng noted, “which means the higher the exposure, the higher the cancer risk.”
Results based on wildfire smoke plume-day counts were generally consistent with those for PM2.5, while associations for black carbon exposure were observed only for breast and bladder cancers.
With wildfires on the rise, these findings suggest that the resulting smoke may become a “major driver for cancer burden in the US in the coming decades,” said Leng, of the University of New Mexico Comprehensive Cancer Center, Albuquerque, New Mexico.
“Wildfire smoke has become a major source of air pollution in the United States,” he continued. Large fires in the US are three times more common than they were 50 years ago, and the “tons of toxicants and particles” released by these fires “can travel hundreds of miles to affect communities far away.”
The investigators also conducted histology-specific analyses, finding that adenocarcinoma showed the strongest association with wildfire smoke among lung cancer subtypes. Among colorectal cancers, proximal tumors appeared more sensitive to wildfire smoke exposure, while among bladder cancers, the association was strongest for muscle-invasive disease.
Wildfire Smoke Exposure Expected to Rise
Under even the most conservative climate projections, wildfire smoke exposure in the US is expected to rise over the next 20-30 years, Leng said.
Annual average wildfire smoke PM2.5 levels, currently estimated at around 0.5 µg/m3, could rise to 1 µg/m3. Based on the study’s dose-response data, this would correspond to substantially greater cancer risk.
There will be “a much larger area” of the US exposed “at a much higher dose,” Leng predicted.
Mitigating the Risks of Wildfire Smoke
This is a “strong hypothesis-generating study,” Jun Wu, PhD, professor of environmental and occupational health at the UC Irvine Program in Public Health, Irvine, California, told Medscape Medical News.
“This is one of the first large, prospective US cohort studies to examine wildfire smoke specifically in relation to cancer risk, especially cancer sites beyond the lung,” Wu said. “A major strength is that the PLCO platform has around 91,000 participants with longitudinal follow-up and detailed covariate data, including smoking history, which is often a weak point in previous air pollution-cancer studies.”
According to Wu, who was not involved in the analysis but recently published data linking wildfire smoke exposure to preterm birth, the reported risks for colorectal, breast, bladder, and hematopoietic cancers represent novel contributions to the literature. However, she cautioned against viewing the specific HRs as a precise estimates of risk due to wide confidence intervals.
The findings should encourage individuals, public health officials, and clinicians to mitigate the risks of wildfire smoke, Wu said.
Specifically, she suggested that public health assessments expand beyond acute outcomes like emergency department visits to include long-term endpoints such as cancer, while community clean-air shelters need to be made more widely available.
She advised clinicians to incorporate wildfire exposure into routine patient histories and to provide vulnerable patients — such as those with asthma, chronic obstructive pulmonary disease, heart failure, or pregnancy — with smoke-season action plans.
Risk mitigation begins with awareness, according to Wu, who advised individuals check their local air quality index on AirNow.gov or PurpleAir.
On smoky days, she suggested prioritizing indoor air quality by keeping windows closed and running air purifiers. If going outside on such days is necessary, she suggested an N95 or KN95 mask, as these offer “meaningful protection,” while cloth and surgical masks do not.
These preventive steps may have once been out of the ordinary, Wu said, but the risk for wildfire smoke exposure is becoming a part of everyday life.
“The common thread is a shift in framing,” Wu said. “Wildfire smoke has traditionally been treated as an acute event, but the emerging evidence points to a chronic environmental exposure. Both our clinical and public health systems have room to grow into that reality.”
The analysis was funded by the National Institutes of Health. The investigators and Wu reported having no conflicts of interest.
This article was previously published on Medscape.
Wildfire smoke exposure may be associated with increased risks for multiple types of cancer, suggests an analysis of prospective cohort data from over 90,000 individuals.
To determine how this widespread pollution might be affecting cancer risk, senior author Shuguang Leng, MBBS, PhD, and colleagues analyzed data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. That prospective national study enrolled approximately 154,000 participants between 1993 and 2001 and tracked cancer incidence through 2018. Of these, 91,460 participants had wildfire smoke exposure data and were included in the analysis.
During the 2006-2018 exposure period, the investigators identified incident cases of 242 ovarian, 800 colorectal, 896 bladder, 1696 hematopoietic, 1739 breast, and 1758 lung cancers, as well as 1127 melanoma cases. The median 36-month moving average for wildfire smoke PM2.5 (fine particulate matter) across the cohort was 0.37 µg/m3.
Wildfire smoke exposure was significantly associated with increased risks for lung, colorectal, breast, bladder, and hematopoietic cancer, according to the results of the study presented by Leng at American Association for Cancer Research (AACR) Annual Meeting 2026.
Each 1 µg/m3 increase in the 36-month moving average of wildfire smoke PM2.5 was associated with a 63% higher risk for hematopoietic cancer (HR, 1.63; 95% CI, 1.02-2.60), a nearly twofold higher risk for lung cancer (hazard ratio [HR], 1.92; 95% CI, 1.18-3.15), more than twofold higher risks for breast cancer (HR, 2.09; 95% CI, 1.34-3.26) and colorectal cancer (HR, 2.31; 95% CI, 1.11-4.81), and a more than threefold higher risk for bladder cancer (HR, 3.49; 95% CI, 1.66-7.34). No significant associations were observed for ovarian cancer or melanoma.
The investigators quantified wildfire smoke exposure at each participant’s residence on a monthly basis using three measures: near-ground wildfire smoke PM2.5, wildfire smoke black carbon, and satellite-derived wildfire smoke plume-day counts, with measurements available from 2006 until first cancer diagnosis or last contact.
Given evidence that 3 years of air pollution exposure can influence the development of epidermal growth factor receptor-positive lung adenocarcinoma, the team modeled exposure as a time-varying variable using 36-month moving averages preceding each month. HRs were estimated using Cox proportional hazards models stratified by study center, with restricted cubic splines applied to evaluate dose-response relationships. Models were adjusted for age, sex, race and ethnicity, education, smoking history, BMI, and trial arm.
All five cancer types linked with wildfire smoke exposure showed linear dose-response relationships, Leng noted, “which means the higher the exposure, the higher the cancer risk.”
Results based on wildfire smoke plume-day counts were generally consistent with those for PM2.5, while associations for black carbon exposure were observed only for breast and bladder cancers.
With wildfires on the rise, these findings suggest that the resulting smoke may become a “major driver for cancer burden in the US in the coming decades,” said Leng, of the University of New Mexico Comprehensive Cancer Center, Albuquerque, New Mexico.
“Wildfire smoke has become a major source of air pollution in the United States,” he continued. Large fires in the US are three times more common than they were 50 years ago, and the “tons of toxicants and particles” released by these fires “can travel hundreds of miles to affect communities far away.”
The investigators also conducted histology-specific analyses, finding that adenocarcinoma showed the strongest association with wildfire smoke among lung cancer subtypes. Among colorectal cancers, proximal tumors appeared more sensitive to wildfire smoke exposure, while among bladder cancers, the association was strongest for muscle-invasive disease.
Wildfire Smoke Exposure Expected to Rise
Under even the most conservative climate projections, wildfire smoke exposure in the US is expected to rise over the next 20-30 years, Leng said.
Annual average wildfire smoke PM2.5 levels, currently estimated at around 0.5 µg/m3, could rise to 1 µg/m3. Based on the study’s dose-response data, this would correspond to substantially greater cancer risk.
There will be “a much larger area” of the US exposed “at a much higher dose,” Leng predicted.
Mitigating the Risks of Wildfire Smoke
This is a “strong hypothesis-generating study,” Jun Wu, PhD, professor of environmental and occupational health at the UC Irvine Program in Public Health, Irvine, California, told Medscape Medical News.
“This is one of the first large, prospective US cohort studies to examine wildfire smoke specifically in relation to cancer risk, especially cancer sites beyond the lung,” Wu said. “A major strength is that the PLCO platform has around 91,000 participants with longitudinal follow-up and detailed covariate data, including smoking history, which is often a weak point in previous air pollution-cancer studies.”
According to Wu, who was not involved in the analysis but recently published data linking wildfire smoke exposure to preterm birth, the reported risks for colorectal, breast, bladder, and hematopoietic cancers represent novel contributions to the literature. However, she cautioned against viewing the specific HRs as a precise estimates of risk due to wide confidence intervals.
The findings should encourage individuals, public health officials, and clinicians to mitigate the risks of wildfire smoke, Wu said.
Specifically, she suggested that public health assessments expand beyond acute outcomes like emergency department visits to include long-term endpoints such as cancer, while community clean-air shelters need to be made more widely available.
She advised clinicians to incorporate wildfire exposure into routine patient histories and to provide vulnerable patients — such as those with asthma, chronic obstructive pulmonary disease, heart failure, or pregnancy — with smoke-season action plans.
Risk mitigation begins with awareness, according to Wu, who advised individuals check their local air quality index on AirNow.gov or PurpleAir.
On smoky days, she suggested prioritizing indoor air quality by keeping windows closed and running air purifiers. If going outside on such days is necessary, she suggested an N95 or KN95 mask, as these offer “meaningful protection,” while cloth and surgical masks do not.
These preventive steps may have once been out of the ordinary, Wu said, but the risk for wildfire smoke exposure is becoming a part of everyday life.
“The common thread is a shift in framing,” Wu said. “Wildfire smoke has traditionally been treated as an acute event, but the emerging evidence points to a chronic environmental exposure. Both our clinical and public health systems have room to grow into that reality.”
The analysis was funded by the National Institutes of Health. The investigators and Wu reported having no conflicts of interest.
This article was previously published on Medscape.
Wildfire smoke exposure may be associated with increased risks for multiple types of cancer, suggests an analysis of prospective cohort data from over 90,000 individuals.
To determine how this widespread pollution might be affecting cancer risk, senior author Shuguang Leng, MBBS, PhD, and colleagues analyzed data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. That prospective national study enrolled approximately 154,000 participants between 1993 and 2001 and tracked cancer incidence through 2018. Of these, 91,460 participants had wildfire smoke exposure data and were included in the analysis.
During the 2006-2018 exposure period, the investigators identified incident cases of 242 ovarian, 800 colorectal, 896 bladder, 1696 hematopoietic, 1739 breast, and 1758 lung cancers, as well as 1127 melanoma cases. The median 36-month moving average for wildfire smoke PM2.5 (fine particulate matter) across the cohort was 0.37 µg/m3.
Wildfire smoke exposure was significantly associated with increased risks for lung, colorectal, breast, bladder, and hematopoietic cancer, according to the results of the study presented by Leng at American Association for Cancer Research (AACR) Annual Meeting 2026.
Each 1 µg/m3 increase in the 36-month moving average of wildfire smoke PM2.5 was associated with a 63% higher risk for hematopoietic cancer (HR, 1.63; 95% CI, 1.02-2.60), a nearly twofold higher risk for lung cancer (hazard ratio [HR], 1.92; 95% CI, 1.18-3.15), more than twofold higher risks for breast cancer (HR, 2.09; 95% CI, 1.34-3.26) and colorectal cancer (HR, 2.31; 95% CI, 1.11-4.81), and a more than threefold higher risk for bladder cancer (HR, 3.49; 95% CI, 1.66-7.34). No significant associations were observed for ovarian cancer or melanoma.
The investigators quantified wildfire smoke exposure at each participant’s residence on a monthly basis using three measures: near-ground wildfire smoke PM2.5, wildfire smoke black carbon, and satellite-derived wildfire smoke plume-day counts, with measurements available from 2006 until first cancer diagnosis or last contact.
Given evidence that 3 years of air pollution exposure can influence the development of epidermal growth factor receptor-positive lung adenocarcinoma, the team modeled exposure as a time-varying variable using 36-month moving averages preceding each month. HRs were estimated using Cox proportional hazards models stratified by study center, with restricted cubic splines applied to evaluate dose-response relationships. Models were adjusted for age, sex, race and ethnicity, education, smoking history, BMI, and trial arm.
All five cancer types linked with wildfire smoke exposure showed linear dose-response relationships, Leng noted, “which means the higher the exposure, the higher the cancer risk.”
Results based on wildfire smoke plume-day counts were generally consistent with those for PM2.5, while associations for black carbon exposure were observed only for breast and bladder cancers.
With wildfires on the rise, these findings suggest that the resulting smoke may become a “major driver for cancer burden in the US in the coming decades,” said Leng, of the University of New Mexico Comprehensive Cancer Center, Albuquerque, New Mexico.
“Wildfire smoke has become a major source of air pollution in the United States,” he continued. Large fires in the US are three times more common than they were 50 years ago, and the “tons of toxicants and particles” released by these fires “can travel hundreds of miles to affect communities far away.”
The investigators also conducted histology-specific analyses, finding that adenocarcinoma showed the strongest association with wildfire smoke among lung cancer subtypes. Among colorectal cancers, proximal tumors appeared more sensitive to wildfire smoke exposure, while among bladder cancers, the association was strongest for muscle-invasive disease.
Wildfire Smoke Exposure Expected to Rise
Under even the most conservative climate projections, wildfire smoke exposure in the US is expected to rise over the next 20-30 years, Leng said.
Annual average wildfire smoke PM2.5 levels, currently estimated at around 0.5 µg/m3, could rise to 1 µg/m3. Based on the study’s dose-response data, this would correspond to substantially greater cancer risk.
There will be “a much larger area” of the US exposed “at a much higher dose,” Leng predicted.
Mitigating the Risks of Wildfire Smoke
This is a “strong hypothesis-generating study,” Jun Wu, PhD, professor of environmental and occupational health at the UC Irvine Program in Public Health, Irvine, California, told Medscape Medical News.
“This is one of the first large, prospective US cohort studies to examine wildfire smoke specifically in relation to cancer risk, especially cancer sites beyond the lung,” Wu said. “A major strength is that the PLCO platform has around 91,000 participants with longitudinal follow-up and detailed covariate data, including smoking history, which is often a weak point in previous air pollution-cancer studies.”
According to Wu, who was not involved in the analysis but recently published data linking wildfire smoke exposure to preterm birth, the reported risks for colorectal, breast, bladder, and hematopoietic cancers represent novel contributions to the literature. However, she cautioned against viewing the specific HRs as a precise estimates of risk due to wide confidence intervals.
The findings should encourage individuals, public health officials, and clinicians to mitigate the risks of wildfire smoke, Wu said.
Specifically, she suggested that public health assessments expand beyond acute outcomes like emergency department visits to include long-term endpoints such as cancer, while community clean-air shelters need to be made more widely available.
She advised clinicians to incorporate wildfire exposure into routine patient histories and to provide vulnerable patients — such as those with asthma, chronic obstructive pulmonary disease, heart failure, or pregnancy — with smoke-season action plans.
Risk mitigation begins with awareness, according to Wu, who advised individuals check their local air quality index on AirNow.gov or PurpleAir.
On smoky days, she suggested prioritizing indoor air quality by keeping windows closed and running air purifiers. If going outside on such days is necessary, she suggested an N95 or KN95 mask, as these offer “meaningful protection,” while cloth and surgical masks do not.
These preventive steps may have once been out of the ordinary, Wu said, but the risk for wildfire smoke exposure is becoming a part of everyday life.
“The common thread is a shift in framing,” Wu said. “Wildfire smoke has traditionally been treated as an acute event, but the emerging evidence points to a chronic environmental exposure. Both our clinical and public health systems have room to grow into that reality.”
The analysis was funded by the National Institutes of Health. The investigators and Wu reported having no conflicts of interest.
This article was previously published on Medscape.
Many Veterans With H&N Cancer Face Access, Equity Barriers
TOPLINE: In 75,453 veterans with head and neck squamous cell carcinoma (HNSCC), 36.4% live in rural or highly rural areas and 32.0% have a national area deprivation index (ADI) ≥ 75. The average drive time to the nearest tertiary or complex US Department of Veterans Affairs (VA) facility is 94 minutes, highlighting potential access and equity barriers related to rurality, deprivation, and distance.
METHODOLOGY:
A retrospective descriptive study using nationwide VA data from fiscal years 2012 to 2022 identified 75,453 veterans with head and neck squamous cell carcinoma (HNSCC) by International Classification of Diseases, Ninth Revision and International Classification of Diseases, Tenth Revision codes.
Patients were grouped into 5 primary tumor subsites: oral cavity, oropharynx, hypopharynx, larynx, and nasopharynx.
Rurality was classified using Rural-Urban Commuting Area-derived urban, rural, and highly rural scores; socioeconomic disadvantage was measured with national ADI scores.
Travel burden was assessed using time and distance to the nearest primary, secondary, and tertiary VA facilities.
TAKEAWAY:
Oropharyngeal cancer (OPC) cases among veterans increased from 26.3% in 2012 to 46.0% in 2022, while laryngeal cancers decreased from 41.2% to 29.3%.
HNSCCs locations included 35.6% in the larynx, 34.4% in the oropharynx, 22.6% in the oral cavity 3.7% in the hypopharynx, and 3.7% in the nasopharynx.
Veterans with OPC were younger than non-OPC patients and more likely to be White; > 70% were current or former smokers.
IN PRACTICE: “Understanding the geographic and socioeconomic landscape of veterans with HNSCC will allow us to tease out the factors associated with poor outcomes and ultimately design interventions that target high-risk veteran populations to improve overall health outcomes,” the authors argued.
SOURCE: The study was led by researchers at the Veterans Affairs Pittsburgh Healthcare System. It was published online in Head & Neck.
LIMITATIONS: The inability to extract accurate data from a large dataset, challenges in obtaining tumor stage information due to varying documentation practices across physicians and treatment courses, and the inability to assess HPV or p16 data for the cohort represents significant limitations that may have impacted interpretation of results. Clinical outcome measures and cause of death assessment were limited in this national database, affecting the ability to draw conclusions regarding the impact of rurality, area deprivation, and travel time on outcomes.
DISCLOSURES: Chad Brenner reported holding several patents related to the development and use of circulating tumor DNA tests in patients with HNSCC. Jose P. Zevallos disclosed being the founder, equity shareholder, and board member of Droplet Biosciences and Echogenesis Therapeutics, serving as chief scientific advisor and shareholder of Vine Medical, and acting as a consultant for Merck and Johnson & Johnson. Matthew E. Spector reported serving as a consultant for Hologic. Kristen L. Zayan, Jennifer L. McCoy, Monique Y. Boudreaux-Kelly, Zachary Hahn, John Hotchkiss, and Jessica H. Maxwell declared 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.
TOPLINE: In 75,453 veterans with head and neck squamous cell carcinoma (HNSCC), 36.4% live in rural or highly rural areas and 32.0% have a national area deprivation index (ADI) ≥ 75. The average drive time to the nearest tertiary or complex US Department of Veterans Affairs (VA) facility is 94 minutes, highlighting potential access and equity barriers related to rurality, deprivation, and distance.
METHODOLOGY:
A retrospective descriptive study using nationwide VA data from fiscal years 2012 to 2022 identified 75,453 veterans with head and neck squamous cell carcinoma (HNSCC) by International Classification of Diseases, Ninth Revision and International Classification of Diseases, Tenth Revision codes.
Patients were grouped into 5 primary tumor subsites: oral cavity, oropharynx, hypopharynx, larynx, and nasopharynx.
Rurality was classified using Rural-Urban Commuting Area-derived urban, rural, and highly rural scores; socioeconomic disadvantage was measured with national ADI scores.
Travel burden was assessed using time and distance to the nearest primary, secondary, and tertiary VA facilities.
TAKEAWAY:
Oropharyngeal cancer (OPC) cases among veterans increased from 26.3% in 2012 to 46.0% in 2022, while laryngeal cancers decreased from 41.2% to 29.3%.
HNSCCs locations included 35.6% in the larynx, 34.4% in the oropharynx, 22.6% in the oral cavity 3.7% in the hypopharynx, and 3.7% in the nasopharynx.
Veterans with OPC were younger than non-OPC patients and more likely to be White; > 70% were current or former smokers.
IN PRACTICE: “Understanding the geographic and socioeconomic landscape of veterans with HNSCC will allow us to tease out the factors associated with poor outcomes and ultimately design interventions that target high-risk veteran populations to improve overall health outcomes,” the authors argued.
SOURCE: The study was led by researchers at the Veterans Affairs Pittsburgh Healthcare System. It was published online in Head & Neck.
LIMITATIONS: The inability to extract accurate data from a large dataset, challenges in obtaining tumor stage information due to varying documentation practices across physicians and treatment courses, and the inability to assess HPV or p16 data for the cohort represents significant limitations that may have impacted interpretation of results. Clinical outcome measures and cause of death assessment were limited in this national database, affecting the ability to draw conclusions regarding the impact of rurality, area deprivation, and travel time on outcomes.
DISCLOSURES: Chad Brenner reported holding several patents related to the development and use of circulating tumor DNA tests in patients with HNSCC. Jose P. Zevallos disclosed being the founder, equity shareholder, and board member of Droplet Biosciences and Echogenesis Therapeutics, serving as chief scientific advisor and shareholder of Vine Medical, and acting as a consultant for Merck and Johnson & Johnson. Matthew E. Spector reported serving as a consultant for Hologic. Kristen L. Zayan, Jennifer L. McCoy, Monique Y. Boudreaux-Kelly, Zachary Hahn, John Hotchkiss, and Jessica H. Maxwell declared 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.
TOPLINE: In 75,453 veterans with head and neck squamous cell carcinoma (HNSCC), 36.4% live in rural or highly rural areas and 32.0% have a national area deprivation index (ADI) ≥ 75. The average drive time to the nearest tertiary or complex US Department of Veterans Affairs (VA) facility is 94 minutes, highlighting potential access and equity barriers related to rurality, deprivation, and distance.
METHODOLOGY:
A retrospective descriptive study using nationwide VA data from fiscal years 2012 to 2022 identified 75,453 veterans with head and neck squamous cell carcinoma (HNSCC) by International Classification of Diseases, Ninth Revision and International Classification of Diseases, Tenth Revision codes.
Patients were grouped into 5 primary tumor subsites: oral cavity, oropharynx, hypopharynx, larynx, and nasopharynx.
Rurality was classified using Rural-Urban Commuting Area-derived urban, rural, and highly rural scores; socioeconomic disadvantage was measured with national ADI scores.
Travel burden was assessed using time and distance to the nearest primary, secondary, and tertiary VA facilities.
TAKEAWAY:
Oropharyngeal cancer (OPC) cases among veterans increased from 26.3% in 2012 to 46.0% in 2022, while laryngeal cancers decreased from 41.2% to 29.3%.
HNSCCs locations included 35.6% in the larynx, 34.4% in the oropharynx, 22.6% in the oral cavity 3.7% in the hypopharynx, and 3.7% in the nasopharynx.
Veterans with OPC were younger than non-OPC patients and more likely to be White; > 70% were current or former smokers.
IN PRACTICE: “Understanding the geographic and socioeconomic landscape of veterans with HNSCC will allow us to tease out the factors associated with poor outcomes and ultimately design interventions that target high-risk veteran populations to improve overall health outcomes,” the authors argued.
SOURCE: The study was led by researchers at the Veterans Affairs Pittsburgh Healthcare System. It was published online in Head & Neck.
LIMITATIONS: The inability to extract accurate data from a large dataset, challenges in obtaining tumor stage information due to varying documentation practices across physicians and treatment courses, and the inability to assess HPV or p16 data for the cohort represents significant limitations that may have impacted interpretation of results. Clinical outcome measures and cause of death assessment were limited in this national database, affecting the ability to draw conclusions regarding the impact of rurality, area deprivation, and travel time on outcomes.
DISCLOSURES: Chad Brenner reported holding several patents related to the development and use of circulating tumor DNA tests in patients with HNSCC. Jose P. Zevallos disclosed being the founder, equity shareholder, and board member of Droplet Biosciences and Echogenesis Therapeutics, serving as chief scientific advisor and shareholder of Vine Medical, and acting as a consultant for Merck and Johnson & Johnson. Matthew E. Spector reported serving as a consultant for Hologic. Kristen L. Zayan, Jennifer L. McCoy, Monique Y. Boudreaux-Kelly, Zachary Hahn, John Hotchkiss, and Jessica H. Maxwell declared 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.
Does Marital Status Affect Cancer Risk?
Adults who have never been married had a higher cancer risk than their married or previously married peers, with patterns observed across many major cancer types and particularly strong for cancers linked to infections, smoking, and reproductive factors, new data suggest.
The findings are based on a large, population-based cancer registry analysis of more than 4 million cases, making it the largest study of its kind in the US.
First author Paulo Pinheiro, PhD, cautioned, however, that the study does not suggest that marriage itself is protective.
"As with any observational study, we cannot establish causation, and unmeasured factors may contribute to the associations,” said Pinheiro, with Sylvester Comprehensive Cancer Center, University of Miami Health System, in Miami.
Marital status may, however, help identify groups with different patterns of cancer risk, which likely reflect social and lifestyle behaviors rather than a direct causal effect, Pinheiro explained.
Married individuals, for instance, are less likely to smoke — a known cancer risk factor — and more likely to have children and undergo cancer screening, which can influence cancer incidence through reproductive effects and screening, including earlier detection and removal of precancerous lesions.
"Marital status is therefore best understood as a marker of those accumulated factors," Pinheiro said.
The study was published online on April 8 in Cancer Research Communications.
Filling a Data Gap
Marriage has consistently been associated with earlier cancer diagnosis and improved survival among those with cancer, but its relationship to cancer incidence remains less clear.
To address that gap, researchers analyzed data from 12 US states that included demographic and cancer information for more than 4.2 million cancer cases diagnosed between 2015 and 2022.
The analysis included more than 500 million person-years at risk in adults 30 years or older, representing an annual population of more than 62 million. The never-married group comprised about 19% of the total population — 22% were men and 17% were women.
Compared with ever-married individuals, never-married men and women had higher cancer incidence across many major cancer types, racial and ethnic groups, and age groups.
Overall, cancer rates were about 68% higher in never-married men and 85% higher in never-married women compared with their ever-married counterparts (incidence rate ratios [IRRs], 1.68 and 1.85, respectively).
Never-married Black men had the highest overall cancer rates (1600 per 100,000), whereas married Black men had significantly lower rates than married White men (752.6 vs 836.2 per 100,000), suggesting complex interactions between marital status and structural factors, the researchers noted.
Site-specific patterns revealed clues to potential mechanisms linking marital status and cancer.
Compared with ever-married individuals, never-married people had the highest excess risks for human papillomavirus-related cancers — about five times higher for anal cancer in men (IRR, 5.04) and approaching three times higher for cervical cancer in women (IRR, 2.64).
Other strong associations between never-married individuals and cancer risk were observed for smoking-related cancers, including lung (IRR, 2.1 for both men and women) and esophageal cancers (IRR, 2.4 in men and 2.7 in women), and malignancies including liver (IRR, 2.3 for both men and women), bladder (IRR, 2.3 women only), and colorectal (IRR, 2.1 women only) cancers.
Among women, the higher incidence of ovarian and uterine cancers (IRR, 2.4 for both) among the never-married group supports the influence of reproductive mechanisms, such as giving birth, on cancer risk.
The association between marital status and cancer risk was weaker for breast, prostate, and thyroid cancers (with IRRs < 2), suggesting potentially less modifiable etiologies.
Overall, “methodologically, it is quite robust, particularly in its clear framing of ever- vs never-married individuals and the use of standardized incidence rates and regression modeling,” Pinheiro said.
The analysis did not adjust for individual-level risk factors such as smoking, diet, physical activity, or alcohol use — factors that may partly explain the observed associations.
Adjusting for these lifestyle and health behavior factors at the individual level would require detailed information on these behaviors, and “data at that level simply do not exist at a national scale,” Pinheiro said. It would also “obscure the real-world pattern we are trying to measure.”
Gilbert Welch, MD, noted that adjusting for these individual-level cancer risk factors “would certainly attenuate the associations.”
“That said, it wouldn’t be crazy to suggest marriage drives some of these risk factors,” said Welch, general internist and senior investigator at the Center for Surgery and Public Health, Brigham and Women’s Hospital, Boston. Married couples benefit from combined incomes and shared expenses, and “may well help support individuals in making healthy choices (like not smoking).”
But, he added, “it would be crazy to suggest that the reason to get married is to lower cancer risk.”
The authors flagged a study limitation — the fact that ever-married status lumps together people who are currently married, divorced, and widowed, and these groups may have different risk profiles. Additionally, “individuals in strained or abusive marriages may not experience protective social benefits,” while those in long-term cohabiting relationships classified as never-married may experience high levels of support, the authors wrote.
Overall, though, Pinheiro clarified that the main finding is “not about marriage as a causal agent, but about identifying a large population group, the never-married, with a consistently higher cancer burden that has been largely overlooked in public health practice and cancer prevention efforts.”
Linda Waite, professor, Department of Sociology, University of Chicago, who wasn’t involved in the study, wasn’t surprised by the findings. For men, not having a spouse may “disadvantage” them in ways that might increase cancer risk.
Unmarried men are more likely to drink and smoke heavily, which increase cancer risk, she said. A spouse may also influence health awareness and decisions, such as noticing suspicious symptoms, pushing their partner to see a doctor, or helping manage their partner’s care.
Plus, “for both men and women, having a spouse may improve medical care by giving each partner a companion for medical appointments and another person to help manage risks of disease,” Waite said.
The study had no commercial funding. Pinheiro and Waite had no relevant disclosures.
A version of this article first appeared on Medscape.com.
Adults who have never been married had a higher cancer risk than their married or previously married peers, with patterns observed across many major cancer types and particularly strong for cancers linked to infections, smoking, and reproductive factors, new data suggest.
The findings are based on a large, population-based cancer registry analysis of more than 4 million cases, making it the largest study of its kind in the US.
First author Paulo Pinheiro, PhD, cautioned, however, that the study does not suggest that marriage itself is protective.
"As with any observational study, we cannot establish causation, and unmeasured factors may contribute to the associations,” said Pinheiro, with Sylvester Comprehensive Cancer Center, University of Miami Health System, in Miami.
Marital status may, however, help identify groups with different patterns of cancer risk, which likely reflect social and lifestyle behaviors rather than a direct causal effect, Pinheiro explained.
Married individuals, for instance, are less likely to smoke — a known cancer risk factor — and more likely to have children and undergo cancer screening, which can influence cancer incidence through reproductive effects and screening, including earlier detection and removal of precancerous lesions.
"Marital status is therefore best understood as a marker of those accumulated factors," Pinheiro said.
The study was published online on April 8 in Cancer Research Communications.
Filling a Data Gap
Marriage has consistently been associated with earlier cancer diagnosis and improved survival among those with cancer, but its relationship to cancer incidence remains less clear.
To address that gap, researchers analyzed data from 12 US states that included demographic and cancer information for more than 4.2 million cancer cases diagnosed between 2015 and 2022.
The analysis included more than 500 million person-years at risk in adults 30 years or older, representing an annual population of more than 62 million. The never-married group comprised about 19% of the total population — 22% were men and 17% were women.
Compared with ever-married individuals, never-married men and women had higher cancer incidence across many major cancer types, racial and ethnic groups, and age groups.
Overall, cancer rates were about 68% higher in never-married men and 85% higher in never-married women compared with their ever-married counterparts (incidence rate ratios [IRRs], 1.68 and 1.85, respectively).
Never-married Black men had the highest overall cancer rates (1600 per 100,000), whereas married Black men had significantly lower rates than married White men (752.6 vs 836.2 per 100,000), suggesting complex interactions between marital status and structural factors, the researchers noted.
Site-specific patterns revealed clues to potential mechanisms linking marital status and cancer.
Compared with ever-married individuals, never-married people had the highest excess risks for human papillomavirus-related cancers — about five times higher for anal cancer in men (IRR, 5.04) and approaching three times higher for cervical cancer in women (IRR, 2.64).
Other strong associations between never-married individuals and cancer risk were observed for smoking-related cancers, including lung (IRR, 2.1 for both men and women) and esophageal cancers (IRR, 2.4 in men and 2.7 in women), and malignancies including liver (IRR, 2.3 for both men and women), bladder (IRR, 2.3 women only), and colorectal (IRR, 2.1 women only) cancers.
Among women, the higher incidence of ovarian and uterine cancers (IRR, 2.4 for both) among the never-married group supports the influence of reproductive mechanisms, such as giving birth, on cancer risk.
The association between marital status and cancer risk was weaker for breast, prostate, and thyroid cancers (with IRRs < 2), suggesting potentially less modifiable etiologies.
Overall, “methodologically, it is quite robust, particularly in its clear framing of ever- vs never-married individuals and the use of standardized incidence rates and regression modeling,” Pinheiro said.
The analysis did not adjust for individual-level risk factors such as smoking, diet, physical activity, or alcohol use — factors that may partly explain the observed associations.
Adjusting for these lifestyle and health behavior factors at the individual level would require detailed information on these behaviors, and “data at that level simply do not exist at a national scale,” Pinheiro said. It would also “obscure the real-world pattern we are trying to measure.”
Gilbert Welch, MD, noted that adjusting for these individual-level cancer risk factors “would certainly attenuate the associations.”
“That said, it wouldn’t be crazy to suggest marriage drives some of these risk factors,” said Welch, general internist and senior investigator at the Center for Surgery and Public Health, Brigham and Women’s Hospital, Boston. Married couples benefit from combined incomes and shared expenses, and “may well help support individuals in making healthy choices (like not smoking).”
But, he added, “it would be crazy to suggest that the reason to get married is to lower cancer risk.”
The authors flagged a study limitation — the fact that ever-married status lumps together people who are currently married, divorced, and widowed, and these groups may have different risk profiles. Additionally, “individuals in strained or abusive marriages may not experience protective social benefits,” while those in long-term cohabiting relationships classified as never-married may experience high levels of support, the authors wrote.
Overall, though, Pinheiro clarified that the main finding is “not about marriage as a causal agent, but about identifying a large population group, the never-married, with a consistently higher cancer burden that has been largely overlooked in public health practice and cancer prevention efforts.”
Linda Waite, professor, Department of Sociology, University of Chicago, who wasn’t involved in the study, wasn’t surprised by the findings. For men, not having a spouse may “disadvantage” them in ways that might increase cancer risk.
Unmarried men are more likely to drink and smoke heavily, which increase cancer risk, she said. A spouse may also influence health awareness and decisions, such as noticing suspicious symptoms, pushing their partner to see a doctor, or helping manage their partner’s care.
Plus, “for both men and women, having a spouse may improve medical care by giving each partner a companion for medical appointments and another person to help manage risks of disease,” Waite said.
The study had no commercial funding. Pinheiro and Waite had no relevant disclosures.
A version of this article first appeared on Medscape.com.
Adults who have never been married had a higher cancer risk than their married or previously married peers, with patterns observed across many major cancer types and particularly strong for cancers linked to infections, smoking, and reproductive factors, new data suggest.
The findings are based on a large, population-based cancer registry analysis of more than 4 million cases, making it the largest study of its kind in the US.
First author Paulo Pinheiro, PhD, cautioned, however, that the study does not suggest that marriage itself is protective.
"As with any observational study, we cannot establish causation, and unmeasured factors may contribute to the associations,” said Pinheiro, with Sylvester Comprehensive Cancer Center, University of Miami Health System, in Miami.
Marital status may, however, help identify groups with different patterns of cancer risk, which likely reflect social and lifestyle behaviors rather than a direct causal effect, Pinheiro explained.
Married individuals, for instance, are less likely to smoke — a known cancer risk factor — and more likely to have children and undergo cancer screening, which can influence cancer incidence through reproductive effects and screening, including earlier detection and removal of precancerous lesions.
"Marital status is therefore best understood as a marker of those accumulated factors," Pinheiro said.
The study was published online on April 8 in Cancer Research Communications.
Filling a Data Gap
Marriage has consistently been associated with earlier cancer diagnosis and improved survival among those with cancer, but its relationship to cancer incidence remains less clear.
To address that gap, researchers analyzed data from 12 US states that included demographic and cancer information for more than 4.2 million cancer cases diagnosed between 2015 and 2022.
The analysis included more than 500 million person-years at risk in adults 30 years or older, representing an annual population of more than 62 million. The never-married group comprised about 19% of the total population — 22% were men and 17% were women.
Compared with ever-married individuals, never-married men and women had higher cancer incidence across many major cancer types, racial and ethnic groups, and age groups.
Overall, cancer rates were about 68% higher in never-married men and 85% higher in never-married women compared with their ever-married counterparts (incidence rate ratios [IRRs], 1.68 and 1.85, respectively).
Never-married Black men had the highest overall cancer rates (1600 per 100,000), whereas married Black men had significantly lower rates than married White men (752.6 vs 836.2 per 100,000), suggesting complex interactions between marital status and structural factors, the researchers noted.
Site-specific patterns revealed clues to potential mechanisms linking marital status and cancer.
Compared with ever-married individuals, never-married people had the highest excess risks for human papillomavirus-related cancers — about five times higher for anal cancer in men (IRR, 5.04) and approaching three times higher for cervical cancer in women (IRR, 2.64).
Other strong associations between never-married individuals and cancer risk were observed for smoking-related cancers, including lung (IRR, 2.1 for both men and women) and esophageal cancers (IRR, 2.4 in men and 2.7 in women), and malignancies including liver (IRR, 2.3 for both men and women), bladder (IRR, 2.3 women only), and colorectal (IRR, 2.1 women only) cancers.
Among women, the higher incidence of ovarian and uterine cancers (IRR, 2.4 for both) among the never-married group supports the influence of reproductive mechanisms, such as giving birth, on cancer risk.
The association between marital status and cancer risk was weaker for breast, prostate, and thyroid cancers (with IRRs < 2), suggesting potentially less modifiable etiologies.
Overall, “methodologically, it is quite robust, particularly in its clear framing of ever- vs never-married individuals and the use of standardized incidence rates and regression modeling,” Pinheiro said.
The analysis did not adjust for individual-level risk factors such as smoking, diet, physical activity, or alcohol use — factors that may partly explain the observed associations.
Adjusting for these lifestyle and health behavior factors at the individual level would require detailed information on these behaviors, and “data at that level simply do not exist at a national scale,” Pinheiro said. It would also “obscure the real-world pattern we are trying to measure.”
Gilbert Welch, MD, noted that adjusting for these individual-level cancer risk factors “would certainly attenuate the associations.”
“That said, it wouldn’t be crazy to suggest marriage drives some of these risk factors,” said Welch, general internist and senior investigator at the Center for Surgery and Public Health, Brigham and Women’s Hospital, Boston. Married couples benefit from combined incomes and shared expenses, and “may well help support individuals in making healthy choices (like not smoking).”
But, he added, “it would be crazy to suggest that the reason to get married is to lower cancer risk.”
The authors flagged a study limitation — the fact that ever-married status lumps together people who are currently married, divorced, and widowed, and these groups may have different risk profiles. Additionally, “individuals in strained or abusive marriages may not experience protective social benefits,” while those in long-term cohabiting relationships classified as never-married may experience high levels of support, the authors wrote.
Overall, though, Pinheiro clarified that the main finding is “not about marriage as a causal agent, but about identifying a large population group, the never-married, with a consistently higher cancer burden that has been largely overlooked in public health practice and cancer prevention efforts.”
Linda Waite, professor, Department of Sociology, University of Chicago, who wasn’t involved in the study, wasn’t surprised by the findings. For men, not having a spouse may “disadvantage” them in ways that might increase cancer risk.
Unmarried men are more likely to drink and smoke heavily, which increase cancer risk, she said. A spouse may also influence health awareness and decisions, such as noticing suspicious symptoms, pushing their partner to see a doctor, or helping manage their partner’s care.
Plus, “for both men and women, having a spouse may improve medical care by giving each partner a companion for medical appointments and another person to help manage risks of disease,” Waite said.
The study had no commercial funding. Pinheiro and Waite had no relevant disclosures.
A version of this article first appeared on Medscape.com.
VHA CRC Screening Has Blind Spots, Disparities
TOPLINE:
More than 1 in 8 colorectal cancer (CRC) cases among veterans occur outside the standard screening age of 50-75 years or those with high-risk personal or family history. High-risk patients face > 6 times the risk for CRC compared with average-risk patients aged 50-75 years who are up to date with screening, while Black patients have > 50% higher risk compared with White patients.
METHODOLOGY:
Researchers conducted a case-control analysis using Veterans Health Administration (VHA) Corporate Data Warehouse data from 2012-2018 at 2 sites: Veterans Affairs (VA) New York Harbor Health Care System and VA Puget Sound Health Care System.
Participants included 3714 cases among veterans with CRC matched to 14,856 controls (4:1), with matching on age (± 3 years), sex, and facility site; each control was used once.
Screening categories included 5 groups by age (50-75 years vs < 50 years or > 75 years), screening up-to-date status, and high-risk status (inflammatory bowel disease, hereditary cancer syndromes, or family history).
CRC screening was considered up to date if US Preventive Services Task Force-recommended tests were completed on time (colonoscopy ≤ 10 years; guaiac-based fecal occult blood test or fecal immunochemical test ≤ 1 year).
TAKEAWAY:
Compared with category 1 (age 50-75 years and up-to-date with screening), CRC was associated with category 4 (age < 50 years or > 75 years and not up to date) (odds ratio [OR], 1.40; 95% CI, 1.11-1.78), and category 5 (high risk) (OR, 6.23; 95% CI, 5.06-7.66).
Race and comorbidity associations included higher CRC risk for Black vs White patients (OR, 1.54; 95% CI, 1.37-1.73), and higher CRC risk with diabetes (OR, 1.65; 95% CI, 1.51-1.81) and alcohol use disorder (OR, 1.53; 95% CI, 1.35-1.73).
Among 3714 CRC cases, 71.1% occurred in individuals aged 50-75 years not up to date with screening.
A total of 12.5% of CRC cases occurred in people outside age 50-75 or with high-risk personal or family history, suggesting that conventional screening-adherence metrics may miss a clinically relevant minority.
IN PRACTICE:
“The conventional measure of CRC screening, focused on average-risk individuals aged 50 to 75, does not reflect screening status in an important minority of CRC patients," the authors wrote.
SOURCE:
The study was led by researchers at NYU Grossman School of Medicine and Veterans Affairs New York Harbor Health Care System, and published online July 9, 2026 in Medicine.
LIMITATIONS:
The study population consisted predominantly of male veterans (97.1%), who tend to be older and have more comorbidities compared with the US population, which may limit the generalizability of findings to other populations. Researchers defined screening status cross-sectionally relative to a single point in time rather than assessing longitudinal screening adherence, which may not fully capture the consistency of screening over time that is likely important for defining CRC risk. Veterans may receive screening at non-VA medical facilities, potentially leading to incomplete documentation of screening status and important covariates such as race, ethnicity, and comorbidities. The possibility of residual confounding cannot be excluded despite adjustment for multiple risk factors in the analysis.
DISCLOSURES:
This study received support from NIH grant K08 CA230162 and the AGA Caroline Craig Augustyn & Damian Augustyn Award in Digestive Cancer, both awarded to Peter S. Liang. Liang disclosed receiving research support from Freenome and serving on the advisory boards for Guardant Health and Natera. The remaining authors reported no funding or conflicts of interest to disclose.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.
TOPLINE:
More than 1 in 8 colorectal cancer (CRC) cases among veterans occur outside the standard screening age of 50-75 years or those with high-risk personal or family history. High-risk patients face > 6 times the risk for CRC compared with average-risk patients aged 50-75 years who are up to date with screening, while Black patients have > 50% higher risk compared with White patients.
METHODOLOGY:
Researchers conducted a case-control analysis using Veterans Health Administration (VHA) Corporate Data Warehouse data from 2012-2018 at 2 sites: Veterans Affairs (VA) New York Harbor Health Care System and VA Puget Sound Health Care System.
Participants included 3714 cases among veterans with CRC matched to 14,856 controls (4:1), with matching on age (± 3 years), sex, and facility site; each control was used once.
Screening categories included 5 groups by age (50-75 years vs < 50 years or > 75 years), screening up-to-date status, and high-risk status (inflammatory bowel disease, hereditary cancer syndromes, or family history).
CRC screening was considered up to date if US Preventive Services Task Force-recommended tests were completed on time (colonoscopy ≤ 10 years; guaiac-based fecal occult blood test or fecal immunochemical test ≤ 1 year).
TAKEAWAY:
Compared with category 1 (age 50-75 years and up-to-date with screening), CRC was associated with category 4 (age < 50 years or > 75 years and not up to date) (odds ratio [OR], 1.40; 95% CI, 1.11-1.78), and category 5 (high risk) (OR, 6.23; 95% CI, 5.06-7.66).
Race and comorbidity associations included higher CRC risk for Black vs White patients (OR, 1.54; 95% CI, 1.37-1.73), and higher CRC risk with diabetes (OR, 1.65; 95% CI, 1.51-1.81) and alcohol use disorder (OR, 1.53; 95% CI, 1.35-1.73).
Among 3714 CRC cases, 71.1% occurred in individuals aged 50-75 years not up to date with screening.
A total of 12.5% of CRC cases occurred in people outside age 50-75 or with high-risk personal or family history, suggesting that conventional screening-adherence metrics may miss a clinically relevant minority.
IN PRACTICE:
“The conventional measure of CRC screening, focused on average-risk individuals aged 50 to 75, does not reflect screening status in an important minority of CRC patients," the authors wrote.
SOURCE:
The study was led by researchers at NYU Grossman School of Medicine and Veterans Affairs New York Harbor Health Care System, and published online July 9, 2026 in Medicine.
LIMITATIONS:
The study population consisted predominantly of male veterans (97.1%), who tend to be older and have more comorbidities compared with the US population, which may limit the generalizability of findings to other populations. Researchers defined screening status cross-sectionally relative to a single point in time rather than assessing longitudinal screening adherence, which may not fully capture the consistency of screening over time that is likely important for defining CRC risk. Veterans may receive screening at non-VA medical facilities, potentially leading to incomplete documentation of screening status and important covariates such as race, ethnicity, and comorbidities. The possibility of residual confounding cannot be excluded despite adjustment for multiple risk factors in the analysis.
DISCLOSURES:
This study received support from NIH grant K08 CA230162 and the AGA Caroline Craig Augustyn & Damian Augustyn Award in Digestive Cancer, both awarded to Peter S. Liang. Liang disclosed receiving research support from Freenome and serving on the advisory boards for Guardant Health and Natera. The remaining authors reported no funding or conflicts of interest to disclose.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.
TOPLINE:
More than 1 in 8 colorectal cancer (CRC) cases among veterans occur outside the standard screening age of 50-75 years or those with high-risk personal or family history. High-risk patients face > 6 times the risk for CRC compared with average-risk patients aged 50-75 years who are up to date with screening, while Black patients have > 50% higher risk compared with White patients.
METHODOLOGY:
Researchers conducted a case-control analysis using Veterans Health Administration (VHA) Corporate Data Warehouse data from 2012-2018 at 2 sites: Veterans Affairs (VA) New York Harbor Health Care System and VA Puget Sound Health Care System.
Participants included 3714 cases among veterans with CRC matched to 14,856 controls (4:1), with matching on age (± 3 years), sex, and facility site; each control was used once.
Screening categories included 5 groups by age (50-75 years vs < 50 years or > 75 years), screening up-to-date status, and high-risk status (inflammatory bowel disease, hereditary cancer syndromes, or family history).
CRC screening was considered up to date if US Preventive Services Task Force-recommended tests were completed on time (colonoscopy ≤ 10 years; guaiac-based fecal occult blood test or fecal immunochemical test ≤ 1 year).
TAKEAWAY:
Compared with category 1 (age 50-75 years and up-to-date with screening), CRC was associated with category 4 (age < 50 years or > 75 years and not up to date) (odds ratio [OR], 1.40; 95% CI, 1.11-1.78), and category 5 (high risk) (OR, 6.23; 95% CI, 5.06-7.66).
Race and comorbidity associations included higher CRC risk for Black vs White patients (OR, 1.54; 95% CI, 1.37-1.73), and higher CRC risk with diabetes (OR, 1.65; 95% CI, 1.51-1.81) and alcohol use disorder (OR, 1.53; 95% CI, 1.35-1.73).
Among 3714 CRC cases, 71.1% occurred in individuals aged 50-75 years not up to date with screening.
A total of 12.5% of CRC cases occurred in people outside age 50-75 or with high-risk personal or family history, suggesting that conventional screening-adherence metrics may miss a clinically relevant minority.
IN PRACTICE:
“The conventional measure of CRC screening, focused on average-risk individuals aged 50 to 75, does not reflect screening status in an important minority of CRC patients," the authors wrote.
SOURCE:
The study was led by researchers at NYU Grossman School of Medicine and Veterans Affairs New York Harbor Health Care System, and published online July 9, 2026 in Medicine.
LIMITATIONS:
The study population consisted predominantly of male veterans (97.1%), who tend to be older and have more comorbidities compared with the US population, which may limit the generalizability of findings to other populations. Researchers defined screening status cross-sectionally relative to a single point in time rather than assessing longitudinal screening adherence, which may not fully capture the consistency of screening over time that is likely important for defining CRC risk. Veterans may receive screening at non-VA medical facilities, potentially leading to incomplete documentation of screening status and important covariates such as race, ethnicity, and comorbidities. The possibility of residual confounding cannot be excluded despite adjustment for multiple risk factors in the analysis.
DISCLOSURES:
This study received support from NIH grant K08 CA230162 and the AGA Caroline Craig Augustyn & Damian Augustyn Award in Digestive Cancer, both awarded to Peter S. Liang. Liang disclosed receiving research support from Freenome and serving on the advisory boards for Guardant Health and Natera. The remaining authors reported no funding or conflicts of interest to disclose.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.
Hidradenitis Suppurativa Associated With Elevated Risks for Multiple Cancer Types
Hidradenitis Suppurativa Associated With Elevated Risks for Multiple Cancer Types
TOPLINE:
In a meta-analysis, patients with hidradenitis suppurativa (HS) faced a more than 80% higher risk for cancer overall than the general population, with particularly elevated risks for gastrointestinal, head and neck, hematologic, and respiratory system cancers.
METHODOLOGY:
- Researchers conducted a meta-analysis including 11 studies from PubMed, Embase, and Web of Science databases published between 2001 and 2024; these studies examined the risk for cancer in patients with HS compared with that in the general population.
- These studies included 624,721 patients diagnosed with HS (mean age, 33.6-43.8 years) and 393,691,636 control individuals from the general population.
- Researchers performed an inverse variance-weighted random-effects analysis to calculate pooled odds ratios (ORs) for cancer overall and specific cancer subtypes.
- Cancer types were categorized into 11 groups for subgroup analysis: bone and soft tissue cancers, breast cancer, central nervous system cancers, endocrine-related cancers, gastrointestinal cancers, head and neck cancers, hematologic cancers, respiratory system cancers, skin cancers, urogenital cancers, and unspecified cancers.
TAKEAWAY:
- Patients with HS demonstrated a significantly higher risk for cancer overall than control individuals (crude OR, 1.82; P = .018).
- Patients with HS showed an increased risk for gastrointestinal cancers (crude OR, 1.61; P = .0002), head and neck cancers (crude OR, 2.41; P = .00001), hematologic cancers (crude OR, 1.71; P = .00005), and respiratory system cancers (crude OR, 1.81; P = .04).
- Patients with HS demonstrated significantly elevated risks for both Hodgkin lymphoma (OR, 2.44; P = .0001) and non-Hodgkin lymphoma (OR, 1.15; P = .012).
- A non-significant increased risk for skin cancer was observed in patients with HS (crude OR, 1.48; P = .08). No increased risks for bone and soft tissue cancers, central nervous system cancers, breast cancer, or urogenital cancers were observed in patients with HS.
IN PRACTICE:
"HS was associated with an increased overall risk of cancer, including several specific subtypes, compared with controls," the authors wrote, suggesting that "studies are adjusting for confounders and assess long-term associations between HS and cancer risk are highly needed to investigate which factors contribute to this cancer risk."
SOURCE:
This study was led by Daniel Isufi, Department of Dermatology and Allergy, Copenhagen University Hospital-Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark. It was published online on March 11, 2026, in Dermatology and Therapy.
LIMITATIONS:
Limited data on cancer subtypes hindered meta-analyses of rare cancers, and the lack of reporting on anti‑inflammatory treatment and disease severity prevented subgroup analyses. Most studies originated from North America, introducing potential geographic bias. No study reported BMI, and ethnicity was poorly documented. Only few studies adjusted for key confounders (smoking, obesity, and alcohol intake), limiting the determination of whether the increased risk for cancer was due to HS itself or shared lifestyle and metabolic factors.
DISCLOSURES:
This study did not receive any funding or sponsorship. Two authors reported receiving research grant funding from the LEO Foundation and having other ties with various other sources.
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:
In a meta-analysis, patients with hidradenitis suppurativa (HS) faced a more than 80% higher risk for cancer overall than the general population, with particularly elevated risks for gastrointestinal, head and neck, hematologic, and respiratory system cancers.
METHODOLOGY:
- Researchers conducted a meta-analysis including 11 studies from PubMed, Embase, and Web of Science databases published between 2001 and 2024; these studies examined the risk for cancer in patients with HS compared with that in the general population.
- These studies included 624,721 patients diagnosed with HS (mean age, 33.6-43.8 years) and 393,691,636 control individuals from the general population.
- Researchers performed an inverse variance-weighted random-effects analysis to calculate pooled odds ratios (ORs) for cancer overall and specific cancer subtypes.
- Cancer types were categorized into 11 groups for subgroup analysis: bone and soft tissue cancers, breast cancer, central nervous system cancers, endocrine-related cancers, gastrointestinal cancers, head and neck cancers, hematologic cancers, respiratory system cancers, skin cancers, urogenital cancers, and unspecified cancers.
TAKEAWAY:
- Patients with HS demonstrated a significantly higher risk for cancer overall than control individuals (crude OR, 1.82; P = .018).
- Patients with HS showed an increased risk for gastrointestinal cancers (crude OR, 1.61; P = .0002), head and neck cancers (crude OR, 2.41; P = .00001), hematologic cancers (crude OR, 1.71; P = .00005), and respiratory system cancers (crude OR, 1.81; P = .04).
- Patients with HS demonstrated significantly elevated risks for both Hodgkin lymphoma (OR, 2.44; P = .0001) and non-Hodgkin lymphoma (OR, 1.15; P = .012).
- A non-significant increased risk for skin cancer was observed in patients with HS (crude OR, 1.48; P = .08). No increased risks for bone and soft tissue cancers, central nervous system cancers, breast cancer, or urogenital cancers were observed in patients with HS.
IN PRACTICE:
"HS was associated with an increased overall risk of cancer, including several specific subtypes, compared with controls," the authors wrote, suggesting that "studies are adjusting for confounders and assess long-term associations between HS and cancer risk are highly needed to investigate which factors contribute to this cancer risk."
SOURCE:
This study was led by Daniel Isufi, Department of Dermatology and Allergy, Copenhagen University Hospital-Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark. It was published online on March 11, 2026, in Dermatology and Therapy.
LIMITATIONS:
Limited data on cancer subtypes hindered meta-analyses of rare cancers, and the lack of reporting on anti‑inflammatory treatment and disease severity prevented subgroup analyses. Most studies originated from North America, introducing potential geographic bias. No study reported BMI, and ethnicity was poorly documented. Only few studies adjusted for key confounders (smoking, obesity, and alcohol intake), limiting the determination of whether the increased risk for cancer was due to HS itself or shared lifestyle and metabolic factors.
DISCLOSURES:
This study did not receive any funding or sponsorship. Two authors reported receiving research grant funding from the LEO Foundation and having other ties with various other sources.
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:
In a meta-analysis, patients with hidradenitis suppurativa (HS) faced a more than 80% higher risk for cancer overall than the general population, with particularly elevated risks for gastrointestinal, head and neck, hematologic, and respiratory system cancers.
METHODOLOGY:
- Researchers conducted a meta-analysis including 11 studies from PubMed, Embase, and Web of Science databases published between 2001 and 2024; these studies examined the risk for cancer in patients with HS compared with that in the general population.
- These studies included 624,721 patients diagnosed with HS (mean age, 33.6-43.8 years) and 393,691,636 control individuals from the general population.
- Researchers performed an inverse variance-weighted random-effects analysis to calculate pooled odds ratios (ORs) for cancer overall and specific cancer subtypes.
- Cancer types were categorized into 11 groups for subgroup analysis: bone and soft tissue cancers, breast cancer, central nervous system cancers, endocrine-related cancers, gastrointestinal cancers, head and neck cancers, hematologic cancers, respiratory system cancers, skin cancers, urogenital cancers, and unspecified cancers.
TAKEAWAY:
- Patients with HS demonstrated a significantly higher risk for cancer overall than control individuals (crude OR, 1.82; P = .018).
- Patients with HS showed an increased risk for gastrointestinal cancers (crude OR, 1.61; P = .0002), head and neck cancers (crude OR, 2.41; P = .00001), hematologic cancers (crude OR, 1.71; P = .00005), and respiratory system cancers (crude OR, 1.81; P = .04).
- Patients with HS demonstrated significantly elevated risks for both Hodgkin lymphoma (OR, 2.44; P = .0001) and non-Hodgkin lymphoma (OR, 1.15; P = .012).
- A non-significant increased risk for skin cancer was observed in patients with HS (crude OR, 1.48; P = .08). No increased risks for bone and soft tissue cancers, central nervous system cancers, breast cancer, or urogenital cancers were observed in patients with HS.
IN PRACTICE:
"HS was associated with an increased overall risk of cancer, including several specific subtypes, compared with controls," the authors wrote, suggesting that "studies are adjusting for confounders and assess long-term associations between HS and cancer risk are highly needed to investigate which factors contribute to this cancer risk."
SOURCE:
This study was led by Daniel Isufi, Department of Dermatology and Allergy, Copenhagen University Hospital-Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark. It was published online on March 11, 2026, in Dermatology and Therapy.
LIMITATIONS:
Limited data on cancer subtypes hindered meta-analyses of rare cancers, and the lack of reporting on anti‑inflammatory treatment and disease severity prevented subgroup analyses. Most studies originated from North America, introducing potential geographic bias. No study reported BMI, and ethnicity was poorly documented. Only few studies adjusted for key confounders (smoking, obesity, and alcohol intake), limiting the determination of whether the increased risk for cancer was due to HS itself or shared lifestyle and metabolic factors.
DISCLOSURES:
This study did not receive any funding or sponsorship. Two authors reported receiving research grant funding from the LEO Foundation and having other ties with various other sources.
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.
Hidradenitis Suppurativa Associated With Elevated Risks for Multiple Cancer Types
Hidradenitis Suppurativa Associated With Elevated Risks for Multiple Cancer Types
“Colon Age” Tool Evaluates Early CRC Risk in Male Vets
TOPLINE: Interviews with 23 male veterans (aged 35-49 years) at average-risk for colorectal cancer (CRC) and 8 primary care practitioners (PCPs) found broad acceptability of the Colon Age concept, with 96% of patients agreeing to calculation. PCPs describe its potential use to support screening discussions (fecal immunochemical test [FIT] vs colonoscopy) but emphasize workflow barriers, requesting electronic medical record integration and “time neutral” implementation.
METHODOLOGY:
Researchers conducted semistructured qualitative interviews with 31 participants (23 male veteran patients aged 35-49 years and 8 PCPs) at the Richard L. Roudebush Veterans Affairs Medical Center between June and September 2022.
Patients were eligible if they were at average risk for CRC, had no prior screening (colonoscopy or fecal immunochemical test [FIT]), no inflammatory bowel disease, and no significant family history of CRC.
Interviews explored participants' experiences with CRC screening, understanding of the Colon Age tool, and perceived clinical use.
Audio-recorded interviews were transcribed, deidentified, and analyzed using the constant comparison method with open and focused coding phases until saturation was reached.
TAKEAWAY:
Among 23 male veteran patients (mean age 47 years), 96% agreed to have their Colon Age calculated; 68% had a Colon Age below their biological age, 14% higher than their biological age, and 18% equal to their biological age.
Patients accepted the Colon Age concept, finding it easy to understand and helpful for being informed about their health, though most were unaware of screening options beyond colonoscopy prior to the interview.
The 8 PCPs (mean age 53 years, 50% female, mean 29 years in practice) interviewed found the tool acceptable and useful for screening conversations, improving uptake, and facilitating shared decision-making, particularly in gray zone cases where screening decisions are unclear.
PCPs emphasized the need for the tool to be integrated into the electronic medical record system and expressed concerns about time commitment, consistency with practice guidelines, and the validation process, stating they would only use the tool if it were time neutral and evidence-based.
IN PRACTICE: “Although the age at which to begin colorectal cancer screening in the US was lowered to 45 years in 2018, uptake of screening in persons aged 45 to 49 has been slow,” wrote the authors of the study.
SOURCE:The study was led by researchers at the VA Center for Health Information and Communication. It was published online on July 15 in BMC Primary Care.
LIMITATIONS: The study was conducted at a single VA medical center in the Midwest and all patient participants were male, which may limit generalizability to nonveteran patients, female patients, and non-VA clinicians. The Colon Age tool has limitations, as it was based on a risk prediction model with modest discrimination, and the linkage to screening recommendations was based on arbitrary Surveillance, Epidemiology and End Results thresholds chosen by the tool developers. Additionally, the qualitative nature of the study with a small sample size may not capture the full range of perspectives across diverse health care settings and patient populations.
DISCLOSURES: The primary author received support from Health Services Research and Development, Veterans Administration. Funding for this project was provided by Richard L. Roudebush VA Medical Center Indianapolis, Indiana Center for Health Information, and Communication COIN funds. The authors reported no relevant 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.
TOPLINE: Interviews with 23 male veterans (aged 35-49 years) at average-risk for colorectal cancer (CRC) and 8 primary care practitioners (PCPs) found broad acceptability of the Colon Age concept, with 96% of patients agreeing to calculation. PCPs describe its potential use to support screening discussions (fecal immunochemical test [FIT] vs colonoscopy) but emphasize workflow barriers, requesting electronic medical record integration and “time neutral” implementation.
METHODOLOGY:
Researchers conducted semistructured qualitative interviews with 31 participants (23 male veteran patients aged 35-49 years and 8 PCPs) at the Richard L. Roudebush Veterans Affairs Medical Center between June and September 2022.
Patients were eligible if they were at average risk for CRC, had no prior screening (colonoscopy or fecal immunochemical test [FIT]), no inflammatory bowel disease, and no significant family history of CRC.
Interviews explored participants' experiences with CRC screening, understanding of the Colon Age tool, and perceived clinical use.
Audio-recorded interviews were transcribed, deidentified, and analyzed using the constant comparison method with open and focused coding phases until saturation was reached.
TAKEAWAY:
Among 23 male veteran patients (mean age 47 years), 96% agreed to have their Colon Age calculated; 68% had a Colon Age below their biological age, 14% higher than their biological age, and 18% equal to their biological age.
Patients accepted the Colon Age concept, finding it easy to understand and helpful for being informed about their health, though most were unaware of screening options beyond colonoscopy prior to the interview.
The 8 PCPs (mean age 53 years, 50% female, mean 29 years in practice) interviewed found the tool acceptable and useful for screening conversations, improving uptake, and facilitating shared decision-making, particularly in gray zone cases where screening decisions are unclear.
PCPs emphasized the need for the tool to be integrated into the electronic medical record system and expressed concerns about time commitment, consistency with practice guidelines, and the validation process, stating they would only use the tool if it were time neutral and evidence-based.
IN PRACTICE: “Although the age at which to begin colorectal cancer screening in the US was lowered to 45 years in 2018, uptake of screening in persons aged 45 to 49 has been slow,” wrote the authors of the study.
SOURCE:The study was led by researchers at the VA Center for Health Information and Communication. It was published online on July 15 in BMC Primary Care.
LIMITATIONS: The study was conducted at a single VA medical center in the Midwest and all patient participants were male, which may limit generalizability to nonveteran patients, female patients, and non-VA clinicians. The Colon Age tool has limitations, as it was based on a risk prediction model with modest discrimination, and the linkage to screening recommendations was based on arbitrary Surveillance, Epidemiology and End Results thresholds chosen by the tool developers. Additionally, the qualitative nature of the study with a small sample size may not capture the full range of perspectives across diverse health care settings and patient populations.
DISCLOSURES: The primary author received support from Health Services Research and Development, Veterans Administration. Funding for this project was provided by Richard L. Roudebush VA Medical Center Indianapolis, Indiana Center for Health Information, and Communication COIN funds. The authors reported no relevant 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.
TOPLINE: Interviews with 23 male veterans (aged 35-49 years) at average-risk for colorectal cancer (CRC) and 8 primary care practitioners (PCPs) found broad acceptability of the Colon Age concept, with 96% of patients agreeing to calculation. PCPs describe its potential use to support screening discussions (fecal immunochemical test [FIT] vs colonoscopy) but emphasize workflow barriers, requesting electronic medical record integration and “time neutral” implementation.
METHODOLOGY:
Researchers conducted semistructured qualitative interviews with 31 participants (23 male veteran patients aged 35-49 years and 8 PCPs) at the Richard L. Roudebush Veterans Affairs Medical Center between June and September 2022.
Patients were eligible if they were at average risk for CRC, had no prior screening (colonoscopy or fecal immunochemical test [FIT]), no inflammatory bowel disease, and no significant family history of CRC.
Interviews explored participants' experiences with CRC screening, understanding of the Colon Age tool, and perceived clinical use.
Audio-recorded interviews were transcribed, deidentified, and analyzed using the constant comparison method with open and focused coding phases until saturation was reached.
TAKEAWAY:
Among 23 male veteran patients (mean age 47 years), 96% agreed to have their Colon Age calculated; 68% had a Colon Age below their biological age, 14% higher than their biological age, and 18% equal to their biological age.
Patients accepted the Colon Age concept, finding it easy to understand and helpful for being informed about their health, though most were unaware of screening options beyond colonoscopy prior to the interview.
The 8 PCPs (mean age 53 years, 50% female, mean 29 years in practice) interviewed found the tool acceptable and useful for screening conversations, improving uptake, and facilitating shared decision-making, particularly in gray zone cases where screening decisions are unclear.
PCPs emphasized the need for the tool to be integrated into the electronic medical record system and expressed concerns about time commitment, consistency with practice guidelines, and the validation process, stating they would only use the tool if it were time neutral and evidence-based.
IN PRACTICE: “Although the age at which to begin colorectal cancer screening in the US was lowered to 45 years in 2018, uptake of screening in persons aged 45 to 49 has been slow,” wrote the authors of the study.
SOURCE:The study was led by researchers at the VA Center for Health Information and Communication. It was published online on July 15 in BMC Primary Care.
LIMITATIONS: The study was conducted at a single VA medical center in the Midwest and all patient participants were male, which may limit generalizability to nonveteran patients, female patients, and non-VA clinicians. The Colon Age tool has limitations, as it was based on a risk prediction model with modest discrimination, and the linkage to screening recommendations was based on arbitrary Surveillance, Epidemiology and End Results thresholds chosen by the tool developers. Additionally, the qualitative nature of the study with a small sample size may not capture the full range of perspectives across diverse health care settings and patient populations.
DISCLOSURES: The primary author received support from Health Services Research and Development, Veterans Administration. Funding for this project was provided by Richard L. Roudebush VA Medical Center Indianapolis, Indiana Center for Health Information, and Communication COIN funds. The authors reported no relevant 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.