Oncology

For patients with cancer, the determining factor in whether they pursue mental health services is often whether their oncologist explicitly says it is a good idea, a psychologist said during the July Association of VA Hematology and Oncology (AVAHO) seminar in Long Beach, California, on treating veterans with renal cell carcinoma (RCC).

Kysa Christie, PhD, of the West Los Angeles Veterans Affairs Medical Center, presented findings from a 2018 study in which researchers asked Swiss patients with cancer whether their oncologist discussed their emotional health with them. 

In terms of boosting intake, it did not matter if oncologists acknowledged distress or pointed out that psychosocial services existed. Instead, a direct recommendation made a difference, increasing the likelihood of using the services over a 4-month period after initial assessment (odds ratio, 6.27).

“What it took was, ‘I really recommend this. This is something that I would want you to try,’” Christie said. 

Oncologists are crucial links between patients and mental health services, Christie said: “If people don’t ask about [distress], you’re not going to see it, but it’s there. Distress is the norm, right? It is not a weakness. It is something that we expect to see.”

Christie noted that an estimated 20% of cancer patients have major depressive disorder, and 35% to 40% have a diagnosable psychiatric condition. RCC shows disproportionately high rates of mental strain. According to Christie, research suggests that about three-fourths of the population report elevated levels of distress as evidenced by patients who scored ≥ 5 on the NCCN Distress Thermometer. Patients with cancer have an estimated 20% higher risk of suicide, especially during the first 12 months after diagnosis and at end of life, she added.

“Early during a diagnosis phase, where you’re having a lot of tests being done, you know something is happening. But you don’t know what,” Christie said. “It could be very serious. That’s just a lot of stress to hold and not know how to plan for.”

After diagnosis, routine could set in and lower distress, she said. Then terminal illness may spike it back up again. Does mental health treatment work in patients with cancer?

“There’s a really strong body of evidence-based treatments for depression, anxiety, adjustment disorders, and coping with different cancers,” Christie said. But it is a step too far to expect patients to ask for help while they are juggling appointments, tests, infusions, and more. “It’s a big ask, right? It’s setting people up for failure.”

To help, Christie said she is embedded with a medical oncology team and routinely talks with the staff about which patients may need help. “One thing I like to do is try to have brief visits with veterans and introduce myself when they come to clinic. I treat it like an opt-out rather than an opt-in program: I’ll just pop into the exam room. They don’t have to ask to see me.”

Christie focuses on open-ended questions and talks about resources ranging from support groups and brief appointments to extensive individual therapy. 

Another approach is a strategy known as the “warm handoff,” when an oncologist directly introduces a patient to a mental health professional. “It’s a transfer of care in front of the veteran: It’s much more time-efficient than putting in a referral.”

Christie explained how this can work. A clinician will ask her to meet with a patient during an appointment, perhaps in a couple minutes.

“Then I pop into the room, and the oncologist says, ‘Thanks for joining us. This is Mr. Jones. He has been experiencing feelings of anxiety and sadness, and we’d appreciate your help in exploring some options that might help.’  I turn to the patient and ask, ‘What more would you add?’ Then I either take Mr. Jones back to my office or stay in clinic, and we’re off to the races.”

Christie reported no disclosures.

For patients with cancer, the determining factor in whether they pursue mental health services is often whether their oncologist explicitly says it is a good idea, a psychologist said during the July Association of VA Hematology and Oncology (AVAHO) seminar in Long Beach, California, on treating veterans with renal cell carcinoma (RCC).

Kysa Christie, PhD, of the West Los Angeles Veterans Affairs Medical Center, presented findings from a 2018 study in which researchers asked Swiss patients with cancer whether their oncologist discussed their emotional health with them. 

In terms of boosting intake, it did not matter if oncologists acknowledged distress or pointed out that psychosocial services existed. Instead, a direct recommendation made a difference, increasing the likelihood of using the services over a 4-month period after initial assessment (odds ratio, 6.27).

“What it took was, ‘I really recommend this. This is something that I would want you to try,’” Christie said. 

Oncologists are crucial links between patients and mental health services, Christie said: “If people don’t ask about [distress], you’re not going to see it, but it’s there. Distress is the norm, right? It is not a weakness. It is something that we expect to see.”

Christie noted that an estimated 20% of cancer patients have major depressive disorder, and 35% to 40% have a diagnosable psychiatric condition. RCC shows disproportionately high rates of mental strain. According to Christie, research suggests that about three-fourths of the population report elevated levels of distress as evidenced by patients who scored ≥ 5 on the NCCN Distress Thermometer. Patients with cancer have an estimated 20% higher risk of suicide, especially during the first 12 months after diagnosis and at end of life, she added.

“Early during a diagnosis phase, where you’re having a lot of tests being done, you know something is happening. But you don’t know what,” Christie said. “It could be very serious. That’s just a lot of stress to hold and not know how to plan for.”

After diagnosis, routine could set in and lower distress, she said. Then terminal illness may spike it back up again. Does mental health treatment work in patients with cancer?

“There’s a really strong body of evidence-based treatments for depression, anxiety, adjustment disorders, and coping with different cancers,” Christie said. But it is a step too far to expect patients to ask for help while they are juggling appointments, tests, infusions, and more. “It’s a big ask, right? It’s setting people up for failure.”

To help, Christie said she is embedded with a medical oncology team and routinely talks with the staff about which patients may need help. “One thing I like to do is try to have brief visits with veterans and introduce myself when they come to clinic. I treat it like an opt-out rather than an opt-in program: I’ll just pop into the exam room. They don’t have to ask to see me.”

Christie focuses on open-ended questions and talks about resources ranging from support groups and brief appointments to extensive individual therapy. 

Another approach is a strategy known as the “warm handoff,” when an oncologist directly introduces a patient to a mental health professional. “It’s a transfer of care in front of the veteran: It’s much more time-efficient than putting in a referral.”

Christie explained how this can work. A clinician will ask her to meet with a patient during an appointment, perhaps in a couple minutes.

“Then I pop into the room, and the oncologist says, ‘Thanks for joining us. This is Mr. Jones. He has been experiencing feelings of anxiety and sadness, and we’d appreciate your help in exploring some options that might help.’  I turn to the patient and ask, ‘What more would you add?’ Then I either take Mr. Jones back to my office or stay in clinic, and we’re off to the races.”

Christie reported no disclosures.

For patients with cancer, the determining factor in whether they pursue mental health services is often whether their oncologist explicitly says it is a good idea, a psychologist said during the July Association of VA Hematology and Oncology (AVAHO) seminar in Long Beach, California, on treating veterans with renal cell carcinoma (RCC).

Kysa Christie, PhD, of the West Los Angeles Veterans Affairs Medical Center, presented findings from a 2018 study in which researchers asked Swiss patients with cancer whether their oncologist discussed their emotional health with them. 

In terms of boosting intake, it did not matter if oncologists acknowledged distress or pointed out that psychosocial services existed. Instead, a direct recommendation made a difference, increasing the likelihood of using the services over a 4-month period after initial assessment (odds ratio, 6.27).

“What it took was, ‘I really recommend this. This is something that I would want you to try,’” Christie said. 

Oncologists are crucial links between patients and mental health services, Christie said: “If people don’t ask about [distress], you’re not going to see it, but it’s there. Distress is the norm, right? It is not a weakness. It is something that we expect to see.”

Christie noted that an estimated 20% of cancer patients have major depressive disorder, and 35% to 40% have a diagnosable psychiatric condition. RCC shows disproportionately high rates of mental strain. According to Christie, research suggests that about three-fourths of the population report elevated levels of distress as evidenced by patients who scored ≥ 5 on the NCCN Distress Thermometer. Patients with cancer have an estimated 20% higher risk of suicide, especially during the first 12 months after diagnosis and at end of life, she added.

“Early during a diagnosis phase, where you’re having a lot of tests being done, you know something is happening. But you don’t know what,” Christie said. “It could be very serious. That’s just a lot of stress to hold and not know how to plan for.”

After diagnosis, routine could set in and lower distress, she said. Then terminal illness may spike it back up again. Does mental health treatment work in patients with cancer?

“There’s a really strong body of evidence-based treatments for depression, anxiety, adjustment disorders, and coping with different cancers,” Christie said. But it is a step too far to expect patients to ask for help while they are juggling appointments, tests, infusions, and more. “It’s a big ask, right? It’s setting people up for failure.”

To help, Christie said she is embedded with a medical oncology team and routinely talks with the staff about which patients may need help. “One thing I like to do is try to have brief visits with veterans and introduce myself when they come to clinic. I treat it like an opt-out rather than an opt-in program: I’ll just pop into the exam room. They don’t have to ask to see me.”

Christie focuses on open-ended questions and talks about resources ranging from support groups and brief appointments to extensive individual therapy. 

Another approach is a strategy known as the “warm handoff,” when an oncologist directly introduces a patient to a mental health professional. “It’s a transfer of care in front of the veteran: It’s much more time-efficient than putting in a referral.”

Christie explained how this can work. A clinician will ask her to meet with a patient during an appointment, perhaps in a couple minutes.

“Then I pop into the room, and the oncologist says, ‘Thanks for joining us. This is Mr. Jones. He has been experiencing feelings of anxiety and sadness, and we’d appreciate your help in exploring some options that might help.’  I turn to the patient and ask, ‘What more would you add?’ Then I either take Mr. Jones back to my office or stay in clinic, and we’re off to the races.”

Christie reported no disclosures.

Colorectal cancer (CRC) is the second-leading cause of cancer-related deaths in the United States, with an estimated 52,550 deaths in 2023.¹ However, the disease burden varies among different segments of the population.² While both CRC incidence and mortality have been decreasing due to screening and advances in treatment, there are disparities in incidence and mortality across the sociodemographic spectrum including race, ethnicity, education, and income.^1-4 While CRC incidence is decreasing for older adults, it is increasing among those aged < 55 years.⁵ The incidence of CRC in adults aged 40 to 54 years has increased by 0.5% to 1.3% annually since the mid-1990s.⁶ The US Preventive Services Task Force now recommends starting CRC screening at age 45 years for asymptomatic adults with average risk.⁷

Disparities also exist across geographical boundaries and living environment. Rural Americans faces additional challenges in health and lifestyle that can affect CRC outcomes. Compared to their urban counterparts, rural residents are more likely to be older, have lower levels of education, higher levels of poverty, lack health insurance, and less access to health care practitioners (HCPs).^8-10 Geographic proximity, defined as travel time or physical distance to a health facility, has been recognized as a predictor of inferior outcomes.¹¹ These aspects of rural living may pose challenges for accessing care for CRC screening and treatment.^11-13 National and local studies have shown disparities in CRC screening rates, incidence, and mortality between rural and urban populations.^14-16

It is unclear whether rural/urban disparities persist under the Veterans Health Administration (VHA) health care delivery model. This study examined differences in baseline characteristics and mortality between rural and urban veterans newly diagnosed with CRC. We also focused on a subpopulation aged ≤ 45 years.

Methods

This study extracted national data from the US Department of Veterans Affairs (VA) Corporate Data Warehouse (CDW) hosted in the VA Informatics and Computing Infrastructure (VINCI) environment. VINCI is an initiative to improve access to VA data and facilitate the analysis of these data while ensuring veterans’ privacy and data security.¹⁷ CDW is the VHA business intelligence information repository, which extracts data from clinical and nonclinical sources following prescribed and validated protocols. Data extracted included demographics, diagnosis, and procedure codes for both inpatient and outpatient encounters, vital signs, and vital status. This study used data previously extracted from a national cohort of veterans that encompassed all patients who received a group of commonly prescribed medications, such as statins, proton pump inhibitors, histamine-2 blockers, acetaminophen-containing products, and hydrocortisone-containing skin applications. This cohort encompassed 8,648,754 veterans, from whom 2,460,727 had encounters during fiscal years (FY) 2016 to 2021 (study period). The cohort was used to ensure that subjects were VHA patients, allowing them to adequately capture their clinical profiles.

Patients were identified as rural or urban based on their residence address at the date of their first diagnosis of CRC. The Geospatial Service Support Center (GSSC) aggregates and updates veterans’ residence address records for all enrolled veterans from the National Change of Address database. The data contain 1 record per enrollee. GSSC Geocoded Enrollee File contains enrollee addresses and their rurality indicators, categorized as urban, rural, or highly rural.¹⁸ Rurality is defined by the Rural Urban Commuting Area (RUCA) categories developed by the Department of Agriculture and the Health Resources and Services Administration of the US Department of Health and Human Services.¹⁹ Urban areas had RUCA codes of 1.0 to 1.1, and highly rural areas had RUCA scores of 10.0. All other areas were classified as rural. Since the proportion of veterans from highly rural areas was small, we included residents from highly rural areas in the rural residents’ group.

Inclusion and Exclusion Criteria

All veterans newly diagnosed with CRC from FY 2016 to 2021 were included. We used the ninth and tenth clinical modification revisions of the International Classification of Diseases (ICD-9-CM and ICD-10-CM) to define CRC diagnosis (Supplemental materials).^4,20 To ensure that patients were newly diagnosed with CRC, this study excluded patients with a previous ICD-9-CM code for CRC diagnosis since FY 2003.

Comorbidities were identified using diagnosis and procedure codes from inpatient and outpatient encounters, which were used to calculate the Charlson Comorbidity Index (CCI) at the time of CRC diagnosis using the weighted method described by Schneeweiss et al.²¹ We defined CRC high-risk conditions and CRC screening tests, including flexible sigmoidoscopy and stool tests, as described in previous studies (Supplemental materials).²⁰

The main outcome was total mortality. The date of death was extracted from the VHA Death Ascertainment File, which contains mortality data from the Master Person Index file in CDW and the Social Security Administration Death Master File. We used the date of death from any cause, as cause of death was not available.

A propensity score (PS) was created to match rural (including highly rural) and urban residents at a ratio of 1:1. Using a standard procedure described in prior publications, multivariable logistic regression used all baseline characteristics to estimate the PS and perform nearest-number matching without replacement.^22,23 A caliper of 0.01 maximized the matched cohort size and achieved balance (Supplemental materials). We then examined the balance of baseline characteristics between PS-matched groups.

Analyses

Cox proportional hazards regression analysis estimated the hazard ratio (HR) of death in rural residents compared to urban residents in the PS-matched cohort. The outcome event was the date of death during the study’s follow-up period (defined as period from first CRC diagnosis to death or study end), with censoring at the study’s end date (September 30, 2021). The proportional hazards assumption was assessed by inspecting the Kaplan-Meier curves. Multiple analyses examined the HR of total mortality in the PS-matched cohort, stratified by sex, race, and ethnicity. We also examined the HR of total mortality stratified by duration of follow-up.

Another PS-matching analysis among veterans aged ≤ 45 years was performed using the same techniques described earlier in this article. We performed a Cox proportional hazards regression analysis to compare mortality in PS-matched urban and rural veterans aged ≤ 45 years. The HR of death in all veterans aged ≤ 45 years (before PS-matching) was estimated using Cox proportional hazard regression analysis, adjusting for PS.

Dichotomous variables were compared using X² tests and continuous variables were compared using t tests. Baseline characteristics with missing values were converted into categorical variables and the proportion of subjects with missing values was equalized between treatment groups after PS-matching. For subgroup analysis, we examined the HR of total mortality in each subgroup using separate Cox proportional hazards regression models similar to the primary analysis but adjusted for PS. Due to multiple comparisons in the subgroup analysis, the findings should be considered exploratory. Statistical tests were 2-tailed, and significance was defined as P < .05. Data management and statistical analyses were conducted from June 2022 to January 2023 using STATA, Version 17. The VA Orlando Healthcare System Institutional Review Board approved the study and waived requirements for informed consent because only deidentified data were used.

Results

After excluding 49 patients (Supplemental materials, available at doi:10.12788/fp.0560), we identified 30,219 veterans with newly diagnosed CRC between FY 2016 to 2021 (Table 1). Of these, 19,422 (64.3%) resided in urban areas and 10,797 (35.7%) resided in rural areas (Table 2). The mean (SD) duration from the first CRC diagnosis to death or study end was 832 (640) days, and the median (IQR) was 723 (246–1330) days. Overall, incident CRC diagnoses were numerically highest in FY 2016 and lowest in FY 2020 (Figure 1). Patients with CRC in rural areas vs urban areas were significantly older (mean, 71.2 years vs 70.8 years, respectively; P < .001), more likely to be male (96.7% vs 95.7%, respectively; P < .001), more likely to be White (83.6% vs 67.8%, respectively; P < .001) and more likely to be non-Hispanic (92.2% vs 87.5%, respectively; P < .001). In terms of general health, rural veterans with CRC were more likely to be overweight or obese (81.5% rural vs 78.5% urban; P < .001) but had fewer mean comorbidities as measured by CCI (5.66 rural vs 5.90 urban; P < .001). A higher proportion of rural veterans with CRC had received stool-based (fecal occult blood test or fecal immunochemical test) CRC screening tests (61.6% rural vs 57.2% urban; P < .001). Fewer rural patients presented with systemic symptoms or signs within 1 year of CRC diagnosis (54.4% rural vs 57.5% urban, P < .001). Among urban patients with CRC, 6959 (35.8%) deaths were observed, compared with 3766 (34.9%) among rural patients (P = .10).

There were 21,568 PS-matched veterans: 10,784 in each group. In the PS-matched cohort, baseline characteristics were similar between veterans in urban and rural communities, including age, sex, race/ethnicity, body mass index, and comorbidities. Among rural patients with CRC, 3763 deaths (34.9%) were observed compared with 3702 (34.3%) among urban veterans. There was no significant difference in the HR of mortality between rural and urban CRC residents (HR, 1.01; 95% CI, 0.97-1.06; P = .53) (Figure 2).

Among veterans aged ≤ 45 years, 551 were diagnosed with CRC (391 urban and 160 rural). We PS-matched 142 pairs of urban and rural veterans without residual differences in baseline characteristics (Table 3). There was no significant difference in the HR of mortality between rural and urban veterans aged ≤ 45 years (HR, 0.97; 95% CI, 0.57-1.63; P = .90) (Figure 2). Similarly, no difference in mortality was observed adjusting for PS between all rural and urban veterans aged ≤ 45 years (HR, 1.03; 95% CI, 0.67-1.59; P = .88).

There was no difference in total mortality between rural and urban veterans in any subgroup except for American Indian or Alaska Native veterans (HR, 2.41; 95% CI, 1.29-4.50; P = .006) (Table 4).

Discussion

This study examined characteristics of patients with CRC between urban and rural areas among veterans who were VHA patients. Similar to other studies, rural veterans with CRC were older, more likely to be White, and were obese, but exhibited fewer comorbidities (lower CCI and lower incidence of congestive heart failure, dementia, hemiplegia, kidney diseases, liver diseases and AIDS, but higher incidence of chronic obstructive lung disease).^8,16 The incidence of CRC in this study population was lowest in FY 2020, which was reported by the Centers for Disease Control and Prevention and is attributed to COVID-19 pandemic disruption of health services.²⁴ The overall mortality in this study was similar to rates reported in other studies from the VA Central Cancer Registry.⁴ In the PS-matched cohort, where baseline characteristics were similar between urban and rural patients with CRC, we found no disparities in CRC-specific mortality between veterans in rural and urban areas. Additionally, when analysis was restricted to veterans aged ≤ 45 years, the results remained consistent.

Subgroup analyses showed no significant difference in mortality between rural and urban areas by sex, race or ethnicity, except rural American Indian or Alaska Native veterans who had double the mortality of their urban counterparts (HR, 2.41; 95% CI, 1.29-4.50; P = .006). This finding is difficult to interpret due to the small number of events and the wide CI. While with a Bonferroni correction the adjusted P value was .08, which is not statistically significant, a previous study found that although CRC incidence was lower overall in American Indian or Alaska Native populations compared to non-Hispanic White populations, CRC incidence was higher among American Indian or Alaska Native individuals in some areas such as Alaska and the Northern Plains.^25,26 Studies have noted that rural American Indian/Alaska Native populations experience greater poverty, less access to broadband internet, and limited access to care, contributing to poorer cancer outcomes and lower survival.²⁷ Thus, the finding of disparity in mortality between rural and urban American Indian or Alaska Native veterans warrants further study.

Other studies have raised concerns that CRC disproportionately affects adults in rural areas with higher mortality rates.^14-16 These disparities arise from sociodemographic factors and modifiable risk factors, including physical activity, dietary patterns, access to cancer screening, and gaps in quality treatment resources.^16,28 These factors operate at multiple levels: from individual, local health system, to community and policy.^2,27 For example, a South Carolina study (1996–2016) found that residents in rural areas were more likely to be diagnosed with advanced CRC, possibly indicating lower rates of CRC screening in rural areas. They also had higher likelihood of death from CRC.¹⁵ However, the study did not include any clinical parameters, such as comorbidities or obesity. A statewide, population-based study in Utah showed that rural men experienced a lower CRC survival in their unadjusted analysis.¹⁶ However, the study was small, with only 3948 urban and 712 rural residents. Additionally, there was no difference in total mortality in the whole cohort (HR, 0.96; 95% CI, 0.86-1.07) or in CRC-specific death (HR, 0.93; 95% CI, 0.81-1.08). A nationwide study also showed that CRC mortality rates were 8% higher in nonmetropolitan or rural areas than in the most urbanized areas containing large metropolitan counties.²⁹ However, this study did not include descriptions of clinical confounders, such as comorbidities, making it difficult to ascertain whether the difference in CRC mortality was due to rurality or differences in baseline risk characteristics.

In this study, the lack of CRC-specific mortality disparities may be attributed to the structures and practices of VHA health care. Recent studies have noted that mortality of several chronic medical conditions treated at the VHA was lower than at non-VHA hospitals.^30,31 One study that measured the quality of nonmetastatic CRC care based on National Comprehensive Cancer Network guidelines showed that > 72% of VHA patients received guideline-concordant care for each diagnostic and therapeutic measure, except for follow-up colonoscopy timing, which appear to be similar or superior to that of the private sector.^30,32,33 Some of the VA initiative for CRC screening may bypass the urban-rurality divide such as the mailed fecal immunochemical test program for CRC. This program was implemented at the onset of the COVID-19 pandemic to avoid disruptions of medical care.³⁴ Rural patients are more likely to undergo fecal immunochemical testing when compared to urban patients in this data. Beyond clinical care, the VHA uses processes to tackle social determinants of health such as housing, food security, and transportation, promoting equal access to health care, and promoting cultural competency among HCPs.^35-37

The results suggest that solutions to CRC disparities between rural and urban areas need to consider known barriers to rural health care, including transportation, diminished rural health care workforce, and other social determinants of health.^9,10,27,38 VHA makes considerable efforts to provide equitable care to all enrolled veterans, including specific programs for rural veterans, including ongoing outreach.³⁹ This study demonstrated lack of disparity in CRC-specific mortality in veterans receiving VHA care, highlighting the importance of these efforts.

Strengths and Limitations

This study used the VHA cohort to compare patient characteristics and mortality between patients with CRC residing in rural and urban areas. The study provides nationwide perspectives on CRC across the geographical spectrum and used a longitudinal cohort with prolonged follow-up to account for comorbidities.

However, the study compared a cohort of rural and urban veterans enrolled in the VHA; hence, the results may not reflect CRC outcomes in veterans without access to VHA care. Rurality has been independently associated with decreased likelihood of meeting CRC screening guidelines among veterans and military service members.³⁸ This study lacked sufficient information to compare CRC staging or treatment modalities among veterans. Although the data cannot identify CRC stage, the proportions of patients with metastatic CRC at diagnosis and CRC location were similar between groups. The study did not have information on their care outside of VHA setting.

This study could not ascertain whether disparities existed in CRC treatment modality since rural residence may result in referral to community-based CRC care, which did not appear in the data. To address these limitations, we used death from any cause as the primary outcome, since death is a hard outcome and is not subject to ascertainment bias. The relatively short follow-up time is another limitation, though subgroup analysis by follow-up did not show significant differences. Despite PS matching, residual unmeasured confounding may exist between urban and rural groups. The predominantly White, male VHA population with high CCI may limit the generalizability of the results.

Conclusions

Rural VHA enrollees had similar survival rates after CRC diagnosis compared to their urban counterparts in a PS-matched analysis. The VHA models of care—including mailed CRC screening tools, several socioeconomic determinants of health (housing, food security, and transportation), and promoting equal access to health care, as well as cultural competency among HCPs—HCPs—may help alleviate disparities across the rural-urban spectrum. The VHA should continue efforts to enroll veterans and provide comprehensive coordinated care in community partnerships.

Colorectal cancer (CRC) is the second-leading cause of cancer-related deaths in the United States, with an estimated 52,550 deaths in 2023.¹ However, the disease burden varies among different segments of the population.² While both CRC incidence and mortality have been decreasing due to screening and advances in treatment, there are disparities in incidence and mortality across the sociodemographic spectrum including race, ethnicity, education, and income.^1-4 While CRC incidence is decreasing for older adults, it is increasing among those aged < 55 years.⁵ The incidence of CRC in adults aged 40 to 54 years has increased by 0.5% to 1.3% annually since the mid-1990s.⁶ The US Preventive Services Task Force now recommends starting CRC screening at age 45 years for asymptomatic adults with average risk.⁷

Disparities also exist across geographical boundaries and living environment. Rural Americans faces additional challenges in health and lifestyle that can affect CRC outcomes. Compared to their urban counterparts, rural residents are more likely to be older, have lower levels of education, higher levels of poverty, lack health insurance, and less access to health care practitioners (HCPs).^8-10 Geographic proximity, defined as travel time or physical distance to a health facility, has been recognized as a predictor of inferior outcomes.¹¹ These aspects of rural living may pose challenges for accessing care for CRC screening and treatment.^11-13 National and local studies have shown disparities in CRC screening rates, incidence, and mortality between rural and urban populations.^14-16

It is unclear whether rural/urban disparities persist under the Veterans Health Administration (VHA) health care delivery model. This study examined differences in baseline characteristics and mortality between rural and urban veterans newly diagnosed with CRC. We also focused on a subpopulation aged ≤ 45 years.

Methods

This study extracted national data from the US Department of Veterans Affairs (VA) Corporate Data Warehouse (CDW) hosted in the VA Informatics and Computing Infrastructure (VINCI) environment. VINCI is an initiative to improve access to VA data and facilitate the analysis of these data while ensuring veterans’ privacy and data security.¹⁷ CDW is the VHA business intelligence information repository, which extracts data from clinical and nonclinical sources following prescribed and validated protocols. Data extracted included demographics, diagnosis, and procedure codes for both inpatient and outpatient encounters, vital signs, and vital status. This study used data previously extracted from a national cohort of veterans that encompassed all patients who received a group of commonly prescribed medications, such as statins, proton pump inhibitors, histamine-2 blockers, acetaminophen-containing products, and hydrocortisone-containing skin applications. This cohort encompassed 8,648,754 veterans, from whom 2,460,727 had encounters during fiscal years (FY) 2016 to 2021 (study period). The cohort was used to ensure that subjects were VHA patients, allowing them to adequately capture their clinical profiles.

Patients were identified as rural or urban based on their residence address at the date of their first diagnosis of CRC. The Geospatial Service Support Center (GSSC) aggregates and updates veterans’ residence address records for all enrolled veterans from the National Change of Address database. The data contain 1 record per enrollee. GSSC Geocoded Enrollee File contains enrollee addresses and their rurality indicators, categorized as urban, rural, or highly rural.¹⁸ Rurality is defined by the Rural Urban Commuting Area (RUCA) categories developed by the Department of Agriculture and the Health Resources and Services Administration of the US Department of Health and Human Services.¹⁹ Urban areas had RUCA codes of 1.0 to 1.1, and highly rural areas had RUCA scores of 10.0. All other areas were classified as rural. Since the proportion of veterans from highly rural areas was small, we included residents from highly rural areas in the rural residents’ group.

Inclusion and Exclusion Criteria

All veterans newly diagnosed with CRC from FY 2016 to 2021 were included. We used the ninth and tenth clinical modification revisions of the International Classification of Diseases (ICD-9-CM and ICD-10-CM) to define CRC diagnosis (Supplemental materials).^4,20 To ensure that patients were newly diagnosed with CRC, this study excluded patients with a previous ICD-9-CM code for CRC diagnosis since FY 2003.

Comorbidities were identified using diagnosis and procedure codes from inpatient and outpatient encounters, which were used to calculate the Charlson Comorbidity Index (CCI) at the time of CRC diagnosis using the weighted method described by Schneeweiss et al.²¹ We defined CRC high-risk conditions and CRC screening tests, including flexible sigmoidoscopy and stool tests, as described in previous studies (Supplemental materials).²⁰

The main outcome was total mortality. The date of death was extracted from the VHA Death Ascertainment File, which contains mortality data from the Master Person Index file in CDW and the Social Security Administration Death Master File. We used the date of death from any cause, as cause of death was not available.

A propensity score (PS) was created to match rural (including highly rural) and urban residents at a ratio of 1:1. Using a standard procedure described in prior publications, multivariable logistic regression used all baseline characteristics to estimate the PS and perform nearest-number matching without replacement.^22,23 A caliper of 0.01 maximized the matched cohort size and achieved balance (Supplemental materials). We then examined the balance of baseline characteristics between PS-matched groups.

Analyses

Cox proportional hazards regression analysis estimated the hazard ratio (HR) of death in rural residents compared to urban residents in the PS-matched cohort. The outcome event was the date of death during the study’s follow-up period (defined as period from first CRC diagnosis to death or study end), with censoring at the study’s end date (September 30, 2021). The proportional hazards assumption was assessed by inspecting the Kaplan-Meier curves. Multiple analyses examined the HR of total mortality in the PS-matched cohort, stratified by sex, race, and ethnicity. We also examined the HR of total mortality stratified by duration of follow-up.

Another PS-matching analysis among veterans aged ≤ 45 years was performed using the same techniques described earlier in this article. We performed a Cox proportional hazards regression analysis to compare mortality in PS-matched urban and rural veterans aged ≤ 45 years. The HR of death in all veterans aged ≤ 45 years (before PS-matching) was estimated using Cox proportional hazard regression analysis, adjusting for PS.

Dichotomous variables were compared using X² tests and continuous variables were compared using t tests. Baseline characteristics with missing values were converted into categorical variables and the proportion of subjects with missing values was equalized between treatment groups after PS-matching. For subgroup analysis, we examined the HR of total mortality in each subgroup using separate Cox proportional hazards regression models similar to the primary analysis but adjusted for PS. Due to multiple comparisons in the subgroup analysis, the findings should be considered exploratory. Statistical tests were 2-tailed, and significance was defined as P < .05. Data management and statistical analyses were conducted from June 2022 to January 2023 using STATA, Version 17. The VA Orlando Healthcare System Institutional Review Board approved the study and waived requirements for informed consent because only deidentified data were used.

Results

After excluding 49 patients (Supplemental materials, available at doi:10.12788/fp.0560), we identified 30,219 veterans with newly diagnosed CRC between FY 2016 to 2021 (Table 1). Of these, 19,422 (64.3%) resided in urban areas and 10,797 (35.7%) resided in rural areas (Table 2). The mean (SD) duration from the first CRC diagnosis to death or study end was 832 (640) days, and the median (IQR) was 723 (246–1330) days. Overall, incident CRC diagnoses were numerically highest in FY 2016 and lowest in FY 2020 (Figure 1). Patients with CRC in rural areas vs urban areas were significantly older (mean, 71.2 years vs 70.8 years, respectively; P < .001), more likely to be male (96.7% vs 95.7%, respectively; P < .001), more likely to be White (83.6% vs 67.8%, respectively; P < .001) and more likely to be non-Hispanic (92.2% vs 87.5%, respectively; P < .001). In terms of general health, rural veterans with CRC were more likely to be overweight or obese (81.5% rural vs 78.5% urban; P < .001) but had fewer mean comorbidities as measured by CCI (5.66 rural vs 5.90 urban; P < .001). A higher proportion of rural veterans with CRC had received stool-based (fecal occult blood test or fecal immunochemical test) CRC screening tests (61.6% rural vs 57.2% urban; P < .001). Fewer rural patients presented with systemic symptoms or signs within 1 year of CRC diagnosis (54.4% rural vs 57.5% urban, P < .001). Among urban patients with CRC, 6959 (35.8%) deaths were observed, compared with 3766 (34.9%) among rural patients (P = .10).

There were 21,568 PS-matched veterans: 10,784 in each group. In the PS-matched cohort, baseline characteristics were similar between veterans in urban and rural communities, including age, sex, race/ethnicity, body mass index, and comorbidities. Among rural patients with CRC, 3763 deaths (34.9%) were observed compared with 3702 (34.3%) among urban veterans. There was no significant difference in the HR of mortality between rural and urban CRC residents (HR, 1.01; 95% CI, 0.97-1.06; P = .53) (Figure 2).

Among veterans aged ≤ 45 years, 551 were diagnosed with CRC (391 urban and 160 rural). We PS-matched 142 pairs of urban and rural veterans without residual differences in baseline characteristics (Table 3). There was no significant difference in the HR of mortality between rural and urban veterans aged ≤ 45 years (HR, 0.97; 95% CI, 0.57-1.63; P = .90) (Figure 2). Similarly, no difference in mortality was observed adjusting for PS between all rural and urban veterans aged ≤ 45 years (HR, 1.03; 95% CI, 0.67-1.59; P = .88).

There was no difference in total mortality between rural and urban veterans in any subgroup except for American Indian or Alaska Native veterans (HR, 2.41; 95% CI, 1.29-4.50; P = .006) (Table 4).

Discussion

This study examined characteristics of patients with CRC between urban and rural areas among veterans who were VHA patients. Similar to other studies, rural veterans with CRC were older, more likely to be White, and were obese, but exhibited fewer comorbidities (lower CCI and lower incidence of congestive heart failure, dementia, hemiplegia, kidney diseases, liver diseases and AIDS, but higher incidence of chronic obstructive lung disease).^8,16 The incidence of CRC in this study population was lowest in FY 2020, which was reported by the Centers for Disease Control and Prevention and is attributed to COVID-19 pandemic disruption of health services.²⁴ The overall mortality in this study was similar to rates reported in other studies from the VA Central Cancer Registry.⁴ In the PS-matched cohort, where baseline characteristics were similar between urban and rural patients with CRC, we found no disparities in CRC-specific mortality between veterans in rural and urban areas. Additionally, when analysis was restricted to veterans aged ≤ 45 years, the results remained consistent.

Subgroup analyses showed no significant difference in mortality between rural and urban areas by sex, race or ethnicity, except rural American Indian or Alaska Native veterans who had double the mortality of their urban counterparts (HR, 2.41; 95% CI, 1.29-4.50; P = .006). This finding is difficult to interpret due to the small number of events and the wide CI. While with a Bonferroni correction the adjusted P value was .08, which is not statistically significant, a previous study found that although CRC incidence was lower overall in American Indian or Alaska Native populations compared to non-Hispanic White populations, CRC incidence was higher among American Indian or Alaska Native individuals in some areas such as Alaska and the Northern Plains.^25,26 Studies have noted that rural American Indian/Alaska Native populations experience greater poverty, less access to broadband internet, and limited access to care, contributing to poorer cancer outcomes and lower survival.²⁷ Thus, the finding of disparity in mortality between rural and urban American Indian or Alaska Native veterans warrants further study.

Other studies have raised concerns that CRC disproportionately affects adults in rural areas with higher mortality rates.^14-16 These disparities arise from sociodemographic factors and modifiable risk factors, including physical activity, dietary patterns, access to cancer screening, and gaps in quality treatment resources.^16,28 These factors operate at multiple levels: from individual, local health system, to community and policy.^2,27 For example, a South Carolina study (1996–2016) found that residents in rural areas were more likely to be diagnosed with advanced CRC, possibly indicating lower rates of CRC screening in rural areas. They also had higher likelihood of death from CRC.¹⁵ However, the study did not include any clinical parameters, such as comorbidities or obesity. A statewide, population-based study in Utah showed that rural men experienced a lower CRC survival in their unadjusted analysis.¹⁶ However, the study was small, with only 3948 urban and 712 rural residents. Additionally, there was no difference in total mortality in the whole cohort (HR, 0.96; 95% CI, 0.86-1.07) or in CRC-specific death (HR, 0.93; 95% CI, 0.81-1.08). A nationwide study also showed that CRC mortality rates were 8% higher in nonmetropolitan or rural areas than in the most urbanized areas containing large metropolitan counties.²⁹ However, this study did not include descriptions of clinical confounders, such as comorbidities, making it difficult to ascertain whether the difference in CRC mortality was due to rurality or differences in baseline risk characteristics.

In this study, the lack of CRC-specific mortality disparities may be attributed to the structures and practices of VHA health care. Recent studies have noted that mortality of several chronic medical conditions treated at the VHA was lower than at non-VHA hospitals.^30,31 One study that measured the quality of nonmetastatic CRC care based on National Comprehensive Cancer Network guidelines showed that > 72% of VHA patients received guideline-concordant care for each diagnostic and therapeutic measure, except for follow-up colonoscopy timing, which appear to be similar or superior to that of the private sector.^30,32,33 Some of the VA initiative for CRC screening may bypass the urban-rurality divide such as the mailed fecal immunochemical test program for CRC. This program was implemented at the onset of the COVID-19 pandemic to avoid disruptions of medical care.³⁴ Rural patients are more likely to undergo fecal immunochemical testing when compared to urban patients in this data. Beyond clinical care, the VHA uses processes to tackle social determinants of health such as housing, food security, and transportation, promoting equal access to health care, and promoting cultural competency among HCPs.^35-37

The results suggest that solutions to CRC disparities between rural and urban areas need to consider known barriers to rural health care, including transportation, diminished rural health care workforce, and other social determinants of health.^9,10,27,38 VHA makes considerable efforts to provide equitable care to all enrolled veterans, including specific programs for rural veterans, including ongoing outreach.³⁹ This study demonstrated lack of disparity in CRC-specific mortality in veterans receiving VHA care, highlighting the importance of these efforts.

Strengths and Limitations

This study used the VHA cohort to compare patient characteristics and mortality between patients with CRC residing in rural and urban areas. The study provides nationwide perspectives on CRC across the geographical spectrum and used a longitudinal cohort with prolonged follow-up to account for comorbidities.

However, the study compared a cohort of rural and urban veterans enrolled in the VHA; hence, the results may not reflect CRC outcomes in veterans without access to VHA care. Rurality has been independently associated with decreased likelihood of meeting CRC screening guidelines among veterans and military service members.³⁸ This study lacked sufficient information to compare CRC staging or treatment modalities among veterans. Although the data cannot identify CRC stage, the proportions of patients with metastatic CRC at diagnosis and CRC location were similar between groups. The study did not have information on their care outside of VHA setting.

This study could not ascertain whether disparities existed in CRC treatment modality since rural residence may result in referral to community-based CRC care, which did not appear in the data. To address these limitations, we used death from any cause as the primary outcome, since death is a hard outcome and is not subject to ascertainment bias. The relatively short follow-up time is another limitation, though subgroup analysis by follow-up did not show significant differences. Despite PS matching, residual unmeasured confounding may exist between urban and rural groups. The predominantly White, male VHA population with high CCI may limit the generalizability of the results.

Conclusions

Rural VHA enrollees had similar survival rates after CRC diagnosis compared to their urban counterparts in a PS-matched analysis. The VHA models of care—including mailed CRC screening tools, several socioeconomic determinants of health (housing, food security, and transportation), and promoting equal access to health care, as well as cultural competency among HCPs—HCPs—may help alleviate disparities across the rural-urban spectrum. The VHA should continue efforts to enroll veterans and provide comprehensive coordinated care in community partnerships.

Colorectal cancer (CRC) is the second-leading cause of cancer-related deaths in the United States, with an estimated 52,550 deaths in 2023.¹ However, the disease burden varies among different segments of the population.² While both CRC incidence and mortality have been decreasing due to screening and advances in treatment, there are disparities in incidence and mortality across the sociodemographic spectrum including race, ethnicity, education, and income.^1-4 While CRC incidence is decreasing for older adults, it is increasing among those aged < 55 years.⁵ The incidence of CRC in adults aged 40 to 54 years has increased by 0.5% to 1.3% annually since the mid-1990s.⁶ The US Preventive Services Task Force now recommends starting CRC screening at age 45 years for asymptomatic adults with average risk.⁷

Disparities also exist across geographical boundaries and living environment. Rural Americans faces additional challenges in health and lifestyle that can affect CRC outcomes. Compared to their urban counterparts, rural residents are more likely to be older, have lower levels of education, higher levels of poverty, lack health insurance, and less access to health care practitioners (HCPs).^8-10 Geographic proximity, defined as travel time or physical distance to a health facility, has been recognized as a predictor of inferior outcomes.¹¹ These aspects of rural living may pose challenges for accessing care for CRC screening and treatment.^11-13 National and local studies have shown disparities in CRC screening rates, incidence, and mortality between rural and urban populations.^14-16

It is unclear whether rural/urban disparities persist under the Veterans Health Administration (VHA) health care delivery model. This study examined differences in baseline characteristics and mortality between rural and urban veterans newly diagnosed with CRC. We also focused on a subpopulation aged ≤ 45 years.

Methods

This study extracted national data from the US Department of Veterans Affairs (VA) Corporate Data Warehouse (CDW) hosted in the VA Informatics and Computing Infrastructure (VINCI) environment. VINCI is an initiative to improve access to VA data and facilitate the analysis of these data while ensuring veterans’ privacy and data security.¹⁷ CDW is the VHA business intelligence information repository, which extracts data from clinical and nonclinical sources following prescribed and validated protocols. Data extracted included demographics, diagnosis, and procedure codes for both inpatient and outpatient encounters, vital signs, and vital status. This study used data previously extracted from a national cohort of veterans that encompassed all patients who received a group of commonly prescribed medications, such as statins, proton pump inhibitors, histamine-2 blockers, acetaminophen-containing products, and hydrocortisone-containing skin applications. This cohort encompassed 8,648,754 veterans, from whom 2,460,727 had encounters during fiscal years (FY) 2016 to 2021 (study period). The cohort was used to ensure that subjects were VHA patients, allowing them to adequately capture their clinical profiles.

Patients were identified as rural or urban based on their residence address at the date of their first diagnosis of CRC. The Geospatial Service Support Center (GSSC) aggregates and updates veterans’ residence address records for all enrolled veterans from the National Change of Address database. The data contain 1 record per enrollee. GSSC Geocoded Enrollee File contains enrollee addresses and their rurality indicators, categorized as urban, rural, or highly rural.¹⁸ Rurality is defined by the Rural Urban Commuting Area (RUCA) categories developed by the Department of Agriculture and the Health Resources and Services Administration of the US Department of Health and Human Services.¹⁹ Urban areas had RUCA codes of 1.0 to 1.1, and highly rural areas had RUCA scores of 10.0. All other areas were classified as rural. Since the proportion of veterans from highly rural areas was small, we included residents from highly rural areas in the rural residents’ group.

Inclusion and Exclusion Criteria

All veterans newly diagnosed with CRC from FY 2016 to 2021 were included. We used the ninth and tenth clinical modification revisions of the International Classification of Diseases (ICD-9-CM and ICD-10-CM) to define CRC diagnosis (Supplemental materials).^4,20 To ensure that patients were newly diagnosed with CRC, this study excluded patients with a previous ICD-9-CM code for CRC diagnosis since FY 2003.

Comorbidities were identified using diagnosis and procedure codes from inpatient and outpatient encounters, which were used to calculate the Charlson Comorbidity Index (CCI) at the time of CRC diagnosis using the weighted method described by Schneeweiss et al.²¹ We defined CRC high-risk conditions and CRC screening tests, including flexible sigmoidoscopy and stool tests, as described in previous studies (Supplemental materials).²⁰

The main outcome was total mortality. The date of death was extracted from the VHA Death Ascertainment File, which contains mortality data from the Master Person Index file in CDW and the Social Security Administration Death Master File. We used the date of death from any cause, as cause of death was not available.

A propensity score (PS) was created to match rural (including highly rural) and urban residents at a ratio of 1:1. Using a standard procedure described in prior publications, multivariable logistic regression used all baseline characteristics to estimate the PS and perform nearest-number matching without replacement.^22,23 A caliper of 0.01 maximized the matched cohort size and achieved balance (Supplemental materials). We then examined the balance of baseline characteristics between PS-matched groups.

Analyses

Cox proportional hazards regression analysis estimated the hazard ratio (HR) of death in rural residents compared to urban residents in the PS-matched cohort. The outcome event was the date of death during the study’s follow-up period (defined as period from first CRC diagnosis to death or study end), with censoring at the study’s end date (September 30, 2021). The proportional hazards assumption was assessed by inspecting the Kaplan-Meier curves. Multiple analyses examined the HR of total mortality in the PS-matched cohort, stratified by sex, race, and ethnicity. We also examined the HR of total mortality stratified by duration of follow-up.

Another PS-matching analysis among veterans aged ≤ 45 years was performed using the same techniques described earlier in this article. We performed a Cox proportional hazards regression analysis to compare mortality in PS-matched urban and rural veterans aged ≤ 45 years. The HR of death in all veterans aged ≤ 45 years (before PS-matching) was estimated using Cox proportional hazard regression analysis, adjusting for PS.

Dichotomous variables were compared using X² tests and continuous variables were compared using t tests. Baseline characteristics with missing values were converted into categorical variables and the proportion of subjects with missing values was equalized between treatment groups after PS-matching. For subgroup analysis, we examined the HR of total mortality in each subgroup using separate Cox proportional hazards regression models similar to the primary analysis but adjusted for PS. Due to multiple comparisons in the subgroup analysis, the findings should be considered exploratory. Statistical tests were 2-tailed, and significance was defined as P < .05. Data management and statistical analyses were conducted from June 2022 to January 2023 using STATA, Version 17. The VA Orlando Healthcare System Institutional Review Board approved the study and waived requirements for informed consent because only deidentified data were used.

Results

After excluding 49 patients (Supplemental materials, available at doi:10.12788/fp.0560), we identified 30,219 veterans with newly diagnosed CRC between FY 2016 to 2021 (Table 1). Of these, 19,422 (64.3%) resided in urban areas and 10,797 (35.7%) resided in rural areas (Table 2). The mean (SD) duration from the first CRC diagnosis to death or study end was 832 (640) days, and the median (IQR) was 723 (246–1330) days. Overall, incident CRC diagnoses were numerically highest in FY 2016 and lowest in FY 2020 (Figure 1). Patients with CRC in rural areas vs urban areas were significantly older (mean, 71.2 years vs 70.8 years, respectively; P < .001), more likely to be male (96.7% vs 95.7%, respectively; P < .001), more likely to be White (83.6% vs 67.8%, respectively; P < .001) and more likely to be non-Hispanic (92.2% vs 87.5%, respectively; P < .001). In terms of general health, rural veterans with CRC were more likely to be overweight or obese (81.5% rural vs 78.5% urban; P < .001) but had fewer mean comorbidities as measured by CCI (5.66 rural vs 5.90 urban; P < .001). A higher proportion of rural veterans with CRC had received stool-based (fecal occult blood test or fecal immunochemical test) CRC screening tests (61.6% rural vs 57.2% urban; P < .001). Fewer rural patients presented with systemic symptoms or signs within 1 year of CRC diagnosis (54.4% rural vs 57.5% urban, P < .001). Among urban patients with CRC, 6959 (35.8%) deaths were observed, compared with 3766 (34.9%) among rural patients (P = .10).

There were 21,568 PS-matched veterans: 10,784 in each group. In the PS-matched cohort, baseline characteristics were similar between veterans in urban and rural communities, including age, sex, race/ethnicity, body mass index, and comorbidities. Among rural patients with CRC, 3763 deaths (34.9%) were observed compared with 3702 (34.3%) among urban veterans. There was no significant difference in the HR of mortality between rural and urban CRC residents (HR, 1.01; 95% CI, 0.97-1.06; P = .53) (Figure 2).

Among veterans aged ≤ 45 years, 551 were diagnosed with CRC (391 urban and 160 rural). We PS-matched 142 pairs of urban and rural veterans without residual differences in baseline characteristics (Table 3). There was no significant difference in the HR of mortality between rural and urban veterans aged ≤ 45 years (HR, 0.97; 95% CI, 0.57-1.63; P = .90) (Figure 2). Similarly, no difference in mortality was observed adjusting for PS between all rural and urban veterans aged ≤ 45 years (HR, 1.03; 95% CI, 0.67-1.59; P = .88).

There was no difference in total mortality between rural and urban veterans in any subgroup except for American Indian or Alaska Native veterans (HR, 2.41; 95% CI, 1.29-4.50; P = .006) (Table 4).

Discussion

This study examined characteristics of patients with CRC between urban and rural areas among veterans who were VHA patients. Similar to other studies, rural veterans with CRC were older, more likely to be White, and were obese, but exhibited fewer comorbidities (lower CCI and lower incidence of congestive heart failure, dementia, hemiplegia, kidney diseases, liver diseases and AIDS, but higher incidence of chronic obstructive lung disease).^8,16 The incidence of CRC in this study population was lowest in FY 2020, which was reported by the Centers for Disease Control and Prevention and is attributed to COVID-19 pandemic disruption of health services.²⁴ The overall mortality in this study was similar to rates reported in other studies from the VA Central Cancer Registry.⁴ In the PS-matched cohort, where baseline characteristics were similar between urban and rural patients with CRC, we found no disparities in CRC-specific mortality between veterans in rural and urban areas. Additionally, when analysis was restricted to veterans aged ≤ 45 years, the results remained consistent.

Subgroup analyses showed no significant difference in mortality between rural and urban areas by sex, race or ethnicity, except rural American Indian or Alaska Native veterans who had double the mortality of their urban counterparts (HR, 2.41; 95% CI, 1.29-4.50; P = .006). This finding is difficult to interpret due to the small number of events and the wide CI. While with a Bonferroni correction the adjusted P value was .08, which is not statistically significant, a previous study found that although CRC incidence was lower overall in American Indian or Alaska Native populations compared to non-Hispanic White populations, CRC incidence was higher among American Indian or Alaska Native individuals in some areas such as Alaska and the Northern Plains.^25,26 Studies have noted that rural American Indian/Alaska Native populations experience greater poverty, less access to broadband internet, and limited access to care, contributing to poorer cancer outcomes and lower survival.²⁷ Thus, the finding of disparity in mortality between rural and urban American Indian or Alaska Native veterans warrants further study.

Other studies have raised concerns that CRC disproportionately affects adults in rural areas with higher mortality rates.^14-16 These disparities arise from sociodemographic factors and modifiable risk factors, including physical activity, dietary patterns, access to cancer screening, and gaps in quality treatment resources.^16,28 These factors operate at multiple levels: from individual, local health system, to community and policy.^2,27 For example, a South Carolina study (1996–2016) found that residents in rural areas were more likely to be diagnosed with advanced CRC, possibly indicating lower rates of CRC screening in rural areas. They also had higher likelihood of death from CRC.¹⁵ However, the study did not include any clinical parameters, such as comorbidities or obesity. A statewide, population-based study in Utah showed that rural men experienced a lower CRC survival in their unadjusted analysis.¹⁶ However, the study was small, with only 3948 urban and 712 rural residents. Additionally, there was no difference in total mortality in the whole cohort (HR, 0.96; 95% CI, 0.86-1.07) or in CRC-specific death (HR, 0.93; 95% CI, 0.81-1.08). A nationwide study also showed that CRC mortality rates were 8% higher in nonmetropolitan or rural areas than in the most urbanized areas containing large metropolitan counties.²⁹ However, this study did not include descriptions of clinical confounders, such as comorbidities, making it difficult to ascertain whether the difference in CRC mortality was due to rurality or differences in baseline risk characteristics.

In this study, the lack of CRC-specific mortality disparities may be attributed to the structures and practices of VHA health care. Recent studies have noted that mortality of several chronic medical conditions treated at the VHA was lower than at non-VHA hospitals.^30,31 One study that measured the quality of nonmetastatic CRC care based on National Comprehensive Cancer Network guidelines showed that > 72% of VHA patients received guideline-concordant care for each diagnostic and therapeutic measure, except for follow-up colonoscopy timing, which appear to be similar or superior to that of the private sector.^30,32,33 Some of the VA initiative for CRC screening may bypass the urban-rurality divide such as the mailed fecal immunochemical test program for CRC. This program was implemented at the onset of the COVID-19 pandemic to avoid disruptions of medical care.³⁴ Rural patients are more likely to undergo fecal immunochemical testing when compared to urban patients in this data. Beyond clinical care, the VHA uses processes to tackle social determinants of health such as housing, food security, and transportation, promoting equal access to health care, and promoting cultural competency among HCPs.^35-37

The results suggest that solutions to CRC disparities between rural and urban areas need to consider known barriers to rural health care, including transportation, diminished rural health care workforce, and other social determinants of health.^9,10,27,38 VHA makes considerable efforts to provide equitable care to all enrolled veterans, including specific programs for rural veterans, including ongoing outreach.³⁹ This study demonstrated lack of disparity in CRC-specific mortality in veterans receiving VHA care, highlighting the importance of these efforts.

Strengths and Limitations

This study used the VHA cohort to compare patient characteristics and mortality between patients with CRC residing in rural and urban areas. The study provides nationwide perspectives on CRC across the geographical spectrum and used a longitudinal cohort with prolonged follow-up to account for comorbidities.

However, the study compared a cohort of rural and urban veterans enrolled in the VHA; hence, the results may not reflect CRC outcomes in veterans without access to VHA care. Rurality has been independently associated with decreased likelihood of meeting CRC screening guidelines among veterans and military service members.³⁸ This study lacked sufficient information to compare CRC staging or treatment modalities among veterans. Although the data cannot identify CRC stage, the proportions of patients with metastatic CRC at diagnosis and CRC location were similar between groups. The study did not have information on their care outside of VHA setting.

This study could not ascertain whether disparities existed in CRC treatment modality since rural residence may result in referral to community-based CRC care, which did not appear in the data. To address these limitations, we used death from any cause as the primary outcome, since death is a hard outcome and is not subject to ascertainment bias. The relatively short follow-up time is another limitation, though subgroup analysis by follow-up did not show significant differences. Despite PS matching, residual unmeasured confounding may exist between urban and rural groups. The predominantly White, male VHA population with high CCI may limit the generalizability of the results.

Conclusions

Rural VHA enrollees had similar survival rates after CRC diagnosis compared to their urban counterparts in a PS-matched analysis. The VHA models of care—including mailed CRC screening tools, several socioeconomic determinants of health (housing, food security, and transportation), and promoting equal access to health care, as well as cultural competency among HCPs—HCPs—may help alleviate disparities across the rural-urban spectrum. The VHA should continue efforts to enroll veterans and provide comprehensive coordinated care in community partnerships.

The annual issue of Cancer Data Trends, produced in collaboration with the Association of VA Hematology/Oncology (AVAHO), highlights the latest research in some of the top cancers impacting US veterans. 

In this issue: 

1. Access, Race, and "Colon Age": Improving CRC Screening
2. Lung Cancer: Mortality Trends in Veterans and New Treatments
3. Racial Disparities, Germline Testing, and Improved Overall Survival in Prostate Cancer
4. Breast and Uterine Cancer: Screening Guidelines, Genetic Testing, and Mortality Trends
5. HCC Updates: Quality Care Framework and Risk Stratification Data
6. Rising Kidney Cancer Cases and Emerging Treatments for Veterans
7. Advances in Blood Cancer Care for Veterans
8. AI-Based Risk Stratification for Oropharyngeal Carcinomas: AIROC
9. Brain Cancer: Epidemiology, TBI, and New Treatments

The annual issue of Cancer Data Trends, produced in collaboration with the Association of VA Hematology/Oncology (AVAHO), highlights the latest research in some of the top cancers impacting US veterans. 

In this issue: 

1. Access, Race, and "Colon Age": Improving CRC Screening
2. Lung Cancer: Mortality Trends in Veterans and New Treatments
3. Racial Disparities, Germline Testing, and Improved Overall Survival in Prostate Cancer
4. Breast and Uterine Cancer: Screening Guidelines, Genetic Testing, and Mortality Trends
5. HCC Updates: Quality Care Framework and Risk Stratification Data
6. Rising Kidney Cancer Cases and Emerging Treatments for Veterans
7. Advances in Blood Cancer Care for Veterans
8. AI-Based Risk Stratification for Oropharyngeal Carcinomas: AIROC
9. Brain Cancer: Epidemiology, TBI, and New Treatments

The annual issue of Cancer Data Trends, produced in collaboration with the Association of VA Hematology/Oncology (AVAHO), highlights the latest research in some of the top cancers impacting US veterans. 

In this issue: 

1. Access, Race, and "Colon Age": Improving CRC Screening
2. Lung Cancer: Mortality Trends in Veterans and New Treatments
3. Racial Disparities, Germline Testing, and Improved Overall Survival in Prostate Cancer
4. Breast and Uterine Cancer: Screening Guidelines, Genetic Testing, and Mortality Trends
5. HCC Updates: Quality Care Framework and Risk Stratification Data
6. Rising Kidney Cancer Cases and Emerging Treatments for Veterans
7. Advances in Blood Cancer Care for Veterans
8. AI-Based Risk Stratification for Oropharyngeal Carcinomas: AIROC
9. Brain Cancer: Epidemiology, TBI, and New Treatments

ATHENS, Greece — At the 11th World Congress of Melanoma and 21st EADO Congress 2025, experts presented divergent perspectives on the merits of population-wide skin cancer screening programs vs more targeted approaches. The debate highlighted concerns about healthcare resource allocation, overdiagnosis, and the true impact of mass skin cancer screening on mortality.

Arguing against widespread screening, particularly in low-to-medium incidence countries like Spain, was Susana Puig, MD, the head of Dermatology at Hospital Clínic de Barcelona, University of Barcelona, and a dermatologist at Barnaclínic+, Barcelona, Spain.

“It’s not efficient. We visit too many healthy individuals to detect melanoma,” she said. “We need to focus on treating patients, not checking healthy people without any risk.”

Championing for population-wide screening was Peter Mohr, MD, a dermatologist at the Clinic of Dermatology in Elbe Klinikum Buxtehude, Buxtehude, Germany, who noted a disproportionate focus on treatment rather than prevention. “The ultimate goal of screening,” he said, “is to prevent advanced disease and reduce melanoma-specific mortality.”

 

Avoid Population-Based Screening

Presenting data from Germany, Puig noted that population-based screening starting at any age requires examining more than 600 people and performing over 24 excisions to detect one melanoma. When setting screening to start at the age of 35 years, the number of people needed to screen to detect one melanoma decreased slightly to 559. 

These findings highlight that population-based screening will include many people who don’t need it and can increase the potential for overdiagnosis, she argued.

Studies and guidelines from the United States align with Puig’s concern about broad-based screening likely leading to overdiagnosis. “The incidence of melanoma has risen sixfold in the past 40 years in the United States, while mortality has remained largely flat, an epidemiological signature consistent with overdiagnosis,” according to Adewole Adamson, MD, an assistant professor of internal medicine, in the Division of Dermatology at Dell Medical School at The University of Texas at Austin, Texas, who published findings to this effect in 2022.

“We cannot saturate the system with healthy people,” Puig said. Instead, “we need to use strategies to identify high-risk patients.” She proposed being more selective about who to screen by identifying those at higher risk of developing melanoma.

Identifying risk factors, such as the presence of atypical nevi and a personal or family history of melanoma, can help hone who is screened, she explained. Patients with a personal history of melanoma, in particular, face a higher risk of developing subsequent melanomas. Data show that patients with two or more primary melanomas had almost three times the risk of developing a subsequent one than those with one prior melanoma — 25.7% vs 8.6%. Puig also pointed out the significant correlation between age and melanoma risk, with people over 70 years exhibiting a 93-fold higher probability of diagnosis than those younger than 30 years.

Citing the German data, she noted that screening people 20 years and older with one risk factor reduced the number needed to screen by more than threefold — from more than 600 to 178.

Puig suggested dedicated surveillance programs for high-risk individuals alongside opportunistic screening during routine medical encounters.

“This would lead to a more efficient allocation of healthcare resources and better outcomes for those most vulnerable to melanoma,” Puig concluded.

 

Perform Population-Based Screening

In contrast, Mohr presented a defense of population-based skin cancer screening. Skin cancer is the most common cancer diagnosed in the United States and is prevalent worldwide, with more than 1.5 million new cases diagnosed globally in 2022.

Screening people and identifying the disease in its earliest stages is important, he said.

Mohr highlighted a recent study exploring biennial skin cancer screening in Germany and found that 4.2% of those screened had a skin cancer finding, but the number of interval melanomas was similar in both screened and unscreened populations.

However, a large retrospective cohort study from Germany involving about 1.4 million people showed a decrease in locoregional metastasis (from 13% to 4%), distant metastases (from 8% to 4%), and systemic treatments (from 21% to 11%) in screened vs unscreened people, as well as better overall survival rates in the screened population.

Mohr highlighted how Germany, in particular, is well-equipped for more broad-based, preventative screening.

Germany has had long-standing primary prevention programs, which have existed for about 24 years and involve extensive public awareness campaigns. Access to dermatologists is significantly better in Germany compared with the Netherlands, with an average waiting time for screening of around 6 weeks and only 1.2 weeks for suspicious lesions, compared with 14 weeks and 3.5 weeks, respectively, in the Netherlands. This access may make a broader screening strategy more feasible in a country like Germany.

However, Mohr did note that there are “no large, randomized trials to show us the value of skin cancer screening.”

 

A Role for Primary Care Physicians?

Although they disagreed about the utility of screening, both Puig and Mohr agreed on the important role primary care physicians play in improving early melanoma detection. “We cannot do it alone, and general practitioners are really fundamental,” Puig said.

Mohr said that continuous education for primary care physicians can dramatically improve their diagnostic skills. In Germany, an 8-hour training session significantly improved their ability to detect basal cell carcinoma and melanomas. However, he cautioned that this improved accuracy tended to wane within a year.

In Spain, Puig highlighted the successful implementation of teledermatology to support general practitioners. “We train them with dermoscopy, and we answer all teledermatology requests in 1 week, reducing in-person visits by 50%,” she explained. This approach allows general practitioners to assess potential skin cancer efficiently and streamline referrals.

Puig reported being on advisory boards for Almirall, Bristol Myers Squibb (BMS), ISDIN, La Roche-Posay, Leo Pharma, Novartis, Pfizer, Regeneron, Roche, Sanofi, and Sun Pharma. She conducts research and trials with AbbVie, Almirall, Amgen, BMS, Biofrontera, Canfield, Cantabria, Fotofinder, GSK, ISDIN, La Roche-Posay, Leo Pharma, MSD, MEDA, Novartis, Pfizer, Polychem, Sanofi, Roche, and Regeneron. She is involved with Athena Technology Solutions and Dermavision Solutions. Mohr reported no relevant financial relationships.

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

ATHENS, Greece — At the 11th World Congress of Melanoma and 21st EADO Congress 2025, experts presented divergent perspectives on the merits of population-wide skin cancer screening programs vs more targeted approaches. The debate highlighted concerns about healthcare resource allocation, overdiagnosis, and the true impact of mass skin cancer screening on mortality.

Arguing against widespread screening, particularly in low-to-medium incidence countries like Spain, was Susana Puig, MD, the head of Dermatology at Hospital Clínic de Barcelona, University of Barcelona, and a dermatologist at Barnaclínic+, Barcelona, Spain.

“It’s not efficient. We visit too many healthy individuals to detect melanoma,” she said. “We need to focus on treating patients, not checking healthy people without any risk.”

Championing for population-wide screening was Peter Mohr, MD, a dermatologist at the Clinic of Dermatology in Elbe Klinikum Buxtehude, Buxtehude, Germany, who noted a disproportionate focus on treatment rather than prevention. “The ultimate goal of screening,” he said, “is to prevent advanced disease and reduce melanoma-specific mortality.”

 

Avoid Population-Based Screening

Presenting data from Germany, Puig noted that population-based screening starting at any age requires examining more than 600 people and performing over 24 excisions to detect one melanoma. When setting screening to start at the age of 35 years, the number of people needed to screen to detect one melanoma decreased slightly to 559. 

These findings highlight that population-based screening will include many people who don’t need it and can increase the potential for overdiagnosis, she argued.

Studies and guidelines from the United States align with Puig’s concern about broad-based screening likely leading to overdiagnosis. “The incidence of melanoma has risen sixfold in the past 40 years in the United States, while mortality has remained largely flat, an epidemiological signature consistent with overdiagnosis,” according to Adewole Adamson, MD, an assistant professor of internal medicine, in the Division of Dermatology at Dell Medical School at The University of Texas at Austin, Texas, who published findings to this effect in 2022.

“We cannot saturate the system with healthy people,” Puig said. Instead, “we need to use strategies to identify high-risk patients.” She proposed being more selective about who to screen by identifying those at higher risk of developing melanoma.

Identifying risk factors, such as the presence of atypical nevi and a personal or family history of melanoma, can help hone who is screened, she explained. Patients with a personal history of melanoma, in particular, face a higher risk of developing subsequent melanomas. Data show that patients with two or more primary melanomas had almost three times the risk of developing a subsequent one than those with one prior melanoma — 25.7% vs 8.6%. Puig also pointed out the significant correlation between age and melanoma risk, with people over 70 years exhibiting a 93-fold higher probability of diagnosis than those younger than 30 years.

Citing the German data, she noted that screening people 20 years and older with one risk factor reduced the number needed to screen by more than threefold — from more than 600 to 178.

Puig suggested dedicated surveillance programs for high-risk individuals alongside opportunistic screening during routine medical encounters.

“This would lead to a more efficient allocation of healthcare resources and better outcomes for those most vulnerable to melanoma,” Puig concluded.

 

Perform Population-Based Screening

In contrast, Mohr presented a defense of population-based skin cancer screening. Skin cancer is the most common cancer diagnosed in the United States and is prevalent worldwide, with more than 1.5 million new cases diagnosed globally in 2022.

Screening people and identifying the disease in its earliest stages is important, he said.

Mohr highlighted a recent study exploring biennial skin cancer screening in Germany and found that 4.2% of those screened had a skin cancer finding, but the number of interval melanomas was similar in both screened and unscreened populations.

However, a large retrospective cohort study from Germany involving about 1.4 million people showed a decrease in locoregional metastasis (from 13% to 4%), distant metastases (from 8% to 4%), and systemic treatments (from 21% to 11%) in screened vs unscreened people, as well as better overall survival rates in the screened population.

Mohr highlighted how Germany, in particular, is well-equipped for more broad-based, preventative screening.

Germany has had long-standing primary prevention programs, which have existed for about 24 years and involve extensive public awareness campaigns. Access to dermatologists is significantly better in Germany compared with the Netherlands, with an average waiting time for screening of around 6 weeks and only 1.2 weeks for suspicious lesions, compared with 14 weeks and 3.5 weeks, respectively, in the Netherlands. This access may make a broader screening strategy more feasible in a country like Germany.

However, Mohr did note that there are “no large, randomized trials to show us the value of skin cancer screening.”

 

A Role for Primary Care Physicians?

Although they disagreed about the utility of screening, both Puig and Mohr agreed on the important role primary care physicians play in improving early melanoma detection. “We cannot do it alone, and general practitioners are really fundamental,” Puig said.

Mohr said that continuous education for primary care physicians can dramatically improve their diagnostic skills. In Germany, an 8-hour training session significantly improved their ability to detect basal cell carcinoma and melanomas. However, he cautioned that this improved accuracy tended to wane within a year.

In Spain, Puig highlighted the successful implementation of teledermatology to support general practitioners. “We train them with dermoscopy, and we answer all teledermatology requests in 1 week, reducing in-person visits by 50%,” she explained. This approach allows general practitioners to assess potential skin cancer efficiently and streamline referrals.

Puig reported being on advisory boards for Almirall, Bristol Myers Squibb (BMS), ISDIN, La Roche-Posay, Leo Pharma, Novartis, Pfizer, Regeneron, Roche, Sanofi, and Sun Pharma. She conducts research and trials with AbbVie, Almirall, Amgen, BMS, Biofrontera, Canfield, Cantabria, Fotofinder, GSK, ISDIN, La Roche-Posay, Leo Pharma, MSD, MEDA, Novartis, Pfizer, Polychem, Sanofi, Roche, and Regeneron. She is involved with Athena Technology Solutions and Dermavision Solutions. Mohr reported no relevant financial relationships.

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

ATHENS, Greece — At the 11th World Congress of Melanoma and 21st EADO Congress 2025, experts presented divergent perspectives on the merits of population-wide skin cancer screening programs vs more targeted approaches. The debate highlighted concerns about healthcare resource allocation, overdiagnosis, and the true impact of mass skin cancer screening on mortality.

Arguing against widespread screening, particularly in low-to-medium incidence countries like Spain, was Susana Puig, MD, the head of Dermatology at Hospital Clínic de Barcelona, University of Barcelona, and a dermatologist at Barnaclínic+, Barcelona, Spain.

“It’s not efficient. We visit too many healthy individuals to detect melanoma,” she said. “We need to focus on treating patients, not checking healthy people without any risk.”

Championing for population-wide screening was Peter Mohr, MD, a dermatologist at the Clinic of Dermatology in Elbe Klinikum Buxtehude, Buxtehude, Germany, who noted a disproportionate focus on treatment rather than prevention. “The ultimate goal of screening,” he said, “is to prevent advanced disease and reduce melanoma-specific mortality.”

 

Avoid Population-Based Screening

Presenting data from Germany, Puig noted that population-based screening starting at any age requires examining more than 600 people and performing over 24 excisions to detect one melanoma. When setting screening to start at the age of 35 years, the number of people needed to screen to detect one melanoma decreased slightly to 559. 

These findings highlight that population-based screening will include many people who don’t need it and can increase the potential for overdiagnosis, she argued.

Studies and guidelines from the United States align with Puig’s concern about broad-based screening likely leading to overdiagnosis. “The incidence of melanoma has risen sixfold in the past 40 years in the United States, while mortality has remained largely flat, an epidemiological signature consistent with overdiagnosis,” according to Adewole Adamson, MD, an assistant professor of internal medicine, in the Division of Dermatology at Dell Medical School at The University of Texas at Austin, Texas, who published findings to this effect in 2022.

“We cannot saturate the system with healthy people,” Puig said. Instead, “we need to use strategies to identify high-risk patients.” She proposed being more selective about who to screen by identifying those at higher risk of developing melanoma.

Identifying risk factors, such as the presence of atypical nevi and a personal or family history of melanoma, can help hone who is screened, she explained. Patients with a personal history of melanoma, in particular, face a higher risk of developing subsequent melanomas. Data show that patients with two or more primary melanomas had almost three times the risk of developing a subsequent one than those with one prior melanoma — 25.7% vs 8.6%. Puig also pointed out the significant correlation between age and melanoma risk, with people over 70 years exhibiting a 93-fold higher probability of diagnosis than those younger than 30 years.

Citing the German data, she noted that screening people 20 years and older with one risk factor reduced the number needed to screen by more than threefold — from more than 600 to 178.

Puig suggested dedicated surveillance programs for high-risk individuals alongside opportunistic screening during routine medical encounters.

“This would lead to a more efficient allocation of healthcare resources and better outcomes for those most vulnerable to melanoma,” Puig concluded.

 

Perform Population-Based Screening

In contrast, Mohr presented a defense of population-based skin cancer screening. Skin cancer is the most common cancer diagnosed in the United States and is prevalent worldwide, with more than 1.5 million new cases diagnosed globally in 2022.

Screening people and identifying the disease in its earliest stages is important, he said.

Mohr highlighted a recent study exploring biennial skin cancer screening in Germany and found that 4.2% of those screened had a skin cancer finding, but the number of interval melanomas was similar in both screened and unscreened populations.

However, a large retrospective cohort study from Germany involving about 1.4 million people showed a decrease in locoregional metastasis (from 13% to 4%), distant metastases (from 8% to 4%), and systemic treatments (from 21% to 11%) in screened vs unscreened people, as well as better overall survival rates in the screened population.

Mohr highlighted how Germany, in particular, is well-equipped for more broad-based, preventative screening.

Germany has had long-standing primary prevention programs, which have existed for about 24 years and involve extensive public awareness campaigns. Access to dermatologists is significantly better in Germany compared with the Netherlands, with an average waiting time for screening of around 6 weeks and only 1.2 weeks for suspicious lesions, compared with 14 weeks and 3.5 weeks, respectively, in the Netherlands. This access may make a broader screening strategy more feasible in a country like Germany.

However, Mohr did note that there are “no large, randomized trials to show us the value of skin cancer screening.”

 

A Role for Primary Care Physicians?

Although they disagreed about the utility of screening, both Puig and Mohr agreed on the important role primary care physicians play in improving early melanoma detection. “We cannot do it alone, and general practitioners are really fundamental,” Puig said.

Mohr said that continuous education for primary care physicians can dramatically improve their diagnostic skills. In Germany, an 8-hour training session significantly improved their ability to detect basal cell carcinoma and melanomas. However, he cautioned that this improved accuracy tended to wane within a year.

In Spain, Puig highlighted the successful implementation of teledermatology to support general practitioners. “We train them with dermoscopy, and we answer all teledermatology requests in 1 week, reducing in-person visits by 50%,” she explained. This approach allows general practitioners to assess potential skin cancer efficiently and streamline referrals.

Puig reported being on advisory boards for Almirall, Bristol Myers Squibb (BMS), ISDIN, La Roche-Posay, Leo Pharma, Novartis, Pfizer, Regeneron, Roche, Sanofi, and Sun Pharma. She conducts research and trials with AbbVie, Almirall, Amgen, BMS, Biofrontera, Canfield, Cantabria, Fotofinder, GSK, ISDIN, La Roche-Posay, Leo Pharma, MSD, MEDA, Novartis, Pfizer, Polychem, Sanofi, Roche, and Regeneron. She is involved with Athena Technology Solutions and Dermavision Solutions. Mohr reported no relevant financial relationships.

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

ATLANTA —Jacqueline Lee, MD, a reproductive endocrinologist at Emory School of Medicine, frequently treats patients with cancer. Recently, she treated 4 women in their 30s with histories of colon cancer, acute lymphoblastic leukemia, lymphoma, and breast cancer. A young man in his 20s sought her care, to discuss his case of lymphoma.

All these patients sought guidance from Lee because they want to protect their ability to have children. At the annual meeting of the Association of VA Hematology/Oncology, Lee explained that plenty of patients are finding themselves in similar straits due in part to recent trends.

Cancer rates in the US have been rising among people aged 15 to 39 years, who now account for 4.2% of all cancer cases. An estimated 84,100 people in this age group are expected to be diagnosed with cancer this year. Meanwhile, women are having children later in life-birth rates are up among those aged 25 to 49 years-making it more likely that they have histories of cancer.

Although it's difficult to predict how cancer will affect fertility, Lee emphasized that many chemotherapy medications, including cisplatin and carboplatin, are cytotoxic. "It's hard to always predict what someone's arc of care is going to be," she said, "so I really have a low threshold for recommending fertility preservation in patients who have a strong desire to have future childbearing."

For women with cancer, egg preservation isn't the only strategy. Clinicians can also try to protect ovarian tissue from pelvic radiation through surgical reposition of the ovaries, Lee noted. In addition goserelin, a hormone-suppressing therapy, may protect the ovaries from chemotherapy, though its effectiveness in boosting pregnancy rates is still unclear.

"When I mentioned this option, it's usually for patients who can't preserve fertility via egg or embryo preservation, or we don't have the luxury of that kind of time," Lee said. "I say that if helps at all, it might help you resume menses after treatment. But infertility is still very common."

For some patients, freezing eggs is an easy decision. "They don't have a reproductive partner they're ready to make embryos with, so we proceed with egg preservation. It's no longer considered experimental and comes with lower upfront costs since the costs of actually making embryos are deferred until the future."

In addition, she said, freezing eggs also avoids the touchy topic of disposing of embryos. Lee cautions patients that retrieving eggs is a 2-week process that requires any initiation of cancer care to be delayed. However, the retrieval process can be adjusted in patients with special needs due to the type of cancer they have.

For prepubertal girls with cancer, ovarian tissue can be removed and frozen as a fertility preservation option. However, this is not considered standard of care. "We don't do it," she said. "We refer out if needed. Hopefully we'll develop a program in the future."

As for the 5 patients that Lee mentioned, with details changed to protect their privacy, their outcomes were as follows:

• The woman with colon cancer, who had undergone a hemicolectomy, chose to defer fertility preservation.
• The woman with acute lymphoblastic leukemia, who was taking depo-Lupron, had undetectable anti-Müllerian hormone (AMH) levels. Lee discussed the possibility of IVF with a donor egg.
• The woman with breast cancer, who was newly diagnosed, deferred fertility preservation.
• The man with lymphoma (Hodgkin's), who was awaiting chemotherapy, had his sperm frozen.
• The woman with lymphoma (new diagnosis) had 27 eggs frozen.

Lee had no disclosures to report.

ATLANTA —Jacqueline Lee, MD, a reproductive endocrinologist at Emory School of Medicine, frequently treats patients with cancer. Recently, she treated 4 women in their 30s with histories of colon cancer, acute lymphoblastic leukemia, lymphoma, and breast cancer. A young man in his 20s sought her care, to discuss his case of lymphoma.

All these patients sought guidance from Lee because they want to protect their ability to have children. At the annual meeting of the Association of VA Hematology/Oncology, Lee explained that plenty of patients are finding themselves in similar straits due in part to recent trends.

Cancer rates in the US have been rising among people aged 15 to 39 years, who now account for 4.2% of all cancer cases. An estimated 84,100 people in this age group are expected to be diagnosed with cancer this year. Meanwhile, women are having children later in life-birth rates are up among those aged 25 to 49 years-making it more likely that they have histories of cancer.

Although it's difficult to predict how cancer will affect fertility, Lee emphasized that many chemotherapy medications, including cisplatin and carboplatin, are cytotoxic. "It's hard to always predict what someone's arc of care is going to be," she said, "so I really have a low threshold for recommending fertility preservation in patients who have a strong desire to have future childbearing."

For women with cancer, egg preservation isn't the only strategy. Clinicians can also try to protect ovarian tissue from pelvic radiation through surgical reposition of the ovaries, Lee noted. In addition goserelin, a hormone-suppressing therapy, may protect the ovaries from chemotherapy, though its effectiveness in boosting pregnancy rates is still unclear.

"When I mentioned this option, it's usually for patients who can't preserve fertility via egg or embryo preservation, or we don't have the luxury of that kind of time," Lee said. "I say that if helps at all, it might help you resume menses after treatment. But infertility is still very common."

For some patients, freezing eggs is an easy decision. "They don't have a reproductive partner they're ready to make embryos with, so we proceed with egg preservation. It's no longer considered experimental and comes with lower upfront costs since the costs of actually making embryos are deferred until the future."

In addition, she said, freezing eggs also avoids the touchy topic of disposing of embryos. Lee cautions patients that retrieving eggs is a 2-week process that requires any initiation of cancer care to be delayed. However, the retrieval process can be adjusted in patients with special needs due to the type of cancer they have.

For prepubertal girls with cancer, ovarian tissue can be removed and frozen as a fertility preservation option. However, this is not considered standard of care. "We don't do it," she said. "We refer out if needed. Hopefully we'll develop a program in the future."

As for the 5 patients that Lee mentioned, with details changed to protect their privacy, their outcomes were as follows:

• The woman with colon cancer, who had undergone a hemicolectomy, chose to defer fertility preservation.
• The woman with acute lymphoblastic leukemia, who was taking depo-Lupron, had undetectable anti-Müllerian hormone (AMH) levels. Lee discussed the possibility of IVF with a donor egg.
• The woman with breast cancer, who was newly diagnosed, deferred fertility preservation.
• The man with lymphoma (Hodgkin's), who was awaiting chemotherapy, had his sperm frozen.
• The woman with lymphoma (new diagnosis) had 27 eggs frozen.

Lee had no disclosures to report.

ATLANTA —Jacqueline Lee, MD, a reproductive endocrinologist at Emory School of Medicine, frequently treats patients with cancer. Recently, she treated 4 women in their 30s with histories of colon cancer, acute lymphoblastic leukemia, lymphoma, and breast cancer. A young man in his 20s sought her care, to discuss his case of lymphoma.

All these patients sought guidance from Lee because they want to protect their ability to have children. At the annual meeting of the Association of VA Hematology/Oncology, Lee explained that plenty of patients are finding themselves in similar straits due in part to recent trends.

Cancer rates in the US have been rising among people aged 15 to 39 years, who now account for 4.2% of all cancer cases. An estimated 84,100 people in this age group are expected to be diagnosed with cancer this year. Meanwhile, women are having children later in life-birth rates are up among those aged 25 to 49 years-making it more likely that they have histories of cancer.

Although it's difficult to predict how cancer will affect fertility, Lee emphasized that many chemotherapy medications, including cisplatin and carboplatin, are cytotoxic. "It's hard to always predict what someone's arc of care is going to be," she said, "so I really have a low threshold for recommending fertility preservation in patients who have a strong desire to have future childbearing."

For women with cancer, egg preservation isn't the only strategy. Clinicians can also try to protect ovarian tissue from pelvic radiation through surgical reposition of the ovaries, Lee noted. In addition goserelin, a hormone-suppressing therapy, may protect the ovaries from chemotherapy, though its effectiveness in boosting pregnancy rates is still unclear.

"When I mentioned this option, it's usually for patients who can't preserve fertility via egg or embryo preservation, or we don't have the luxury of that kind of time," Lee said. "I say that if helps at all, it might help you resume menses after treatment. But infertility is still very common."

For some patients, freezing eggs is an easy decision. "They don't have a reproductive partner they're ready to make embryos with, so we proceed with egg preservation. It's no longer considered experimental and comes with lower upfront costs since the costs of actually making embryos are deferred until the future."

In addition, she said, freezing eggs also avoids the touchy topic of disposing of embryos. Lee cautions patients that retrieving eggs is a 2-week process that requires any initiation of cancer care to be delayed. However, the retrieval process can be adjusted in patients with special needs due to the type of cancer they have.

For prepubertal girls with cancer, ovarian tissue can be removed and frozen as a fertility preservation option. However, this is not considered standard of care. "We don't do it," she said. "We refer out if needed. Hopefully we'll develop a program in the future."

As for the 5 patients that Lee mentioned, with details changed to protect their privacy, their outcomes were as follows:

• The woman with colon cancer, who had undergone a hemicolectomy, chose to defer fertility preservation.
• The woman with acute lymphoblastic leukemia, who was taking depo-Lupron, had undetectable anti-Müllerian hormone (AMH) levels. Lee discussed the possibility of IVF with a donor egg.
• The woman with breast cancer, who was newly diagnosed, deferred fertility preservation.
• The man with lymphoma (Hodgkin's), who was awaiting chemotherapy, had his sperm frozen.
• The woman with lymphoma (new diagnosis) had 27 eggs frozen.

Lee had no disclosures to report.

Background

Cancer clinical trials (CCTs) are central to improving cancer care. However, generalizability of findings from CCTs is difficult due to the lack of diversity in most United States CCTs. Clinical trial accrual of underrepresented groups, is low throughout the United States and is approximately 4-5% in most CCTs. Reasons for low accrual in this population are multifactorial. Despite numerous factors related to accruing racial and ethnic underrepresented groups, many institutions have sought to address these barriers. We conducted a scoping review to identify evidence-based approaches to increase participation in cancer treatment clinical trials.

Methods

We reviewed the Salisbury VA Medical Center Oncology clinical trial database from October 2019 to June 2024. The participants in these clinical trials required consent. These clinical trials included treatment interventional as well as non-treatment interventional. Fifteen studies were included and over 260 Veterans participated.

Results

Key themes emerged that included a focus on patient education, cultural competency, and building capacity in the clinics to care for the Veteran population at three separate sites in the Salisbury VA system. The Black Veteran accrual rate of 29% was achieved. This accrual rate is representative of our VA catchment population of 33% for Black Veterans, and is five times the national average.

Conclusions

The research team’s success in enrolling Black Veterans in clinical trials is attributed to several factors. The demographic composition of Veterans served by the Salisbury, Charlotte, and Kernersville VA provided a diverse population that included a 33% Black group. The type of clinical trials focused on patients who were most impacted by the disease. The VA did afford less barriers to access to health care.

Background

Cancer clinical trials (CCTs) are central to improving cancer care. However, generalizability of findings from CCTs is difficult due to the lack of diversity in most United States CCTs. Clinical trial accrual of underrepresented groups, is low throughout the United States and is approximately 4-5% in most CCTs. Reasons for low accrual in this population are multifactorial. Despite numerous factors related to accruing racial and ethnic underrepresented groups, many institutions have sought to address these barriers. We conducted a scoping review to identify evidence-based approaches to increase participation in cancer treatment clinical trials.

Methods

We reviewed the Salisbury VA Medical Center Oncology clinical trial database from October 2019 to June 2024. The participants in these clinical trials required consent. These clinical trials included treatment interventional as well as non-treatment interventional. Fifteen studies were included and over 260 Veterans participated.

Results

Key themes emerged that included a focus on patient education, cultural competency, and building capacity in the clinics to care for the Veteran population at three separate sites in the Salisbury VA system. The Black Veteran accrual rate of 29% was achieved. This accrual rate is representative of our VA catchment population of 33% for Black Veterans, and is five times the national average.

Conclusions

The research team’s success in enrolling Black Veterans in clinical trials is attributed to several factors. The demographic composition of Veterans served by the Salisbury, Charlotte, and Kernersville VA provided a diverse population that included a 33% Black group. The type of clinical trials focused on patients who were most impacted by the disease. The VA did afford less barriers to access to health care.

Background

Cancer clinical trials (CCTs) are central to improving cancer care. However, generalizability of findings from CCTs is difficult due to the lack of diversity in most United States CCTs. Clinical trial accrual of underrepresented groups, is low throughout the United States and is approximately 4-5% in most CCTs. Reasons for low accrual in this population are multifactorial. Despite numerous factors related to accruing racial and ethnic underrepresented groups, many institutions have sought to address these barriers. We conducted a scoping review to identify evidence-based approaches to increase participation in cancer treatment clinical trials.

Methods

We reviewed the Salisbury VA Medical Center Oncology clinical trial database from October 2019 to June 2024. The participants in these clinical trials required consent. These clinical trials included treatment interventional as well as non-treatment interventional. Fifteen studies were included and over 260 Veterans participated.

Results

Key themes emerged that included a focus on patient education, cultural competency, and building capacity in the clinics to care for the Veteran population at three separate sites in the Salisbury VA system. The Black Veteran accrual rate of 29% was achieved. This accrual rate is representative of our VA catchment population of 33% for Black Veterans, and is five times the national average.

Conclusions

The research team’s success in enrolling Black Veterans in clinical trials is attributed to several factors. The demographic composition of Veterans served by the Salisbury, Charlotte, and Kernersville VA provided a diverse population that included a 33% Black group. The type of clinical trials focused on patients who were most impacted by the disease. The VA did afford less barriers to access to health care.