Influence of Cost-Related Considerations on Clinical Trial Participation: Results from the 2020 Health Information National Trends Survey (HINTS).

BACKGROUND: People experiencing financial burden are underrepresented in clinical trials. OBJECTIVE: Describe the prevalence of cost-related considerations influential to trial participation and their associations with person-level characteristics. DESIGN: This cross-sectional study used and assessed how three cost-related considerations would influence the decision to participate in a hypothetical clinical trial. PARTICIPANTS: A total of 3682 US adult respondents to the Health Information National Trends Survey MAIN MEASURES: Survey-weighted multivariable logistic regression estimated associations between respondent characteristics and odds of reporting cost-related considerations as very influential to participation. KEY RESULTS: Among 3682 respondents, median age was 48 (IQR 33-61). Most were non-Hispanic White (60%), living comfortably or getting by on their income (74%), with ≥ 1 medical condition (61%). Over half (55%) of respondents reported at least one cost-related consideration as very influential to trial participation, including if usual care was not covered by insurance (reported by 42%), payment for participation (24%), or support for participation (24%). Respondents who were younger (18-34 vs. ≥ 75, adjusted odds ratio [aOR] 4.3, 95% CI 2.3-8.1), more educated (high school vs.

A History of Health Economics and Healthcare Delivery Research at the National Cancer Institute.

With increased attention to the financing and structure of healthcare, dramatic increases in the cost of diagnosing and treating cancer, and corresponding disparities in access, the study of healthcare economics and delivery has become increasingly important. The Healthcare Delivery Research Program (HDRP) in the Division of Cancer Control and Population Sciences at the National Cancer Institute (NCI) was formed in 2015 to provide a hub for cancer-related healthcare delivery and economics research. However, the roots of this program trace back much farther, at least to the formation of the NCI Division of Cancer Prevention and Control in 1983. The creation of a division focused on understanding and explaining trends in cancer morbidity and mortality was instrumental in setting the direction of cancer-related healthcare delivery and health economics research over the subsequent decades. In this commentary, we provide a brief history of health economics and healthcare delivery research at NCI, describing the organizational structure and highlighting key initiatives developed by the division, and also briefly discuss future directions. HDRP and its predecessors have supported the growth and evolution of these fields through the funding of grants and contracts; the development of data, tools, and other research resources; and thought leadership including stimulation of research on previously understudied topics. As the availability of new data, methods, and computing capacity to evaluate cancer-related healthcare delivery and economics expand, HDRP aims to continue to support this growth and evolution.

Delivery of Financial Navigation Services Within National Cancer Institute-Designated Cancer Centers.

Background: Cancer centers have a responsibility to help patients manage the costs of their cancer treatment. This article describes the availability of financial navigation services within the National Cancer Institute (NCI)-designated cancer centers. Methods: Data were obtained from the NCI Survey of Financial Navigation Services and Research, an online survey administered to NCI-designated cancer centers from July to September 2019. Of the 62 eligible centers, 57 completed all or most of the survey, for a response rate of 90.5%. Results: Nearly all cancer centers reported providing help with applications for pharmaceutical assistance programs and medical discounts (96.5%), health insurance coverage (91.2%), assistance with nonmedical costs (96.5%), and help understanding medical bills and out-of-pocket costs (85.9%). Although other services were common, in some cases they were only available to certain patients. These services included direct financial assistance with medical and nonmedical costs and referrals to outside organizations for financial assistance. The least common services included medical debt management (63.2%), detailed discussions about the cost of treatment (54.4%), and guidance about legal protections (50.1%). Providing treatment cost transparency to patients was reported as a common challenge: 71.9% of centers agreed or strongly agreed that it is difficult to determine how much a cancer patient's treatment will cost, and 70.2% of oncologists are reluctant to discuss financial issues with patients. Conclusions: Cancer centers provide many financial services and resources. However, there remains a need to build additional capacity to deliver comprehensive financial navigation services and to understand the extent to which patients are referred and helped by these services.

Comparison of Physician Data in Two Data Files Available for Cancer Health Services Research.

INTRODUCTION: Physicians are vital to health-care delivery, but assessing their impact on care can be challenging given limited data. Historically, health services researchers have obtained physician characteristics data from the American Medical Association (AMA) Physician Masterfile. The Center for Medicare and Medicaid Services' Medicare Data on Provider Practice and Specialty (MD-PPAS) file was assessed, as an alternative source of physician data, particularly in the context of cancer health services research. METHODS: We used physician National Provider Identifiers in the MD-PPAS data (2008-2014) to identify physicians in the AMA data current as of July 18, 2016. Within each source, we grouped physicians into six broad specialty groups. Percent agreement and Cohen's kappa coefficient (k) were calculated for age, sex, specialty, and practice state. RESULTS: Among the 698 202 included physicians, there was excellent agreement for age (percent agreement = 97.7%, k = 0.97) and sex (99.4%, k = 0.99) and good agreement for specialty (86.1%, k = 0.80). Within specialty, using AMA as the reference, agreement was lowest for oncologists (77%). Approximately 85.9% of physicians reported the same practice state in both data sets. CONCLUSION: Although AMA data have been commonly used to account for physician-level factors in health services research, MD-PPAS data provide researchers with an alternative option depending on study needs. MD-PPAS data may be optimal if nonphysicians, provider utilization, practice characteristics, and/or temporal changes are of interest. In contrast, the AMA data may be optimal if more granular specialty, physician training, and/or a broader inclusion of physicians is of interest.

Addressing Challenges in Converting Grant-Funded Infrastructures to Broadly Used Research Resources.

The NCI invests heavily in research resources to serve the research community, including datasets, biospecimen banks, and networks of institutions in which clinical trials and other human subjects research are conducted. These resources often begin as grant-funded infrastructure initiated by scientists based on their own scientific interests, with a subsequent recognition of additional scientific uses. Although converting existing project-specific research activities into research resources may appear efficient in terms of time and financial investment, challenges can arise that undermine this efficiency and jeopardize future use. Here, we describe three challenges in the conversion process: (i) project-based infrastructure versus a research resource for a broader research community; (ii) complexity versus ease of use; and (iii) individual professional goals versus research resource priorities. We use our experience with the NCI-funded Cancer Research Network, particularly the Virtual Data Warehouse, to illustrate each challenge, concluding with strategies to mitigate each one. As studies grow in size and complexity, an ever-increasing volume of data, biospecimens, and human subjects research networks will be available for conversion to resources for scientific questions beyond those originally proposed. Addressing likely challenges thoughtfully can result in a more efficient conversion process and ultimately greater scientific impact.

Developing a Quality of Cancer Survivorship Care Framework: Implications for Clinical Care, Research, and Policy.

There are now close to 17 million cancer survivors in the United States, and this number is expected to continue to grow. One decade ago the Institute of Medicine report, From Cancer Patient to Cancer Survivor: Lost in Transition, outlined 10 recommendations aiming to provide coordinated, comprehensive care for cancer survivors. Although there has been noteworthy progress made since the release of the report, gaps remain in research, clinical practice, and policy. Specifically, the recommendation calling for the development of quality measures in cancer survivorship care has yet to be fulfilled. In this commentary, we describe the development of a comprehensive, evidence-based cancer survivorship care quality framework and propose the next steps to systematically apply it in clinical settings, research, and policy.

Healthcare Expenditure Burden Among Non-elderly Cancer Survivors, 2008-2012.

INTRODUCTION: There is increasing concern regarding the financial burden of cancer on patients and their families. This study presents nationally representative estimates of annual out-of-pocket (OOP) burden among non-elderly cancer survivors and assesses the association between high OOP burden and access to care and preventive service utilization. METHODS: Using the 2008-2012 Medical Expenditure Panel Survey, 4,271 cancer survivors and 96,780 individuals without a history of cancer were identified, all aged 18-64 years. High annual OOP burden was defined as spending >20% of annual family income on OOP healthcare costs. Associations between high OOP burden and access to care were evaluated with multivariable logistic regression. Analyses were conducted in 2015. RESULTS: Compared with individuals without a cancer history, cancer survivors were more likely to report a high OOP burden (4.3% vs 3.4%, p=0.009) in adjusted analyses. High OOP burden was more common among cancer survivors who were poor (18.4%), with either public insurance (7.9%) or uninsured (5.7%), and not working (10.2%). Among cancer survivors, high OOP burden was associated with being unable to obtain necessary medical care (19.2% vs 12.5%, p=0.002), delaying necessary medical care (21.6% vs 13.8%, p=0.002), and lower breast cancer screening rates among age-appropriate women (63.2% vs 75.9%, p=0.02). CONCLUSIONS: High OOP burden is more common among adults with a cancer history than those without a cancer history. High OOP burden was associated with being unable to obtain necessary medical care, delaying necessary medical care, and lower breast cancer screening rates among women.

Race and Insurance Differences in the Receipt of Adjuvant Chemotherapy Among Patients With Stage III Colon Cancer.

PURPOSE: Although the incidence and mortality of colon cancer in the United States has declined over the past two decades, blacks have worse outcomes than whites. Variations in treatment may contribute to mortality differentials. METHODS: Patients diagnosed with stage III colon cancer were randomly sampled from the SEER program from the years 1990, 1991, 1995, 2000, 2005, and 2010. Patients were categorized as non-Hispanic white (n = 835) or black (n = 384). Treatment data were obtained from a review of the medical records, and these data were verified through contact with the original treating physicians. Log-binomial regression models were used to estimate the association between race and receipt of adjuvant chemotherapy. Effect modification by insurance was assessed with use of single referent models. RESULTS: Receipt of adjuvant chemotherapy among both white and black patients increased from the period encompassing the years 1990 and 1991 (white, 58%; black, 45%) to the year 2005 (white, 72%; black, 71%) and then decreased in the year 2010 (white, 66%; black, 57%). There were marked racial disparities in the time period of 1990 to 1991 and again in 2010, with black patients less likely to receive adjuvant chemotherapy as compared with white patients (risk ratio [RR], .82; 95% CI, .72 to .93). For black patients, receipt of adjuvant chemotherapy did not differ across insurance categories (RR for private insurance, .80; 95% CI, .69 to .93; RR for Medicare, .84; 95% CI, .69 to 1.02; and RR for Medicaid, .84; 95% CI, .69 to 1.02), although a larger proportion had Medicaid in all years of the study as compared with white patients. CONCLUSION: The chemotherapy differential narrowed after the time period of 1990 to 1991, but our findings suggest that the disparity reemerged in 2010. Recent decreases in chemotherapy use may be due, in part, to the economic downturn and an increase in Medicaid coverage.

Unifying screening processes within the PROSPR consortium: a conceptual model for breast, cervical, and colorectal cancer screening.

General frameworks of the cancer screening process are available, but none directly compare the process in detail across different organ sites. This limits the ability of medical and public health professionals to develop and evaluate coordinated screening programs that apply resources and population management strategies available for one cancer site to other sites. We present a trans-organ conceptual model that incorporates a single screening episode for breast, cervical, and colorectal cancers into a unified framework based on clinical guidelines and protocols; the model concepts could be expanded to other organ sites. The model covers four types of care in the screening process: risk assessment, detection, diagnosis, and treatment. Interfaces between different provider teams (eg, primary care and specialty care), including communication and transfer of responsibility, may occur when transitioning between types of care. Our model highlights across each organ site similarities and differences in steps, interfaces, and transitions in the screening process and documents the conclusion of a screening episode. This model was developed within the National Cancer Institute-funded consortium Population-based Research Optimizing Screening through Personalized Regimens (PROSPR). PROSPR aims to optimize the screening process for breast, cervical, and colorectal cancer and includes seven research centers and a statistical coordinating center. Given current health care reform initiatives in the United States, this conceptual model can facilitate the development of comprehensive quality metrics for cancer screening and promote trans-organ comparative cancer screening research. PROSPR findings will support the design of interventions that improve screening outcomes across multiple cancer sites.

Disparities in barriers to follow-up care between African American and White breast cancer survivors.

PURPOSE: Despite recommendations for breast cancer survivorship care, African American women are less likely to receive appropriate follow-up care, which is concerning due to their higher mortality rates. This study describes differences in barriers to follow-up care between African American and White breast cancer survivors. METHODS: We conducted a mailed survey of women treated for non-metastatic breast cancer in 2009-2011, 6-24 months post-treatment (N = 203). Survivors were asked about 14 potential barriers to follow-up care. We used logistic regression to explore associations between barriers and race, adjusting for covariates. RESULTS: Our participants included 31 African American and 160 White survivors. At least one barrier to follow-up care was reported by 62 %. Compared to White survivors, African Americans were more likely to identify barriers related to out-of-pocket costs (28 vs. 51.6 %, p = 0.01), other health care costs (21.3 vs. 45.2 %, p = 0.01), anxiety/worry (29.4 vs. 51.6 %, p = 0.02), and transportation (4.4 vs. 16.1 %, p = 0.03). After adjustment for covariates, African Americans were three times as likely to report at least one barrier to care (odds ratio (OR) = 3.3, 95 % confidence interval (CI) = 1.1-10.1). CONCLUSIONS: Barriers to care are common among breast cancer survivors, especially African American women. Financial barriers to care may prevent minority and underserved survivors from accessing follow-up care. Enhancing insurance coverage or addressing out-of-pocket costs may help address financial barriers to follow-up care among breast cancer survivors. Psychosocial care aimed at reducing fear of recurrence may also be important to improve access among African American breast cancer survivors.

Impact of rural residence on forgoing healthcare after cancer because of cost.

BACKGROUND: Routine follow-up care is recommended to promote the well-being of cancer survivors, but financial difficulties may interfere. Rural-urban disparities in forgoing healthcare due to cost have been observed in the general population; however, it is unknown whether this disparity persists among survivors. The purpose of this study was to examine rural-urban disparities in forgoing healthcare after cancer due to cost. METHODS: We analyzed data from 7,804 cancer survivors in the 2006 to 2010 National Health Interview Survey. Logistic regression models, adjusting for sociodemographic and clinical characteristics, were used to assess rural-urban disparities in forgoing medical care, prescription medications, and dental care due to cost, stratified by age (younger: 18-64, older: 65+). RESULTS: Compared with urban survivors, younger rural survivors were more likely to forgo medical care (P < 0.001) and prescription medications (P < 0.001) due to cost; older rural survivors were more likely to forgo medical (P < 0.001) and dental care (P = 0.05). Rural-urban disparities did not persist among younger survivors in adjusted analyses; however, older rural survivors remained more likely to forgo medical [OR = 1.66, 95% confidence interval (CI) = 1.11-2.48] and dental care (OR = 1.54, 95%CI = 1.08-2.20). CONCLUSIONS: Adjustment for health insurance and other sociodemographic characteristics attenuates rural-urban disparities in forgoing healthcare among younger survivors, but not older survivors. Financial factors relating to healthcare use among rural survivors should be a topic of continued investigation. IMPACT: Addressing out-of-pocket costs may be an important step in reducing rural-urban disparities in healthcare, especially for older survivors. It will be important to monitor how healthcare reform efforts impact disparities observed in this vulnerable population.

Racial/Ethnic disparities in health care receipt among male cancer survivors.

OBJECTIVES: We examined racial/ethnic disparities in health care receipt among a nationally representative sample of male cancer survivors. METHODS: We identified men aged 18 years and older from the 2006-2010 National Health Interview Survey who reported a history of cancer. We assessed health care receipt in 4 self-reported measures: primary care visit, specialist visit, flu vaccination, and pneumococcal vaccination. We used hierarchical logistic regression modeling, stratified by age (< 65 years vs ≥ 65 years). RESULTS: In adjusted models, older African American and Hispanic survivors were approximately twice as likely as were non-Hispanic Whites to not see a specialist (odds ratio [OR] = 1.78; 95% confidence interval [CI] = 1.19, 2.68 and OR = 2.09; 95% CI = 1.18, 3.70, respectively), not receive the flu vaccine (OR = 2.21; 95% CI = 1.45, 3.37 and OR = 2.20; 95% CI = 1.21, 4.01, respectively), and not receive the pneumococcal vaccine (OR = 2.24; 95% CI = 1.54, 3.24 and OR = 3.10; 95% CI = 1.75, 5.51, respectively). CONCLUSIONS: Racial/ethnic disparities in health care receipt are evident among older, but not younger, cancer survivors, despite access to Medicare. These survivors may be less likely to see specialists, including oncologists, and receive basic preventive care.

Rural-urban differences in health behaviors and implications for health status among US cancer survivors.

PURPOSE: Rural US adults have increased risk of poor outcomes after cancer, including increased cancer mortality. Rural-urban differences in health behaviors have been identified in the general population and may contribute to cancer health disparities, but have not yet been examined among US survivors. We examined rural-urban differences in health behaviors among cancer survivors and associations with self-reported health and health-related unemployment. METHODS: We identified rural (n = 1,642) and urban (n = 6,162) survivors from the cross-sectional National Health Interview Survey (2006-2010) and calculated the prevalence of smoking, physical activity, overweight/obesity, and alcohol consumption. Multivariable models were used to examine the associations of fair/poor health and health-related unemployment with health behaviors and rural-urban residence. RESULTS: The prevalence of fair/poor health (rural 36.7 %, urban 26.6 %), health-related unemployment (rural 18.5 %, urban 10.6 %), smoking (rural 25.3 %, urban 15.8 %), and physical inactivity (rural 50.7 %, urban 38.7 %) was significantly higher in rural survivors (all p < .05); alcohol consumption was lower (rural 46.3 %, urban 58.6 %), and there were no significant differences in overweight/obesity (rural 65.4 %, urban 62.6 %). All health behaviors were significantly associated with fair/poor health and health-related unemployment in both univariate and multivariable models. After adjustment for behaviors, rural survivors remained more likely than urban survivors to report fair/poor health (OR = 1.21, 95 % CI 1.03-1.43) and health-related unemployment (OR = 1.49, 95 % CI 1.18-1.88). CONCLUSIONS: Rural survivors may need tailored, accessible health promotion interventions to address health-compromising behaviors and improve outcomes after cancer.

Geriatric assessment predicts survival for older adults receiving induction chemotherapy for acute myelogenous leukemia.

We investigated the predictive value of geriatric assessment (GA) on overall survival (OS) for older adults with acute myelogenous leukemia (AML). Consecutive patients ≥ 60 years with newly diagnosed AML and planned intensive chemotherapy were enrolled at a single institution. Pretreatment GA included evaluation of cognition, depression, distress, physical function (PF) (self-reported and objectively measured), and comorbidity. Objective PF was assessed using the Short Physical Performance Battery (SPPB, timed 4-m walk, chair stands, standing balance) and grip strength. Cox proportional hazards models were fit for each GA measure as a predictor of OS. Among 74 patients, the mean age was 70 years, and 78.4% had an Eastern Cooperative Oncology Group (ECOG) score ≤ 1. OS was significantly shorter for participants who screened positive for impairment in cognition and objectively measured PF. Adjusting for age, gender, ECOG score, cytogenetic risk group, myelodysplastic syndrome, and hemoglobin, impaired cognition (Modified Mini-Mental State Exam < 77) and impaired objective PF (SPPB < 9) were associated with worse OS. GA methods, with a focus on cognitive and PF, improve risk stratification and may inform interventions to improve outcomes for older AML patients.

Rural-urban disparities in health status among US cancer survivors.

BACKGROUND: Although rural residents are more likely to be diagnosed with more advanced cancers and to die of cancer, little is known about rural-urban disparities in self-reported health among survivors. METHODS: The authors identified adults who had a self-reported history of cancer from the National Health Interview Survey (2006-2010). Rural-urban residence was defined using US Census definitions. Logistic regression with weighting to account for complex sampling was used to assess rural-urban differences in health status after accounting for differences in demographic characteristics. RESULTS: Of the 7804 identified cancer survivors, 20.8% were rural residents. This translated to a population of 2.8 million rural cancer survivors in the United States. Rural survivors were more likely than urban survivors to be non-Hispanic white (P < .001), to have less education (P < .001), and to lack health insurance (P < .001). Rural survivors reported worse health in all domains. After adjustment for sex, race/ethnicity, age, marital status, education, insurance, time since diagnosis, and number of cancers, rural survivors were more likely to report fair/poor health (odds ratio, 1.39; 95% confidence interval, 1.20-1.62), psychological distress (odds ratio, 1.23; 95% confidence interval, 1.00-1.50), ≥2 noncancer comorbidities (odds ratio, 1.15; 95% confidence interval, 1.01-1.32), and health-related unemployment (odds ratio, 1.66; 95% confidence interval, 1.35-2.03). CONCLUSIONS: The current results provide the first estimates of the proportion and number of US adult cancer survivors who reside in rural areas. Rural cancer survivors are at greater risk for a variety of poor health outcomes, even many years after their cancer diagnosis, and should be a target for interventions to improve their health and well being.

The feasibility of inpatient geriatric assessment for older adults receiving induction chemotherapy for acute myelogenous leukemia.

OBJECTIVES: To test the feasibility and utility of a bedside geriatric assessment (GA) to detect impairment in multiple geriatric domains in older adults initiating chemotherapy for acute myelogenous leukemia (AML). DESIGN: Prospective observational cohort study. SETTING: Single academic institution. PARTICIPANTS: Individuals aged 60 and older with newly diagnosed AML and planned chemotherapy. MEASUREMENTS: Bedside GA was performed during inpatient exmination for AML. GA measures included the modified Mini-Mental State Examination; Center for Epidemiologic Studies Depression Scale; Distress Thermometer, Pepper Assessment Tool for Disability (includes self- reported activities of daily living (ADLs), instrumental ADLs, and mobility questions); Short Physical Performance Battery (includes timed 4-m walk, chair stands, standing balance); grip strength, and Hematopoietic Cell Transplantation Comorbidity Index. RESULTS: Of 54 participants (mean age 70.8 ± 6.4) eligible for this analysis, 92.6% completed the entire GA battery (mean time 44.0 ± 14 minutes). The following impairments were detected: cognitive impairment, 31.5%; depression, 38.9%; distress, 53.7%; impairment in ADLs, 48.2%; impaired physical performance, 53.7%; and comorbidity, 46.3%. Most were impaired in one (92.6%) or more (63%) functional domains. For the 38 participants rated as having good performance status according to standard oncologic assessment (Eastern Cooperative Oncology Performance Scale score ≤1), impairments in individual GA measures ranged from 23.7% to 50%. Significant variability in cognitive, emotional, and physical status was detected even after stratification according to tumor biology (cytogenetic risk group classification). CONCLUSION: Inpatient GA was feasible and added new information to standard oncology assessment, which may be important for stratifying therapeutic risk in older adults with AML.

Adjuvant chemotherapy among medicaid-enrolled patients diagnosed with nonmetastatic colon cancer.

OBJECTIVE: It has been suggested that low-income populations may not receive adjuvant chemotherapy for colon cancer, although factors associated with its receipt have not been well-elucidated. This article describes the characteristics associated with chemotherapy among a Medicaid-insured population diagnosed with colon cancer. METHODS: A retrospective cohort design among 692 Medicaid-insured individuals diagnosed with regional colon cancer was conducted. Logistic regression analyses assessed patient, hospital, and community characteristics associated with chemotherapy. Data were derived from the N.C. Central Cancer Registry, N.C. Medicaid Claims, the American Hospital Directory, and the US Census. RESULTS: Forty-two percent received chemotherapy. Persons <65 years of age, diagnosis and treatment at different facilities, and living in a community with a higher percentage of persons in poverty were associated with receipt of chemotherapy. Individuals <65 years at time of diagnosis and had a score of 1+ on the Charlson Comorbidity index were 16% less likely to receive chemotherapy as those less than 65 years of age with no comorbid conditions. Receipt of chemotherapy among those 65 to 74 and those 75 and older did not differ appreciably by comorbidity status. CONCLUSION: Patient age was important in predicting who received adjuvant care, although the impact of comorbidity on chemotherapy was more pronounced among those <65 years of age.

Under utilization of surveillance mammography among older breast cancer survivors.

BACKGROUND: Annual surveillance mammography is recommended for follow-up of women with a history of breast cancer. We examined surveillance mammography among breast cancer survivors who were enrolled in integrated healthcare systems. METHODS: Women in this study were 65 or older when diagnosed with early stage invasive breast cancer (N = 1,762). We assessed mammography use during 4 years of follow-up, using generalized estimating equations to account for repeated measurements. RESULTS: Eighty-two percent had mammograms during the first year after treatment; the percentage declined to 68.5% in the fourth year of follow-up. Controlling for age and comorbidity, women who were at higher risk of recurrence by being diagnosed at stage II or receiving breast-conserving surgery (BCS) without radiation therapy were less likely to have yearly mammograms (compared to stage I, odds ratio [OR] for stage IIA 0.72, confidence interval [CI] 0.59, 0.87, OR for stage IIB 0.75, CI 0.57, 1.0; compared to BCS with radiation, OR 0.58, CI 0.43, 0.77). Women with visits to a breast cancer surgeon or oncologist were more likely to receive mammograms (OR for breast cancer surgeon 6.0, CI 4.9, 7.4, OR for oncologist 7.4, CI 6.1, 9.0). CONCLUSIONS: Breast cancer survivors who are at greater risk of recurrence are less likely to receive surveillance mammograms. Women without a visit to an oncologist or breast cancer surgeon during a year have particularly low rates of mammography. Improvements to surveillance care for breast cancer survivors may require active participation by primary care physicians and improvements in cancer survivorship programs by healthcare systems.