Abstract
Objective
This study examined the receipt of therapies for cancer, hypertension, and diabetes in association with age and racial disparities in mortality among women with breast cancer.
Methods
This study identified 92,829 women diagnosed with breast cancer at age ≥ 65 years in 2007–2015 with follow-up to 2016 from the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database.
Results
There were substantial age and racial disparities in the prevalence of hypertension and diabetes, which was higher in women ≥ 75 (86.3% and 32.0%) than younger women 65–74 (72.8% and 29.3%), and the highest in Black women (91.1% and 49.1%), followed by Asian women (80.2% and 40.5%), and White women (77.6 and 27.8%). Black women were significantly less likely to receive chemotherapy (odds ratio: 0.70, 95% CI: 0.64–0.75), radiation therapy (0.87, 0.83–0.92), and hormone therapy (0.80, 0.76–0.85), but significantly more likely to receive antihypertensive (1.26, 1.19–1.33) and antidiabetic (1.19, 1.10–1.28) drugs than White women, after adjusting for sociodemographic and tumor factors. As compared to White women, Black women had a significantly higher risk of all-cause mortality (1.46, 1.41–1.52), but it became insignificant after adjusting for treatment factors (1.01, 0.97–1.06), whereas the adjusted risk of breast cancer-specific mortality remained significantly higher (1.08, 1.01–1.15) in Black women; Asian and other ethnic women had a significantly lower risk of all-cause and breast cancer-specific mortality.
Conclusions
There were substantial age and racial disparities in the prevalence of hypertension and diabetes and in the receipt of medications. Black women did not have a significantly higher risk of all-cause mortality but had a significantly higher risk of breast cancer-specific mortality as compared to White women.
Keywords: Breast cancer, Racial disparities, Chemotherapy, Antihypertensive treatment, Antidiabetic treatment, SEER areas
Introduction
Substantial racial and ethnic disparities in health care and clinical outcomes, including mortality and survival, have been reported over the past several decades [1–20]. Studies on racial disparities in the receipt of standard therapy for medical illnesses and cancer are extremely consistent, as highlighted by the Institute of Medicine’s report on unequal treatments in different ethnicities [1] and other reports [2–10]. However, findings on racial disparities in mortality and survival in patients with cancer have been less consistent, likely due to heterogeneities in study designs, methods, measurements, analyses, and adjustments for confounding factors [11–34]. This issue is further complicated by comorbid conditions in patients with cancer, which can affect the overall outcomes of patients with cancer. Yet few studies on racial disparities in cancer patients have examined the receipt of treatment for their comorbid illnesses. One of the main reasons is that there is a lack of clinical treatment data for treating comorbid diseases. In 2006, Medicare Part D comprehensive drug coverage was implemented in the USA, making it possible to examine the receipts of treatment for comorbid conditions in patients diagnosed with cancer. In addition, older women with breast cancer were reported to be less likely to receive adjuvant therapies due to concern of their low tolerance for therapy-related toxicities and other reasons. Therefore, this study aimed to examine the prevalence of two common comorbid illnesses (i.e., hypertension and diabetes) in patients with breast cancer, and to explore age and racial disparities in the receipt of anticancer, antihypertensive, and antidiabetic medications and the impact of these treatments on survival in women with breast cancer.
Methods
Data Sources
This study used the de-identified SEER-Medicare linked database for breast cancer cases in 2007–2015 with a follow-up to 2016. The SEER program, supported by the National Cancer Institute (NCI), includes 17 population-based tumor registries in 8 states (Connecticut, Iowa, New Mexico, Utah, Hawaii, Kentucky, Louisiana, and New Jersey), 7 metropolitan or rural areas (San Francisco/Oakland, Detroit, Atlanta, Seattle, Rural Georgia, Los Angeles County, and the San Jose-Monterey areas), Greater California, and Greater Georgia, covering 27.8% of the US population since 2000. The Medicare program provides payments for hospital, physician, and outpatient medical services for > 97% of people aged ≥ 65 [35, 36]. Cases reported by SEER cancer registries were linked with Medicare claims [35]. The Committee for the Protection of Human Subjects at the University of Texas Health Science Center at Houston approved this study.
Study Population
The study population consisted of 92,829 women who were diagnosed with breast cancer at age ≥ 65 years from 2007 through 2015, and who had full coverage of both Medicare Part A and Part B and were not enrolled with Health Maintenance Organizations from the date of diagnosis to the date of death or the date of the last follow-up on December 31, 2016.
Study Variables
Sociodemographic Variables
Main sociodemographic variables include age at diagnosis (categorized as 65–69, 70–74, 75–79, 80–89, and > = 90) and race/ethnicity (classified as White, Black, Asian, or Pacific Islanders, and others). Other sociodemographic variables are marital status (married, unmarried, or unknown), health insurance status (insured for private insurance, Medicaid, uninsured, or unknown) at the time of breast cancer diagnosis, SEER areas (by state), and year of diagnosis.
Comorbidity
Comorbidities are defined as coexisting medical conditions other than the study interest of cancer under study. Hypertension and diabetes were mainly examined for their prevalence and treatment. Hypertension was defined if there was an ICD-9 diagnosis code of 401, 402, 403, 404, or 405; or if there was an ICD-10 diagnosis code of I10, I11, I12, I13, or I15 in Medicare claims (inpatient, outpatient, and physician claim files). Diabetes was defined if there was a diagnosis code of 250.1–250.9 or E08-E13. Hence, comorbidities in this study included myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, chronic pulmonary disease, congestive tissue disease, ulcer disease, mild liver disease, hemiplegia, moderate or severe renal disease, leukemia, moderate or severe liver disease, and acquired immune deficiency syndrome. These coexisting medical conditions were identified through diagnoses or procedures in Medicare claims (inpatient, outpatient, and physician claim files) made within 1 year prior to and 30 days after the date of breast cancer diagnosis based on the comorbidity program and codes of the National Cancer Institute [35]. Each comorbid disease was weighted according to the severity of comorbid conditions [35, 37, 38] and was well validated using Medicare claims [37, 38]. The sum of all scores was analyzed as a categorical variable (scores of 0, 1, 2, and ≥ 3).
Tumor Characteristics
Tumor characteristics include tumor stage (in situ, AJCC stages I–IV, or unknown), tumor grade (well, moderately or poorly differentiated, or unknown), tumor size (in cm), and hormone receptor status (estrogen receptor or progesterone receptor-positive, negative, or unknown).
Treatment for Breast Cancer, Hypertension, and Diabetes
Details on the definition of surgery for breast cancer from SEER and Medicare data were described elsewhere [17]. Patients were categorized as having received cancer-directed surgery (breast-conserving surgery or mastectomy) or not. Breast-conserving surgery was defined as receiving segmental mastectomy, lumpectomy, quadrantectomy, tylectomy, wedge resection, nipple resection, or excisional biopsy. Mastectomy was defined as subcutaneous, total, modified radical, radical, or extended radical mastectomy. Similarly, patients were defined as having received radiation therapy if either SEER or Medicare claims so indicated [4]. Chemotherapy was defined if there were a claim or procedure for chemotherapy: the ICD-9 procedure code of 99.25 or ICD-10 procedure of Z51.11, the CPT codes 96400–96549, J8530-J8999, J9000-J9999, or Q0083-Q0085, or revenue center codes 0331, 0332, or 0335 [35]. Hormone therapy for breast cancer was defined as having received selective estrogen receptor modulators (SERMs, tamoxifen cirate, nolvadex, fareston, evista, tamoxifen citrate, toremifene citrate, nolvadex, or raloxifene hcl) or aromatase inhibitors (AIs, anastrozole, letrozole, exemestane, arimidex, aromasin, or femara) in Medicare Part D drug files. Antihypertensive drugs were identified through both generic and brand drug names (variables GNN and BN) in Medicare Part D drug files [7–9] These drugs were then classified into the following antihypertensive medication classes: aldosterone receptor antagonists, α-blockers, angiotensin-converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), β-blockers, calcium channel blockers (CCBs), central-acting agents, direct vasodilators, diuretics (thiazide, loop, and potassium-sparing, separately), and renin inhibitors (see Supplement Table S1) [39]. Antidiabetic drugs were also identified from Medicare Part D drug files, including 15 categories of drugs (see Supplement Table S2) [40].
Mortality Outcome Variables
All-cause mortality was defined as death from any cause as indicated in the SEER registry data by December 31, 2015, or in Medicare data by December 31, 2016. The cause of death is identified by the SEER program through linking the SEER data with the National Death Index data from the National Center for Vital Statistics. Patients still alive at the last date of follow-up (December 31, 2016) were censored. Breast cancer-specific mortality was defined as breast cancer as the underlying cause of death in SEER data. In this specific analysis, patients who died of causes other than breast cancer or who were still alive at the date of the last follow-up were censored. Survival time in months was calculated from the date of diagnosis to the date of death or to the date of last follow-up (December 31, 2016).
Analysis
Differences in the distribution of baseline characteristics among age groups and racial/ethnic groups were tested using the chi-square statistics. The adjusted odds ratios of receiving chemotherapy, radiation therapy, and hormone therapy for breast cancer, and the adjusted odds ratios of receiving antihypertensive and antidiabetic drugs were obtained from multiple logistic regression models, adjusting for patient demographic characteristics, tumor biological factors, comorbidity, year of diagnosis, and geographic area. Cox proportional hazard regression model was used for the analysis of survival using the PHREG procedure available in the SAS system version 9.4 (Cary, NC: SAS Institute, Inc). The proportionality assumption was considered to be satisfied when the log–log Kaplan–Meier curves for survival functions by race/ethnicity were parallel and did not intersect. In the Cox proportional hazard regression analyses, three models were presented. The first model was a crude analysis without adjustments for other factors. The second model adjusted for patient demographic characteristics (including age and marital status), tumor biological factors (tumor stage, grade, size, and hormone receptor status), comorbidity, year of diagnosis, geographic area. The third model adjusted for the treatments for breast cancer, hypertension, and diabetes in addition to factors in the second model.
Results
Table 1 presents the distribution of baseline characteristics in women with breast cancer by race/ethnicity and age groups. The mean and median ages are almost identical by race/ethnicity groups and there was a slightly higher proportion of younger age in White patients diagnosed with breast cancer. A higher percentage of White and Asian women were married than that of Black women. The proportion of having private health insurance at the time of cancer diagnosis was the highest in White women, followed by Asian, Black, and others. Overall, Asian and White women had more favorable tumor characteristics than Black women, such as higher percentages of having earlier tumor stage, smaller size, better grade, and more positive hormone receptor status. Black and Asian women had a higher percentage of comorbidity scores of > 1 and a much higher prevalence of hypertension (91.1% and 80.2%) and diabetes (49.1% and 40.5%) than White women (77.6% for hypertension and 27.8% for diabetes).
Table 1.
Comparison of patient and tumor characteristics in women diagnosed with breast cancer by age and race/ethnicity, 2007–2015
| Number of cases (column %) by race/ethnicity | Number of cases (column %) by age | |||||||
|---|---|---|---|---|---|---|---|---|
|
|
|
|||||||
| Patient and tumor characteristics | Whites | Blacks | Asians/PI | Others | P-value | 65–74 | 75 or older | P-value |
|
| ||||||||
| Median age (range) | 74 (65–114) | 73 (65–104) | 73 (65–100) | 73(65–103) | < 0.001 | 69 (65–74) | 81(75–114) | < 0.001 |
| Age (years) | ||||||||
| 65–69 | 23,291 (29.5) | 2549 (30.5) | 1499 (32.2) | 275 (31.8) | < 0.001 | 27,614 (54.83) | 0 | < 0.001 |
| 70–74 | 19,173 (24.3) | 2112 (25.3) | 1223 (26.3) | 244 (28.2) | 22,752 (45.17) | 0 | ||
| 75–79 | 15,013 (19.0) | 1602 (19.2) | 887 (19.1) | 139 (16.1) | 0 | 17,641 (41.54) | ||
| 80–89 | 18,219 (23.1) | 1696 (20.3) | 902 (19.4) | 163 (18.9) | 0 | 3842 (9.05) | ||
| 90 or older | 3265 (4.1) | 392 (4.7) | 142 (3.1) | 43 (5.0) | 0 | 20,980 (49.41) | ||
| Race/ethnicity | ||||||||
| Whites | 78,961 (100.0) | 0 | 0 | 0 | 42,464 (84.3) | 36,497 (86.0) | < 0.001 | |
| Blacks | 0 | 8351 (100.0) | 0 | 0 | 4661 (9.3) | 3690 (8.7) | ||
| Asians/Pacific Islanders | 0 | 0 | 4653 (100.0) | 0 | 2722 (5.4) | 1931 (4.6) | ||
| Others | 0 | 0 | 0 | 864 (100.0) | 519 (1.0) | 345 (0.8) | ||
| Marital status | ||||||||
| Married | 34,188 (43.3) | 1694 (20.3) | 2279 (49.0) | 229 (26.5) | < 0.001 | 25,585 (50.8) | 12,805 (30.2) | < 0.001 |
| Unmarried | 40,412 (51.2) | 6103 (73.1) | 2156 (46.3) | 334 (38.7) | 22,075 (43.8) | 26,930 (63.4) | ||
| Unknown | 4361 (5.5) | 554 (6.6) | 218 (4.7) | 301 (34.8) | 2706 (5.4) | 2728 (6.4) | ||
| Health insurance status at the time of cancer diagnosis | ||||||||
| Insured for private insurance | 69,157 (87.6) | 5953 (71.3) | 3381 (72.7) | 514 (59.5) | < 0.001 | 43,377 (86.1) | 35,628 (83.9) | < 0.001 |
| Medicaid | 7097 (9.0) | 2083 (24.9) | 1122 (24.1) | 125 (14.5) | 5528 (11.0) | 4899 (11.5) | ||
| Uninsured/missing | 2707 (2.4) | 315 (3.8) | 150 (3.3) | 225 (26.0) | 1461 (2.9) | 1936 (4.6) | ||
| AJCC tumor stage | ||||||||
| 0 (in situ) | 11,743 (14.9) | 1398 (16.7) | 921 (19.8) | 165 (19.1) | < 0.001 | 8975 (17.8) | 5252 (12.4) | < 0.001 |
| I | 32,978 (41.8) | 2552 (30.6) | 1811 (38.9) | 268 (31.0) | 21,425 (42.5) | 16,184 (38.1) | ||
| II | 19,554 (24.8) | 2354 (28.2) | 1180 (25.4) | 190 (22.0) | 12,236 (24.3) | 11,042 (26.0) | ||
| III | 5977 (7.6) | 848 (10.2) | 337 (7.2) | 50 (5.8) | 3641 (7.2) | 3571 (8.4) | ||
| IV | 4795 (6.1) | 708 (8.5) | 192 (4.1) | 29 (3.4) | 2585 (5.1) | 3139 (7.4) | ||
| Unknown/missing | 3914 (5.0) | 491 (5.9) | 212 (4.6) | 162 (18.8) | 1504 (3.0) | 3275 (7.7) | ||
| Tumor size (cm) | ||||||||
| < 1 | 17,820 (22.6) | 1427 (17.1) | 1085 (23.3) | 160 (18.5) | < 0.001 | 12,312 (24.4) | 8180 (19.3) | < 0.001 |
| 1– < 2 | 24,730 (31.3) | 2160 (25.9) | 1371 (29.5) | 209 (24.2) | 16,237 (32.2) | 12,233 (28.8) | ||
| 2– < 3 | 12,815 (16.2) | 1408 (16.9) | 808 (17.4) | 125 (14.5) | 7952 (15.8) | 7204 (17.0) | ||
| 3– < 4 | 6255 (7.9) | 811 (9.7) | 436 (9.4) | 61 (7.1) | 3746 (7.4) | 3817 (9.0) | ||
| ≥ 4 | 10,540 (13.4) | 1646 (19.7) | 645 (13.9) | 111 (12.9) | 6300 (12.5) | 6642 (15.6) | ||
| Missing | 6801 (8.6) | 899 (10.8) | 308 (6.6) | 198 (22.9) | 3819 (7.6) | 4387 (10.3) | ||
| Tumor grade | ||||||||
| Well differentiated | 17,670 (22.4) | 1346 (16.1) | 1006 (21.6) | 189 (21.9) | < 0.001 | 11,210 (22.3) | 9001 (21.2) | < 0.001 |
| Moderately differentiated | 32,738 (41.5) | 3102 (37.2) | 2018 (43.4) | 334 (38.7) | 20,834 (41.4) | 17,358 (40.9) | ||
| Poorly differentiated | 20,225 (25.6) | 2777 (33.3) | 1234 (26.5) | 192 (22.2) | 13,775 (27.4) | 10,653 (25.1) | ||
| Unknown/missing | 8328 (10.6) | 1126 (13.5) | 395 (8.5) | 149 (17.3) | 4547 (9.0) | 5451 (12.8) | ||
| Hormone receptor status | ||||||||
| Positive | 63,175 (80.0) | 5998 (71.8) | 3682 (79.1) | 627 (72.6) | < 0.001 | 40,531 (80.5) | 32,951 (77.6) | < 0.001 |
| Negative | 9666 (12.2) | 1603 (19.2) | 653 (14.0) | 72 (8.3) | 6702 (13.3) | 5292 (12.5) | ||
| Unknown | 6120 (7.8) | 750 (9.0) | 318(6.8) | 165 (19.1) | 3133 (6.2) | 4220 (9.9) | ||
| Comorbidity scores | ||||||||
| 0 | 46,732 (59.2) | 4274 (51.2) | 3031 (65.1) | 535 (61.9) | < 0.001 | 32,517 (64.6) | 22,055 (51.9) | < 0.001 |
| 1 | 21,392 (27.1) | 2271 (27.2) | 1088 (23.4) | 209 (24.2) | 12,464 (24.8) | 12,496 (29.4) | ||
| ≥ 2 | 10,837 (13.7) | 1806 (21.6) | 534 (11.5) | 120 (13.9) | 5385 (10.7) | 7912 (18.6) | ||
| Hypertension | ||||||||
| No | 17,670 (22.4) | 742 (8.9) | 921 (19.8) | 191 (22.1) | < 0.001 | 13,703 (27.2) | 5821 (13.7) | < 0.001 |
| Yes | 61,291 (77.6) | 7609 (91.1) | 3732 (80.2) | 673 (77.9) | 36,663 (72.8) | 36,642 (86.3) | ||
| Diabetes | ||||||||
| No | 56,978 (72.2) | 4254 (50.9) | 2770 (59.5) | 532 (61.6) | < 0.001 | 35,636 (70.8) | 28,898 (68.1) | < 0.001 |
| Yes | 21,983 (27.8) | 4097 (49.1) | 1883 (40.5) | 332 (38.4) | 14,730 (29.3) | 13,565 (32.0) | ||
| Year of diagnosis | < 0.001 | < 0.001 | ||||||
| 2007 | 7623 (9.7) | 854 (10.2) | 384 (8.3) | 50 (5.8) | 4347 (8.6) | 4564 (10.8) | ||
| 2008 | 7572 (9.6) | 787 (9.4) | 411 (8.8) | 61 (7.1) | 4440 (8.8) | 4391 (10.3) | ||
| 2009 | 7846 (9.9) | 837 (10.0) | 415 (8.9) | 58 (6.7) | 4708 (9.4) | 4448 (10.5) | ||
| 2010 | 7756 (9.8) | 787 (9.4) | 475 (10.2) | 70 (8.1) | 4773 (9.5) | 4315 (10.2) | ||
| 2011 | 8517 (10.8) | 868 (10.4) | 481 (10.3) | 90 (10.4) | 5337 (10.6) | 4619 (10.9) | ||
| 2012 | 9551 (12.1) | 992 (11.9) | 595 (12.8) | 94 (10.9) | 6079 (12.1) | 5153 (12.1) | ||
| 2013 | 9721 (12.3) | 1073 (12.9) | 595 (12.8) | 128 (14.8) | 6460 (12.8) | 5057 (11.9) | ||
| 2014 | 10,073 (12.8) | 1062 (12.7) | 648 (13.9) | 143 (16.6) | 6996 (13.9) | 4930 (11.6) | ||
| 2015 | 10,302 (13.1) | 1091 (13.1) | 649 (14.0) | 170 (19.7) | 7226 (14.4) | 4986 (11.7) | ||
| Total | 78,961 | 8351 | 4653 | 864 | 50,366 | 42,463 | ||
P-values were from the chi-square test
Table 2 presents the percentage of receiving chemotherapy, radiation therapy, and hormone therapy in women with breast cancer, and the percentages of receiving antihypertensive and antidiabetic drugs in those with breast cancer who also had hypertension and diabetes, whereas Table 3 presents the odds ratio of receiving these therapies by adjusting for potential confounding factors. Younger women aged 65–69 had a higher percentage of receiving chemotherapy (19.1%), radiation therapy (59.2%), and antidiabetic therapy (37.5%) as compared to 3.3%, 10.4 and 34.4% respectively in those aged ≥ 90, but had a lower percentage of receiving hormone therapy (39.4%) and antihypertensive therapy (60.6%) than 44.3% and 67.1% in women aged ≥ 90. The adjusted odds ratios of receiving these therapies were statistically significantly different by age group. There were also significant differences in receiving these therapies between Black and White women with breast cancer. For example, Black women were significantly less likely to receive chemotherapy (odds ratio: 0.70, 95% CI: 0.64–0.75), radiation therapy (0.87, 0.83–0.92), and hormone therapy (0.80, 0.76–0.85), but significantly more likely to receive antihypertensive (1.26, 1.19–1.33) and antidiabetic (1.19, 1.10–1.28) drugs than White women, after adjusting for sociodemographic and tumor factors. Asian women were less likely to receive radiation therapy, more likely to receive hormone therapy and antidiabetic therapy, and not significantly different in receiving chemotherapy and antihypertensive therapy as compared to White women. Married women were more likely to receive chemotherapy and radiation therapy and less likely to receive antihypertensive and antidiabetic therapies but had no significant difference in receiving hormone therapy as compared to unmarried women. There were no significant differences in receiving these therapies according to health insurance status (insured and uninsured) at the time of cancer diagnosis. Not surprisingly, the receipt of cancer therapies was associated with tumor characteristics and those with a comorbidity score of > 1 were significantly less likely to receive chemotherapy and radiation therapy but more likely to receive hormone therapy, antihypertensive and antidiabetic therapies. There was no obvious trend over time in receiving these therapies except that the receipt of hormone therapy appeared to increase from 2007 to 2015. Some geographic variations by SEER areas in these therapies were also observed.
Table 2.
Percentages of receiving therapies for breast cancer and for hypertension and diabetes in a cohort of women with breast cancer by race/ethnicity, age, and other factors
| In women with breast cancer (N = 92,829) | In women breast cancer ERPR + (N = 73,482) | In women with breast cancer who also had hypertension (N = 73,305) | In women with breast cancer who also had diabetes (N = 28,295) | ||
|---|---|---|---|---|---|
|
|
|||||
| Characteristics | Chemotherapy | Radiation therapy | Hormone therapy | Antihypertensives | Antidiabetics |
|
| |||||
| Age (years) | |||||
| 65–69 | 19.13 | 59.17 | 39.35 | 60.56 | 37.45 |
| 70–74 | 15.46 | 54.81 | 43.07 | 63.96 | 37.97 |
| 75–79 | 11.47 | 48.22 | 43.56 | 65.89 | 37.31 |
| 80–89 | 6.31 | 58.79 | 42.84 | 67.31 | 35.64 |
| 90 or older | 3.28 | 10.36 | 44.28 | 67.11 | 34.37 |
| Race/ethnicity | |||||
| Whites | 13.28 | 48.52 | 42.66 | 63.81 | 35.81 |
| Blacks | 13.42 | 41.61 | 38.31 | 69.63 | 41.86 |
| Asians/Pacific Islanders | 12.19 | 45.41 | 42.75 | 63.96 | 39.56 |
| Others | 11.69 | 38.19 | 41.31 | 63.15 | 42.77 |
| Marital status | |||||
| Married | 15.05 | 55.78 | 42.10 | 61.71 | 34.96 |
| Unmarried | 11.97 | 42.39 | 42.63 | 66.52 | 38.44 |
| Unknown | 11.50 | 37.63 | 40.73 | 62.77 | 35.82 |
| Health insurance status at the time of cancer diagnosis | |||||
| Insured for private insurance | 13.20 | 49.66 | 41.76 | 63.09 | 34.99 |
| Medicaid | 14.08 | 38.64 | 46.35 | 73.73 | 46.09 |
| Not insured | 19.31 | 41.63 | 41.36 | 62.50 | 45.68 |
| Unknown/missing | 10.56 | 27.65 | 43.42 | 62.67 | 37.01 |
| Tumor stage | |||||
| In situ | 1.72 | 9.34 | 28.83 | 64.12 | 34.58 |
| Local | 9.38 | 45.82 | 46.26 | 64.74 | 35.70 |
| Regional | 28.41 | 51.72 | 39.53 | 65.51 | 40.90 |
| Distant | 26.28 | 29.07 | 43.12 | 60.31 | 38.04 |
| Unknown/missing | 8.36 | 9.34 | 42.58 | 62.03 | 41.21 |
| Tumor size (cm) | |||||
| < 1 | 5.05 | 56.37 | 42.26 | 63.09 | 33.33 |
| 1– < 2 | 11.07 | 55.87 | 44.62 | 65.04 | 35.34 |
| 2– < 3 | 18.55 | 45.67 | 42.76 | 65.48 | 39.38 |
| 3– < 4 | 22.12 | 38.36 | 41.11 | 66.06 | 40.61 |
| ≥ 4 | 22.01 | 37.59 | 39.41 | 63.99 | 40.21 |
| Missing | 9.16 | 25.43 | 35.65 | 62.64 | 37.03 |
| Tumor grade | |||||
| Well differentiated | 5.28 | 52.65 | 44.86 | 64.17 | 35.53 |
| Moderately differentiated | 11.38 | 50.24 | 43.60 | 64.71 | 36.56 |
| Poorly differentiated | 23.89 | 47.81 | 36.56 | 64.63 | 39.11 |
| Unknown/missing | 10.21 | 27.27 | 40.98 | 63.30 | 36.21 |
| Hormone receptor status | |||||
| Positive | 11.09 | 50.71 | 42.30 | 64.57 | 36.66 |
| Negative | 29.72 | 46.17 | - | 64.36 | 38.72 |
| Unknown | 7.63 | 19.50 | - | 63.03 | 37.84 |
| Comorbidity scores | |||||
| 0 | 13.33 | 51.62 | 41.06 | 62.64 | 36.15 |
| 1 | 13.61 | 45.68 | 44.26 | 64.05 | 35.12 |
| ≥ 2 | 12.04 | 35.06 | 43.92 | 70.64 | 41.50 |
| Year of diagnosis | |||||
| 2007 | 13.48 | 43.96 | 37.04 | 65.21 | 37.80 |
| 2008 | 13.50 | 45.33 | 38.85 | 69.75 | 41.58 |
| 2009 | 12.71 | 45.54 | 38.89 | 69.39 | 39.99 |
| 2010 | 12.98 | 45.92 | 41.69 | 68.00 | 39.95 |
| 2011 | 13.53 | 47.21 | 41.26 | 64.77 | 36.66 |
| 2012 | 14.65 | 47.74 | 41.22 | 60.16 | 34.00 |
| 2013 | 14.16 | 48.06 | 45.62 | 63.09 | 35.16 |
| 2014 | 15.03 | 50.57 | 45.25 | 61.52 | 35.13 |
| 2015 | 9.15 | 51.92 | 46.52 | 60.79 | 35.32 |
| SEER areas | |||||
| Connecticut | 10.72 | 51.88 | 44.33 | 64.99 | 35.50 |
| Detroit | 14.20 | 54.59 | 38.40 | 58.87 | 30.92 |
| Hawaii | 10.68 | 52.26 | 38.16 | 61.43 | 42.52 |
| Iowa | 12.18 | 49.24 | 46.84 | 67.39 | 40.14 |
| New Mexico | 16.13 | 45.33 | 39.64 | 64.48 | 38.70 |
| Seattle | 12.08 | 54.90 | 36.74 | 67.46 | 40.77 |
| Utah | 16.99 | 53.20 | 40.40 | 64.77 | 41.29 |
| Atlanta/Rural Georgia | 15.29 | 47.66 | 44.54 | 64.86 | 40.67 |
| Kentucky | 13.29 | 41.14 | 48.82 | 67.10 | 39.56 |
| Louisiana | 14.65 | 42.01 | 44.67 | 67.72 | 42.45 |
| New Jersey | 13.04 | 48.38 | 46.43 | 61.45 | 31.95 |
| California | 12.64 | 46.25 | 38.52 | 64.41 | 36.94 |
Table 3.
Adjusted odds ratio (95% CI) of receiving therapies for breast cancer and for hypertension and diabetes in a cohort of women with breast cancer by age and race/ethnicity
| Adjusted* odds ratio (95% CI) of receiving therapies | |||||
|---|---|---|---|---|---|
|
|
|||||
| In women with breast cancer (N = 92,829) | In women breast cancer ERPR + (N = 73,482) | In women with breast cancer who also had hypertension (N = 73,305) | In women with breast cancer who also had diabetes (N = 28,295) | ||
|
|
|||||
| Characteristics | Chemotherapy | Radiation therapy | Hormone therapy | Antihypertensives | Antidiabetics |
|
| |||||
| Age (years) | |||||
| 65–69 | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| 70–74 | 0.75 (0.71–0.79) | 0.85 (0.82–0.88) | 1.15 (1.10–1.20) | 1.14 (1.09–1.19) | 1.02 (0.95–1.09) |
| 75–79 | 0.49 (0.46–0.52) | 0.67 (0.64–0.70) | 1.16 (1.11–1.21) | 1.22 (1.17–1.28) | 0.98 (0.91–1.05) |
| 80–89 | 0.21 (0.20–0.23) | 0.35 (0.34–0.37) | 1.18 (1.13–1.24) | 1.28 (1.22–1.33) | 0.88 (0.82–0.95) |
| 90 or older | 0.09 (0.07–0.11) | 0.11 (0.10–0.12) | 1.11 (1.02–1.21) | 1.30 (1.20–1.41) | 0.79 (0.68–0.91) |
| Race/ethnicity | |||||
| Whites | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| Blacks | 0.70 (0.64–0.75) | 0.87 (0.83–0.92) | 0.80 (0.76–0.85) | 1.26 (1.19–1.33) | 1.19 (1.10–1.28) |
| Asians/Pacific Islanders | 0.95 (0.85–1.05) | 0.79 (0.74–0.85) | 1.18 (1.09–1.27) | 0.99 (0.92–1.07) | 1.12 (1.00–1.25) |
| Others | 0.95 (0.75–1.20) | 0.83 (0.71–0.96) | 1.03(0.87–1.21) | 1.01 (0.86–1.18) | 1.31 (1.05–1.64) |
| Marital status | |||||
| Married | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| Unmarried | 0.81 (0.78–0.85) | 0.83 (0.80–0.85) | 0.99 (0.96–1.02) | 1.10 (1.07–1.14) | 1.09 (1.03–1.15) |
| Unknown | 0.83 (0.75–0.92) | 0.72 (0.67–0.77) | 0.89 (0.83–0.96) | 1.04 (0.96–1.11) | 1.05 (0.94–1.18) |
| Health insurance status at the time of cancer diagnosis | |||||
| Insured for private insurance | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| Medicaid | 0.96 (0.90–1.03) | 0.78 (0.74–0.81) | 1.30 (1.24–1.37) | 1.49 (1.42–1.57) | 1.44 (1.35–1.54) |
| Not insured | 1.13 (0.78–1.63) | 0.81 (0.61–1.07) | 1.03 (0.75–1.41) | 1.00 (0.74–1.37) | 1.52 (0.98–2.36) |
| Unknown/missing | 1.12 (0.97–1.28) | 0.77 (0.70–0.85) | 1.11 (1.00–1.23) | 1.02 (0.92–1.11) | 1.05 (0.91,1.22) |
| Tumor stage | |||||
| In situ | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| Local | 8.35 (7.29–9.55) | 1.17 (1.12–1.22) | 1.99 (1.89–2.10) | 0.97 (0.92–1.01) | 1.06 (0.98–1.15) |
| Regional | 25.79 (22.51–29.56) | 1.32 (1.26–1.39) | 1.60 (1.51–1.69) | 0.95 (0.90–1.01) | 1.20 (1.10–1.31) |
| Distant | 23.17 (20.07–26.75) | 0.78 (0.73–0.83) | 1.90 (1.76–2.05) | 0.77 (0.72–0.83) | 1.13 (1.01–1.27) |
| Unknown/missing | 12.53 (10.00–15.71) | 0.47 (0.39–0.55) | 1.79 (1.51–2.13) | 0.84 (0.74–0.95) | 1.34 (1.10–1.63) |
| Tumor size (cm) | |||||
| < 1 | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| 1– < 2 | 1.71 (1.58–1.84) | 0.99 (0.96–1.03) | 1.08 (1.03–1.12) | 1.07 (1.02–1.12) | 1.05 (0.98–1.13) |
| 2– < 3 | 2.37 (2.18–2.57) | 0.70 (0.67–0.73) | 1.04 (0.99–1.09) | 1.07 (1.01–1.13) | 1.21 (1.11–1.31) |
| 3– < 4 | 2.52 (2.30–2.77) | 0.55 (0.51–0.58) | 0.99 (0.93–1.06) | 1.09 (1.02–1.16) | 1.23 (1.11–1.36) |
| ≥ 4 | 2.43 (2.23–2.65) | 0.60 (0.57–0.63) | 0.95 (0.90,1.01) | 1.01 (0.95–1.07) | 1.21 (1.11–1.33) |
| Missing | 1.96 (1.73–2.21) | 0.54 (0.51–0.58) | 0.97 (0.89–1.05) | 0.99 (0.93–1.07) | 1.13 (1.01,1.26) |
| Tumor grade | |||||
| Well differentiated | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| Moderately differentiated | 1.81 (1.69–1.95) | 1.01 (0.97–1.04) | 0.98 (0.95–1.02) | 1.02 (0.98–1.07) | 1.01 (0.94–1.08) |
| Poorly differentiated | 3.38 (3.13–3.65) | 1.05 (1.01–1.10) | 0.79 (0.76–0.83) | 1.01 (0.97–1.07) | 1.07 (0.99–1.16) |
| Unknown/missing | 1.79 (1.61–1.99) | 0.74 (0.69–0.78) | 0.95 (0.89–1.02) | 1.03 (0.96–1.10) | 0.97 (0.87–1.07) |
| Hormone receptor status | |||||
| Positive | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| Negative | 2.45 (2.31–2.58) | 0.92 (0.88–0.96) | - | 0.96 (0.92–1.01) | 0.98 (0.91–1.06) |
| Unknown | 0.89 (0.80–0.99) | 0.44 (0.41–0.47) | - | 0.90 (0.84–0.96) | 1.00 (0.90–1.11) |
| Comorbidity scores | |||||
| 0 | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| 1 | 1.10 (1.05, 1.16) | 0.89 (0.86–0.92) | 1.10 (1.07–1.14) | 1.03 (1.00–1.07) | 0.95 (0.89–1.00) |
| ≥ 2 | 0.92 (0.86–0.98) | 0.67 (0.64–0.70) | 1.07 (1.02–1.12) | 1.36 (1.30–1.42) | 1.20 (1.13–1.28) |
| Year of diagnosis | |||||
| 2007 | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| 2008 | 1.00 (0.91–1.10) | 1.03 (0.97–1.10) | 1.09 (1.02–1.17) | 1.24 (1.15–1.33) | 1.17 (1.05–1.31) |
| 2009 | 0.94 (0.85–1.03) | 1.02 (0.96–1.09) | 1.10 (1.02–1.18) | 1.22 (1.14–1.31) | 1.11 (0.99–1.24) |
| 2010 | 0.97 (0.88–1.06) | 1.01 (0.95–1.08) | 1.24 (1.16–1.33) | 1.15 (1.07–1.23) | 1.09 (0.98–1.22) |
| 2011 | 1.04 (0.95–1.15) | 1.04 (0.98–1.17) | 1.22 (1.14–1.31) | 1.00 (0.93–1.07) | 0.98 (0.87,1.09) |
| 2012 | 1.15 (1.05–1.26) | 1.03 (0.97–1.09) | 1.24 (1.16–1.32) | 0.83 (0.77–0.88) | 0.88 (0.79–0.97) |
| 2013 | 1.11 (1.01–1.21) | 1.00 (0.95–1.07) | 1.49 (1.39–1.59) | 0.94 (0.88–1.01) | 0.92 (0.83–1.02) |
| 2014 | 1.18 (1.08–1.28) | 1.08 (1.02–1.14) | 1.47 (1.38–1.57) | 0.89 (0.84–0.95) | 0.93 (0.84–1.04) |
| 2015 | 0.60 (0.54–0.66) | 1.13 (1.07–1.20) | 1.55 (1.45–1.65) | 0.86 (0.81–0.92) | 0.94 (0.85–1.05) |
| SEER areas | |||||
| Connecticut | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| Detroit | 1.16 (1.01–1.33) | 1.14 (1.04–1.24) | 0.82 (0.74–0.89) | 0.74 (0.68–0.81) | 0.76 (0.66–0.88) |
| Hawaii | 0.86 (0.68–1.10) | 1.07 (0.92–1.24) | 0.70 (0.60–0.82) | 0.90 (0.77–1.06) | 1.28 (1.00–1.64) |
| Iowa | 1.08 (0.95–1.24) | 0.74 (0.68–0.80) | 1.12 (1.03–1.23) | 1.16 (1.06–1.27) | 1.30(1.11–1.51) |
| New Mexico | 1.36 (1.15–1.61) | 0.69 (0.62–0.78) | 0.84 (0.74–0.95) | 1.02 (0.90–1.17) | 1.12 (0.90–1.40) |
| Seattle | 0.97 (0.85–1.12) | 0.97 (0.89–1.05) | 0.73 (0.67–0.80) | 1.15 (1.04–1.27) | 1.24 (1.05–1.46) |
| Utah | 1.39 (1.17–1.65) | 0.87 (0.78–0.98) | 0.86 (0.76–0.98) | 1.07 (0.94–1.22) | 1.33 (1.07–1.66) |
| Atlanta/rural Georgia | 1.35 (1.21–1.52) | 0.74 (0.69–0.80) | 1.07 (0.99–1.16) | 0.97 (0.89–1.05) | 1.18 (1.04–1.35) |
| Kentucky | 1.05 (0.92–1.19) | 0.56 (0.52–0.61) | 1.20 (1.10–1.30) | 1.10 (1.01–1.20) | 1.16 (1.01–1.34) |
| Louisiana | 1.24 (1.09–1.41) | 0.65 (0.60–0.71) | 1.06 (0.97–1.16) | 1.04 (0.95–1.14) | 1.19 (1.03–1.38) |
| New Jersey | 1.18 (1.06–1.32) | 0.88 (0.82–0.94) | 1.13 (1.05–1.20) | 0.88 (0.81–0.95) | 0.87 (0.76–0.98) |
| California | 1.03 (0.93–1.15) | 0.72 (0.67–0.76) | 0.77 (0.72–0.83) | 0.97 (0.91–1.04) | 1.00 (0.89–1.13) |
Odds ratios from logistic regression were adjusted for variables listed in this table
Table 4 presents the odds ratios of receiving chemotherapy, radiation therapy, hormone therapy, antihypertensive, and antidiabetic drugs by age and race/ethnicity, stratified by health insurance status at the time of cancer diagnosis and tumor stage at diagnosis. Overall patterns and point estimates by age and race/ethnicity regardless of health insurance status and tumor stage were generally similar to the findings in Table 3, although 95% confidence intervals became wider due to the smaller number of cases in stratified analyses. For example, those aged 75–79 were significantly less likely to receive chemotherapy (0.48, 0.45–0.51 for insured women; 0.53, 0.37–0.75 for uninsured women) and more likely to receive antihypertensives (1.22, 1.16–1.28 for insured women; 1.37, 1.05–1.77 for uninsured women) as compared to women aged 65–69. Black women were significantly less likely to receive chemotherapy (0.68, 0.63–0.75 for insured; 0.60, 0.38–0.95 for uninsured) and more likely to receive antihypertensives (1.27, 1.19–1.35 for insured; 1.16, 0.87–1.53 for uninsured) as compared to White women.
Table 4.
Adjusted odds ratio (95% CI) of receiving therapies for breast cancer and for hypertension and diabetes in a cohort of women with breast cancer by age and race/ethnicity, stratified by health insurance status at the time of cancer diagnosis and tumor stage
| Adjusted* odds ratio (95% CI) of receiving therapies | |||||
|---|---|---|---|---|---|
|
|
|||||
| In women with breast cancer (N = 92,829) | In women breast cancer ERPR + (N = 73,482) | In women with breast cancer who also had hypertension (N = 73,305) | In women with breast cancer who also had diabetes (N = 28,295) | ||
|
|
|||||
| Characteristics | Chemotherapy | Radiation therapy | Hormone therapy | Antihypertensives | Antidiabetics |
|
| |||||
| Insured for private insurance at the time of cancer diagnosis | |||||
| Age (years) | |||||
| 65–69 | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| 70–74 | 0.74 (0.70–0.78) | 0.84 (0.81–0.88) | 1.16 (1.11–1.22) | 1.14 (1.09–1.20) | 1.03 (0.95–1.11) |
| 75–79 | 0.48 (0.45–0.51) | 0.67 (0.65– 0.70) | 1.16 (1.12–1.23) | 1.22 (1.16–1.28) | 0.98 (0.90–1.06) |
| 80 or older | 0.19 (0.17–0.20) | 0.32 (0.30– 0.33) | 1.15 (1.10–1.20) | 1.28 (1.22–1.34) | 0.89 (0.82–0.97) |
| Race/ethnicity | |||||
| Whites | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| Blacks | 0.68 (0.63–0.75) | 0.84 (0.80–0.90) | 0.78 (0.73–0.84) | 1.27 (1.19–1.35) | 1.26 (1.16–1.38) |
| Asians/Pacific Islanders | 0.91 (0.80–1.04) | 0.74 (0.68–0.80) | 1.13 (1.03–1.23) | 1.02 (0.93–1.12) | 1.20 (1.05–1.38) |
| Others | 0.89 (0.65–1.20) | 0.89 (0.74–1.07) | 1.03 (0.84–1.26) | 1.10 (0.89–1.36) | 1.48 (1.10–1.99) |
| Medicaid at the time of cancer diagnosis | |||||
| Age (years) | |||||
| 65–69 | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| 70–74 | 0.82 (0.70–0.95) | 0.82 (0.74–0.92) | 1.08 (0.96–1.22) | 1.10 (0.97–1.25) | 0.99 (0.85–1.16) |
| 75–79 | 0.55 (0.46–0.65) | 0.63 (0.56–0.71) | 1.10 (0.96–1.25) | 1.26 (1.09–1.44) | 1.00 (0.84–1.18) |
| 80 or older | 0.21 (0.18–0.26) | 0.31 (0.27–0.35) | 1.25 (1.10–1.41) | 1.27 (1.12–1.45) | 0.81 (0.69–0.95) |
| Race/ethnicity | |||||
| Whites | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| Blacks | 0.77 (0.65–0.92) | 0.98 (0.87–1.11) | 0.89 (0.79–1.02) | 1.22 (1.06–1.39) | 1.01 (0.86–1.18) |
| Asians/Pacific Islanders | 0.99 (0.80–1.22) | 0.92 (0.80–1.07) | 1.29 (1.10–1.50) | 0.97 (0.83–1.13) | 0.94 (0.78–1.15) |
| Others | 0.92 (0.54–1.58) | 1.06 (0.73–1.55) | 0.84 (0.56–1.26) | 0.92 (0.61–1.41) | 0.97 (0.60–1.57) |
| Not-insured/missing data at the time of cancer diagnosis | |||||
| Age (years) | |||||
| 65–69 | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| 70–74 | 0.77 (0.56–1.05) | 1.12 (0.89–1.41) | 1.21 (0.92–1.59) | 1.37 (1.06–1.78) | 0.92 (0.61–1.39) |
| 75–79 | 0.53 (0.37–0.75) | 0.77 (0.60–0.99) | 1.24 (0.92–1.66) | 1.37 (1.05–1.77) | 0.97 (0.64–1.47) |
| 80 or older | 0.20 (0.14–0.28) | 0.30 (0.23–0.38) | 1.61 (1.23–2.09) | 1.50 (1.19–1.89) | 0.83 (0.57–1.21) |
| Race/ethnicity | |||||
| Whites | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| Blacks | 0.60 (0.38–0.95) | 0.96 (0.70–1.30) | 0.92 (0.64–1.32) | 1.16 (0.87–1.53) | 1.29 (0.86–1.94) |
| Asians/Pacific Islanders | 1.03 (0.53–2.00) | 1.04 (0.64–1.69) | 1.11 (0.64–1.93) | 1.00 (0.61–1.62) | 0.79 (0.38–1.63) |
| Others | 1.11 (0.65–1.90) | 0.60 (0.39–0.92) | 1.01 (0.66–1.53) | 0.80 (0.57–1.14) | 1.08 (0.62–1.88) |
| Early tumor stage (0, I, II) | |||||
| Age (years) | |||||
| 65–69 | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| 70–74 | 0.76 (0.72–0.81) | 0.85 (0.81–0.88) | 1.14 (1.09–1.19) | 1.14 (1.09–1.19) | 1.03 (0.95–1.11) |
| 75–79 | 0.49 (0.46–0.53) | 0.68 (0.65–0.71) | 1.12 (1.07–1.17) | 1.23 (1.17–1.29) | 0.98 (0.90–1.06) |
| 80 or older | 0.21 (0.20–0.23) | 0.31 (0.30–0.32) | 1.07 (1.03–1.12) | 1.31 (1.25–1.37) | 0.89 (0.82–0.96) |
| Race/ethnicity | |||||
| Whites | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| Blacks | 0.75 (0.68–0.82) | 0.89 (0.84–0.95) | 0.77 (0.73–0.82) | 1.31 (1.23–1.40) | 1.22 (1.12–1.33) |
| Asians/Pacific Islanders | 0.82 (0.72–0.93) | 0.76 (0.71–0.82) | 1.13 (1.04–1.22) | 1.00 (0.92–1.09) | 1.12 (1.00–1.27) |
| Others | 0.71 (0.52–0.99) | 0.78 (0.66–0.93) | 1.09 (0.91–1.31) | 0.98 (0.81–1.18) | 1.47 (1.13–1.91) |
| Late tumor stage (III, IV, and unknown) | |||||
| Age (years) | |||||
| 65–69 | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| 70–74 | 0.74 (0.67–0.81) | 0.87 (0.79–0.96) | 1.26 (1.12–1.42) | 1.17 (1.05–1.30) | 0.97 (0.82–1.13) |
| 75–79 | 0.50 (0.45–0.55) | 0.66 (0.60–0.73) | 1.60 (1.41–1.80) | 1.21 (1.08–1.36) | 0.99 (0.83–1.16) |
| 80 or older | 0.18 (0.16–0.20) | 0.36 (0.33–0.40) | 2.16 (1.94–2.40) | 1.23 (1.12–1.35) | 0.80 (0.69–0.93) |
| Race/ethnicity | |||||
| Whites | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| Blacks | 0.67 (0.59–0.76) | 0.78 (0.70–0.88) | 0.84 (0.74–0.97) | 1.14 (1.02–1.27) | 1.09 (0.93–1.27) |
| Asians/Pacific Islanders | 1.13 (0.93–1.38) | 0.96 (0.80–1.15) | 1.27 (1.03–1.57) | 1.00 (0.82–1.20) | 1.06 (0.83–1.37) |
| Others | 1.27 (0.90–1.78) | 1.09 (0.79–1.51) | 0.75 (0.53–1.07) | 1.02 (0.74–1.39) | 0.96 (0.62–1.50) |
Odds ratios from logistic regression were adjusted for age, marital status, tumor stage, size, grade, year of diagnosis, SEER registries, and comorbidity score
The mean survival months in women with breast cancer between 2007 and 2016 were 100.3, 95.9, 86.8, and 61.4 for women aged 65–69, 70–74, 75–79, and ≥ 80, respectively; and 86.3 for Whites, 72.3 for Blacks, 94.9 for Asians/Pacific Islanders, and 91.6 for other women. Table 5 presents the crude and adjusted risk of all-cause mortality and breast cancer-specific mortality by age, race/ethnicity, and the type of therapies. The risk of both all-cause mortality and breast cancer-specific mortality increased significantly with age in both crude and adjusted Cox regression models. For example, the risk of all-cause mortality was 66% higher in women aged 75–79 (hazard ratio: 1.66, 95% CI: 1.59–1.73) and over 3 times higher in those aged 90 or older (3.87, 3.67–4.08) as compared to women aged 65–69, after adjusting for patient sociodemographic factors, tumor characteristics, and type of therapies for breast cancer, hypertension, and diabetes. The adjusted risk of breast cancer-specific mortality also increased with age and was 39% higher in women aged 75–79 (1.39, 1.31–1.48) and over 2 times higher in those aged 90 or older (2.29, 2.12–2.48) as compared to women aged 65–69 years.
Table 5.
Risk of all-cause and breast cancer-specific mortality in association with therapies for cancer, hypertension and diabetes by age and race/ethnicity
| Hazard ratio (95% CI) of all-cause mortality* | Hazard ratio (95% CI) of breast cancer-specific mortality* | |||||
|---|---|---|---|---|---|---|
|
|
|
|||||
| Model-1 | Model-2 | Model-3 | Model-1 | Model-2 | Model-3 | |
|
| ||||||
| Age (years) | ||||||
| 65–69 | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| 70–74 | 1.28 (1.22–1.33) | 1.23 (1.17–1.28) | 1.20 (1.15–1.26) | 1.12 (1.05–1.19) | 1.12 (1.05–1.19) | 1.22 (1.06–1.19) |
| 75–79 | 1.91 (1.83–1.99) | 1.75 (1.68–1.82) | 1.66 (1.59–1.73) | 1.45 (1.36–1.54) | 1.40 (1.32–1.50) | 1.39 (1.31–1.48) |
| 80–89 | 3.79 (3.65–3.93) | 2.81 (2.71–2.92) | 2.55 (2.45–2.65) | 5.65 (5.25–6.08) | 1.78 (1.69–1.89) | 1.73 (1.63–1.83) |
| 90 or older | 8.93 (8.50–9.37) | 4.51 (4.29–4.75) | 3.87 (3.67–4.08) | 2.48 (2.35–2.62) | 2.48 (2.29–2.68) | 2.29 (2.12–2.48) |
| Race/ethnicity | ||||||
| Whites | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| Blacks | 1.46 (1.41–1.52) | 1.10 (1.06–1.15) | 1.01 (0.97–1.06) | 1.64 (1.55–1.74) | 1.16 (1.09–1.23) | 1.08 (1.01–1.15) |
| Asians/Pacific Islanders | 0.66 (0.62–0.71) | 0.74 (0.68–0.79) | 0.71 (0.66–0.77) | 0.70 (0.63–0.77) | 0.80 (0.71–0.90) | 0.79 (0.71–0.89) |
| Others | 0.66 (0.56–0.78) | 0.58 (0.49–0.68) | 0.56 (0.47–0.66) | 0.69 (0.53–0.88) | 0.52 (0.40–0.67) | 0.52 (0.40–0.67) |
| Chemotherapy | ||||||
| No | 1.00 (reference) | - | 1.00 (reference) | 1.00 (reference) | - | 1.00 (reference) |
| Yes | 1.02 (0.98–1.05) | - | 0.72 (0.69–0.75) | 1.72 (1.64–1.80) | - | 0.77 (0.73–0.81) |
| Radiotherapy | ||||||
| No | 1.00 (reference) | - | 1.00 (reference) | 1.00 (reference) | - | 1.00 (reference) |
| Yes | 0.36 (0.35–0.37) | - | 0.65 (0.63–0.67) | 0.35 (0.34–0.37) | - | 0.72 (0.69–0.75) |
| Hormone therapy | ||||||
| Hormone receptor (HR) negative | 1.00 (reference) | - | 1.00 (reference) | 1.00 (reference) | - | 1.00 (reference) |
| HR positive-did not receive hormone therapy | 1.63(1.57–1.69) | - | 1.33 (1.28–1.38) | 2.41 (2.28–2.53) | - | 1.57 (1.49–1.66) |
| HR positive-received hormone therapy | 0.92 (0.89–0.94) | - | 0.73 (0.70–0.75) | 0.90 (0.85–0.94) | - | 0.68 (0.65–0.71) |
| Unknown/missing | 2.81(2.70–2.92) | - | 1.49 (1.42–1.56) | 4.24 (4.00–4.48) | - | 1.69 (1.57–1.81) |
| Hypertension treatment | ||||||
| No Hypertension | 1.00 (reference) | - | 1.00 (reference) | 1.00 (reference) | - | 1.00 (reference) |
| Hypertension – no treatment | 1.44 (1.38–1.50) | - | 1.13 (0.93–1.38) | 1.12 (1.06–1.19) | - | 1.06 (0.80–1.40) |
| Hypertension – received treatment | 1.58 (1.53–1.64) | - | 1.13 (0.93–1.37) | 1.01 (0.96–1.07) | - | 0.97 (0.73–1.28) |
| Diabetes treatment | ||||||
| No diabetes | 1.00 (reference) | - | 1.00 (reference) | 1.00 (reference) | - | 1.00 (reference) |
| Diabetes – no treatment | 1.46 (1.41–1.51) | - | 0.93 (0.76–1.13) | 1.03 (0.98–1.08) | - | 0.89 (0.67–1.18) |
| Diabetes – received treatment | 2.09 (2.00–2.18) | - | 1.20 (0.99–1.46) | 1.26 (1.18–1.35) | - | 0.96 (0.73–1.26) |
Model-1 was a crude model without adjusting for other factors. Model-2 adjusted for age, marital status, health insurance, tumor stage, size, grade, year of diagnosis, SEER registries, surgery, and comorbidity score. Model-3 adjusted for chemotherapy, radiation therapy, hormone therapy, antihypertensive therapy, and antidiabetic therapy, in addition to other factors in Model-2
Black women had a significantly higher unadjusted risk of all-cause mortality (1.46, 1.41–1.52) and still had a significantly higher risk (1.10, 1.06–1.15) after adjusting for sociodemographic factors, tumor characteristics, and health insurance status at the time of cancer diagnosis, but that became insignificant after adjusting for treatment factors (1.01, 0.97–1.06), whereas the adjusted risk of breast cancer-specific mortality remained significantly higher (1.08, 1.01–1.15) in Black women as compared to White women. Asian and other ethnic women had a significantly lower risk of both all-cause and breast cancer-specific mortality than White women. Those who received chemotherapy and radiation therapy had a significantly reduced risk of both all-cause and breast cancer-specific mortality than those who did not, after adjusting for other factors. As compared to patients with hormone receptor-negative breast cancer, those with hormone receptor-positive tumors who received hormone therapy had a significantly lower risk of both all-cause and breast cancer-specific mortality, but those with hormone receptor-positive tumors who did not receive hormone therapy as well as those with unknown hormone receptor status had a significantly higher risk of mortality. In women with breast cancer who had a history of hypertension or diabetes as comorbid conditions, the receipt of antihypertensive or antidiabetic treatment appeared to have no significant impact on the risk of mortality as compared to those without or with such comorbid conditions who did not receive medications, after adjusting for other factors. The survival curves by chemotherapy, radiation therapy, hormone therapy, antihypertensive therapy, and antidiabetic therapy were shown in Figs. 1 and 2. The results were consistent with what is presented in Table 5.
Fig. 1.
Kaplan–Meier survival curves for overall survival by chemotherapy, radiation therapy, hormone therapy, antihypertensive therapy, and antidiabetic therapy (including a to e, 5 curves)
Fig. 2.
Kaplan–Meier survival curves for breast cancer specified survival by chemotherapy, radiation therapy, hormone therapy, antihypertensive therapy, and antidiabetic therapy (including a to e, 5 curves)
Discussion
This study demonstrated substantial age and racial disparities in the prevalence of two common comorbid illnesses (i.e., hypertension and diabetes) and in the distribution of other comorbidity scores among patients with breast cancer, and large racial differences in the receipt of anticancer therapy, antihypertensive therapy, and antidiabetic treatment. Older women were more likely to receive hormone therapy and antihypertensive therapy but had a lower proportion of receiving chemotherapy, radiation therapy, and antidiabetic therapy regardless of health insurance status at the time of cancer diagnosis and tumor stage. The study also showed that anticancer therapies (chemotherapy, radiation therapy, and hormone therapy) were significantly associated with the decreased risk of mortality, while antihypertensive or antidiabetic therapies were not. Black women did not have a significantly higher risk of all-cause mortality but had a significantly higher risk of breast cancer-specific mortality as compared to White women after adjusting for treatment factors, whereas Asian and other ethnic women had a significantly lower risk of both all-cause and breast cancer-specific mortality.
Racial and ethnic disparities in access to and in the receipt of health care and medical services have been consistently documented for almost all medical conditions, including breast cancer care [1–10]. However, studies on racial disparities in cancer survival and mortality may be less consistent because disparities really depend on whether studies have controlled for other confounding factors that might have explained the differences among different race/ethnic populations [11–34]. For example, some studies showed that racial disparities in mortality persisted after adjusting for treatment delay, comorbidities, and other factors [12, 16, 29, 30], whereas other studies showed that racial disparities in all-cause mortality in older women aged 65 or older no longer existed after adjusting for tumor characteristics and socioeconomic factors [17, 28]. Our current study in a large recent cohort of older women with breast cancer in 2007–2015 also demonstrated similar findings, i.e., there was no significant disparity in the risk of all-cause mortality between Black and White women with breast cancer after adjusting for treatment factors, whereas there was still a significant difference in the risk of breast cancer-specific mortality between them and other ethnic women had significantly different risks of all-cause and breast cancer-specific mortality.
What is particularly unique in our study was that we examined racial disparities in the prevalence of hypertension and diabetes and also examined racial disparities in the receipt of antihypertensive and antidiabetic drug therapies in multiple ethnic women with breast cancer. Because Medicare Part-D comprehensive drug coverage was implemented since 2006, antihypertensive and antidiabetic medications can be well captured using the long lists of all currently available antihypertensive and antidiabetic drugs [39, 40]. Hypertension and diabetes as common comorbid conditions in women with breast cancer can be reliably identified from Medicare inpatient, outpatient, and physician claims. The overall prevalence of hypertension and diabetes are high in all ethnic women with breast cancer but are the highest in Black women. The receipt of antihypertensive and antidiabetic medications in Black women was higher than in other ethnic women. However, the receipt of antihypertensive and antidiabetic medication was not significantly associated with the risk of all-cause and breast cancer-specific mortality. Hence, racial/ethnic disparities in mortality might have been minimally affected by the differential receipt of these antihypertensive and antidiabetic treatments.
The causes of racial/ethnic disparities in cancer mortality and survival are multifactorial. Numerous studies have shown biological, genetic, and socioeconomic differences among the various ethnic population [11–34]. For example, African American women were reported to be more likely to have breast cancer with triple-negative status (estrogen receptor-negative, progesterone receptor-negative, and human epidermal growth factor receptor-2 negative), poorer tumor grade, and higher tumor stage [21, 23]. Some studies reported biological factors such as genetic factors and obesity and non-biologic factors such as unsafe neighborhoods, poverty, social stress, and toxic-waste dumping, which might have affected ethnic disparities in breast cancer survival outcomes [17–34]. In addition, socioeconomic status was a strong confounding factor in the association between race/ethnicity and survival, and poorer socioeconomic status was reported to be associated with poorer health outcomes and increased mortality. Other studies showed that there may be systematic and structural racism within the health care systems and among clinicians that may have played a role in ethnic disparities in poorer outcomes [41, 42]. These socioeconomic factors, health insurance, and receipt of effective medical care are modifiable factors. Therefore, efforts to provide equal opportunities for education, employment, adequate housing, health insurance, good neighborhoods, and standard of health care and medical services may have great clinical and public health implications in reducing or eliminating racial/ethnic disparities in health outcomes, survival, and mortality.
This study has some limitations to be kept in mind. First, information on early detection and mammography screening for early-stage breast cancer was not available for analysis. Therefore, their effects on racial disparities in mortality cannot be addressed. Second, there was a lack of information on the health care system, hospital, and physician characteristics; hence, potential racial discriminations related to these factors and their impacts on patient survival cannot be examined. Third, patients’ personal health knowledge, preference, and compliance to cancer therapies, which are essential for the success of defeating cancer, cannot be examined by race and ethnicity. Finally, this study only included women aged 65 and older who were Medicare beneficiaries. The findings may not be generalizable to younger patients.
In conclusion, there were substantial age and racial disparities in the prevalence of hypertension and diabetes in patients with breast cancer and the receipt of anticancer therapy, antihypertensive therapy, and antidiabetic treatment regardless of health insurance status at the time of cancer diagnosis and tumor stage. Black women did not have a significantly higher risk of all-cause mortality but had a significantly higher risk of breast cancer-specific mortality as compared to White women, whereas Asian and other ethnic women had a significantly lower risk of both all-cause and breast cancer-specific mortality. Further studies may be needed to assess how the receipt of cancer therapies can be improved among ethnic populations and to identify other factors that are barriers to health disparities in women with breast cancer.
Supplementary Material
Acknowledgements
We acknowledge the efforts of the NCI, CMS, IMS, and the SEER registries in the creation of this SEER-Medicare linked database. This study was supported by the NIH grant numbers R01AG058971 and R01AG067498. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Funding
This study was supported by the NIH grants (numbers R01AG058971 and R01AG067498).
Footnotes
Conflict of Interest The authors declare no competing interests.
Declarations
Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s40615-022-01235-4.
Ethics Approval This study used the existing and de-identified SEER-Medicare linked datasets. There is no patient contact and no health risk to the subjects under study. This study was approved by the Committee for Protection of Human Subjects at the University of Texas Health Science Center in Houston.
Data Availability
The National Cancer Institute’s SEER (Surveillance, Epidemiology, and End Results)-Medicare Data User Agreement (DUA) specifically requests that “You (the Investigators) will not permit others to use the data except for collaborators within your institution involved with the research as described in your proposal.” However, the SEER-Medicare linked data are available to researchers from the National Cancer Institute upon signing the DUA, having the study proposal approved, and pay the related costs. We plan to share the statistical models and statistical programs that we used to analyze these data upon request and to share study findings and related study resources. We also plan to make results and algorithms available for verification or replication by other researchers.
References
- 1.Institute of Medicine. Unequal treatment: confronting racial and ethnic disparities in health care Washington, DC: National Academy Press; 2002. [PMC free article] [PubMed] [Google Scholar]
- 2.Shavers VL, Brown ML. Racial and ethnic disparities in the receipt of cancer treatment. J Natl Cancer Inst. 2002;94:334–57. [DOI] [PubMed] [Google Scholar]
- 3.Mandelblatt JS, Kerner JF, Hadley J, Hwang YT, Eggert L, Johnson LE, et al. Variations in breast carcinoma treatment in older Medicare beneficiaries: is it Black or White? Cancer. 2002;95:1401–14. [DOI] [PubMed] [Google Scholar]
- 4.Du XL, Gor BJ. Racial disparities and trends in radiation therapy following breast conserving surgery for early-stage breast cancer in women from 1992 to 2002. Ethn Dis. 2007;17:122–8. [PMC free article] [PubMed] [Google Scholar]
- 5.Green AK, Aviki EM, Matsoukas K, Patil S, Korenstein D, Blinder V. Racial disparities in chemotherapy administration for early-stage breast cancer: a systematic review and meta-analysis. Breast Cancer Res Treat. 2018;172(2):247–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Roberts MC, Wheeler SB, Reeder-Hayes K. Racial/Ethnic and socioeconomic disparities in endocrine therapy adherence in breast cancer: a systematic review. Am J Public Health. 2015;105(Suppl 3 (Suppl 3)):e4–15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Farias AJ, Du XL. Ethnic differences in initiation and timing of adjuvant endocrine therapy among older women with hormone receptor-positive breast cancer enrolled in Medicare part D. Med Oncol. 2016;33(2):19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Farias AJ, Du XL. The association between out-of-pocket costs, race/ethnicity, and adjuvant endocrine therapy adherence among Medicare patients with breast cancer. J Clin Oncol. 2017;35(1):86–95. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Farias AJ, Du XL. Racial differences in adjuvant endocrine therapy use and discontinuation in association with mortality among Medicare breast cancer patients by receptor status. Cancer Epidemiol Biomarkers Prev. 2017;26(8):1266–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Heiney SP, Truman S, Babatunde OA, Felder TM, Eberth JM, Crouch E, et al. racial and geographic disparities in endocrine therapy adherence among younger breast cancer survivors. Am J Clin Oncol. 2020;43(7):504–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Tammemagi CM, Nerenz D, Neslund-Dudas C, Feldkamp C, Nathanson D. Comorbidity and survival disparities among Black and White patients with breast cancer. JAMA. 2005;294:1765–72. [DOI] [PubMed] [Google Scholar]
- 12.Hershman D, McBride R, Jacobson JS, et al. Racial disparities in treatment and survival among women with early-stage breast cancer. J Clin Oncol. 2005;23:6639–46. [DOI] [PubMed] [Google Scholar]
- 13.Field TS, Buist DS, Doubeni C, et al. Disparities and survival among breast cancer patients. J Natl Cancer Inst Monogr. 2005;35:88–95. [DOI] [PubMed] [Google Scholar]
- 14.Blackman DJ, Masi CM. Racial and ethnic disparities in breast cancer mortality: are we doing enough to address the root causes? J Clin Oncol. 2006;24:2170–8. [DOI] [PubMed] [Google Scholar]
- 15.Grann V, Troxel AB, Zojwalla N, Hershman D, Glied SA, Jacobson JS. Regional and racial disparities in breast cancer-specific mortality. Soc Sci Med. 2006;62:337–47. [DOI] [PubMed] [Google Scholar]
- 16.Komenaka IK, Martinez ME, Pennington RE Jr, Hsu CH, Clare SE, Thompson PA. Race and ethnicity and breast cancer outcomes in an underinsured population. J Natl Cancer Inst. 2010;102(15):1178–87. [DOI] [PubMed] [Google Scholar]
- 17.Du XL, Fang S, Meyer TE. Impact of treatment and socioeconomic status on racial disparities in survival among older women with breast cancer. Am J Clin Oncol. 2008;31(2):125–32. [DOI] [PubMed] [Google Scholar]
- 18.Warner ET, Tamimi RM, Hughes ME, Ottesen RA, Wong YN, Edge SB, et al. Racial and ethnic differences in breast cancer survival: mediating effect of tumor characteristics and sociodemographic and treatment factors. J Clin Oncol. 2015;33(20):2254–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Bandera EV, Maskarinec G, Romieu I, John EM. Racial and ethnic disparities in the impact of obesity on breast cancer risk and survival: a global perspective. Adv Nutr. 2015;6(6):803–19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Yedjou CG, Tchounwou PB, Payton M, Miele L, Fonseca DD, Lowe L, Alo RA. Assessing the racial and ethnic disparities in breast cancer mortality in the United States. Int J Environ Res Public Health. 2017;14(5):486. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Newman LA, Kaljee LM. Health Disparities and triple-negative breast cancer in African American Women: a review. JAMA Surg. 2017;152(5):485–93. [DOI] [PubMed] [Google Scholar]
- 22.DeSantis CE, Ma J, Goding Sauer A, Newman LA, Jemal A. Breast cancer statistics, 2017, racial disparity in mortality by state. CA Cancer J Clin. 2017;67(6):439–48. [DOI] [PubMed] [Google Scholar]
- 23.Newman LA. Breast cancer disparities: socioeconomic factors versus biology. Ann Surg Oncol. 2017;24(10):2869–75. [DOI] [PubMed] [Google Scholar]
- 24.Farias AJ, Wu WH, Du XL. Racial differences in long-term adjuvant endocrine therapy adherence and mortality among Medicaid-insured breast cancer patients in Texas: findings from TCR-Medicaid linked data. BMC Cancer. 2018;18:1214. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Silber JH, Rosenbaum PR, Ross RN, Reiter JG, Niknam BA, Hill AS, et al. Disparities in breast cancer survival by socioeconomic status despite Medicare and Medicaid insurance. Milbank Q. 2018;96(4):706–54. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Yedjou CG, Sims JN, Miele L, Noubissi F, Lowe L, Fonseca DD, et al. Health and racial disparity in breast cancer. Adv Exp Med Biol. 2019;1152:31–49. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Guan A, Lichtensztajn D, Oh D, Jain J, Tao L, Hiatt RA, Gomez SL, Fejerman L. Breast cancer in San Francisco: disentangling disparities at the neighborhood level. Cancer Epidemiol Biomarkers Prev. 2019;28(12):1968–76. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Ren JX, Gong Y, Ling H, Hu X, Shao ZM. Racial/ethnic differences in the outcomes of patients with metastatic breast cancer: contributions of demographic, socioeconomic, tumor and metastatic characteristics. Breast Cancer Res Treat. 2019;173(1):225–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Hoppe EJ, Hussain LR, Grannan KJ, Dunki-Jacobs EM, Lee DY, Wexelman BA. Racial disparities in breast cancer persist despite early detection: analysis of treatment of stage 1 breast cancer and effect of insurance status on disparities. Breast Cancer Res Treat. 2019;173(3):597–602. [DOI] [PubMed] [Google Scholar]
- 30.Mets EJ, Chouairi FK, Gabrick KS, Avraham T, Alperovich M. Persistent disparities in breast cancer surgical outcomes among Hispanic and African American patients. Eur J Surg Oncol. 2019;45(4):584–90. [DOI] [PubMed] [Google Scholar]
- 31.Pellom ST Jr, Arnold T, Williams M, Brown VL, Samuels AD. Examining breast cancer disparities in African Americans with suggestions for policy. Cancer Causes Control. 2020;31(9):795–800. [DOI] [PubMed] [Google Scholar]
- 32.Chapman-Davis E, Zhou ZN, Fields JC, Frey MK, Jordan B, Sapra KJ, et al. racial and ethnic disparities in genetic testing at a hereditary breast and ovarian cancer center. J Gen Intern Med. 2021;36(1):35–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Wang F, Zheng W, Bailey CE, Mayer IA, Pietenpol JA, Shu XO. Racial/ethnic disparities in all-cause mortality among patients diagnosed with triple-negative breast cancer. Cancer Res. 2021;81(4):1163–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Poulson MR, Beaulieu-Jones BR, Kenzik KM, Dechert TA, Ko NY, Sachs TE, Cassidy MR. Residential racial segregation and disparities in breast cancer presentation, treatment, and survival. Ann Surg. 2021;273(1):3–9. [DOI] [PubMed] [Google Scholar]
- 35.National Cancer Institute. SEER-Medicare: brief description of the SEER-Medicare Database. https://healthcaredelivery.cancer.gov/seermedicare/overview/, accessed on 18 July 2021. [Google Scholar]
- 36.Warren JL, Klabunde CN, Schrag D, Bach PB, Riley GF. Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population. Med Care. 2002;40(8 Suppl):IV3–IV18. [DOI] [PubMed] [Google Scholar]
- 37.Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–83. [DOI] [PubMed] [Google Scholar]
- 38.Klabunde CN, Potosky AL, Legler JM, Warren JL. Development of a comorbidity index using physician claims data. J Clin Epidemiol. 2000;53:1258–67. [DOI] [PubMed] [Google Scholar]
- 39.Healthline: a list of blood pressure medications. https://www.healthline.com/health/high-blood-pressure-hypertension-medication#overview, accessed 2 Apr 2021.
- 40.Healthline: a complete list of diabetes medications https://www.healthline.com/health/diabetes/medications-list, accessed 2 Apr 2021.
- 41.Hall WJ, Chapman MV, Lee KM, Merino YM, Thomas TW, Payne BK, et al. implicit racial/ethnic bias among health care professionals and its influence on health care outcomes: a systematic review. Am J Public Health. 2015;105(12):e60–76. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Bailey ZD, Krieger N, Agénor M, Graves J, Linos N, Bassett MT. Structural racism and health inequities in the USA: evidence and interventions. Lancet. 2017;389(10077):1453–63. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The National Cancer Institute’s SEER (Surveillance, Epidemiology, and End Results)-Medicare Data User Agreement (DUA) specifically requests that “You (the Investigators) will not permit others to use the data except for collaborators within your institution involved with the research as described in your proposal.” However, the SEER-Medicare linked data are available to researchers from the National Cancer Institute upon signing the DUA, having the study proposal approved, and pay the related costs. We plan to share the statistical models and statistical programs that we used to analyze these data upon request and to share study findings and related study resources. We also plan to make results and algorithms available for verification or replication by other researchers.