Disparities in Breast Cancer Survival by Socioeconomic Status Despite Medicare and Medicaid Insurance

Abstract

Policy Points Patients with low socioeconomic status (SES) experience poorer survival rates after diagnosis of breast cancer, even when enrolled in Medicare and Medicaid. Most of the difference in survival is due to more advanced cancer on presentation and the general poor health of lower SES patients, while only a very small fraction of the SES disparity is due to differences in cancer treatment. Even when comparing only low- versus not-low-SES whites (without confounding by race) the survival disparity between disparate white SES populations is very large and is associated with lower use of preventive care, despite having insurance.

Context: Disparities in breast cancer survival by socioeconomic status (SES) exist despite the "safety net" programs Medicare and Medicaid. What is less clear is the extent to which SES disparities affect various racial and ethnic groups and whether causes differ across populations.

Methods: We conducted a tapered matching study comparing 1,890 low-SES (LSES) non-Hispanic white, 1,824 black, and 723 Hispanic white women to 60,307 not-low-SES (NLSES) non-Hispanic white women, all in Medicare and diagnosed with invasive breast cancer between 1992 and 2010 in 17 US Surveillance, Epidemiology, and End Results (SEER) regions. LSES Medicare patients were Medicaid dual-eligible and resided in neighborhoods with both high poverty and low education. NLSES Medicare patients had none of these factors.

Measurements: 5-year and median survival.

Findings: LSES non-Hispanic white patients were diagnosed with more stage IV disease (6.6% vs 3.6%; p < 0.0001), larger tumors (24.6 mm vs 20.2 mm; p < 0.0001), and more chronic diseases such as diabetes (37.8% vs 19.0%; p < 0.0001) than NLSES non-Hispanic white patients. Disparity in 5-year survival (NLSES - LSES) was 13.7% (p < 0.0001) when matched for age, year, and SEER site (a 42-month difference in median survival). Additionally, matching 55 presentation factors, including stage, reduced the disparity to 4.9% (p = 0.0012), but further matching on treatments yielded little further change in disparity: 4.6% (p = 0.0014). Survival disparities among LSES blacks and Hispanics, also versus NLSES whites, were significantly associated with presentation factors, though black patients also displayed disparities related to initial treatment. Before being diagnosed, all LSES populations used significantly less preventive care services than matched NLSES controls.

Conclusions: In Medicare, SES disparities in breast cancer survival were large (even among non-Hispanic whites) and predominantly related to differences of presentation characteristics at diagnosis rather than differences in treatment. Preventive care was less frequent in LSES patients, which may help explain disparities at presentation.

Keywords: Medicare; breast cancer; disparities; socioeconomic status.

Figure 1

Conceptual Model of Tapered Matching Analyses Hypothetical Kaplan‐Meier Curves of Breast Cancer Survival for LSES Focal Patients (bottom) and Their 3 Matched NLSES Control Groups: (1) NLSES controls matched only on demographics (age, year of diagnosis, and SEER site) (top); (2) NLSES controls matched on both presentation factors and demographics (eg, tumor stage, size, pathology, patient comorbidities like diabetes and heart failure as well as the demographic variables); and finally (3) NLSES controls matched on treatment variables (eg, surgery, radiation, and chemotherapy) and both presentation factors and demographic variables. Note the size of the total disparity at a specified follow‐up time is D_TOT; the disparity associated with differences in how patients present on admission is the D_PRES, which is the difference in survival between the control group that is matched on demographics and the control group that is matched on both demographics and presentation factors. The disparity D_TX is the difference in survival between the control group that is matched on presentation and demographics factors and the control group that is matched on treatment, presentation, and demographics. If there is any disparity noted after the treatment match, we refer to that as the residual disparity (D_RES).

Figure 2

Kaplan‐Meier Curve for Breast Cancer Survival for LSES Non‐Hispanic Whites and 3 Matched NLSES Non‐Hispanic White (NHW) Populations Diagnosed Between 1992 and 2010

Figure 3

Kaplan‐Meier Curve for Breast Cancer Survival for LSES Blacks and 3 Matched NLSES Non‐Hispanic White (NHW) Populations Diagnosed Between 1992 and 2010

Figure 4

Kaplan‐Meier Curve for Breast Cancer Survival for LSES Hispanics and 3 Matched NLSES Non‐Hispanic White (NHW) Populations Diagnosed Between 1992 and 2010