Measurement of Treatment Adequacy Influences Racial Disparities Estimates in Endometrial Cancer Care

Abstract Background: Guideline-concordant treatment (GCT) is a key indicator of cancer care quality, yet most studies rely on cancer registry data, which incompletely capture treatment adequacy and vary in population composition. As a result, estimates of racial and ethnic disparities in GCT may differ depending on treatment measurement and populations represented in the data. Methods: We conducted analyses using Surveillance, Epidemiology, and End Results (SEER)-17, the National Cancer Database (NCDB), and SEER-Medicare to evaluate how treatment measurement and population composition influence disparities in guideline-concordant endometrial cancer treatment. GCT was defined according to National Comprehensive Cancer Network recommendations. Primary analyses used adequacy-based definitions incorporating treatment receipt, timing, amount, and duration, when available, while sensitivity analyses used receipt-based definitions based only on documented receipt. Logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs) for associations between race/ethnicity and GCT within each data source. Additional sensitivity analyses evaluated influences of differences in underlying study populations. Results: Using adequacy-based definitions of GCT, Black patients had lower GCT odds than White patients (SEER OR=0.84, 95% CI=0.79-0.90; NCDB OR=0.75, 95% CI=0.73-0.77; SEER-Medicare OR=0.73, 95% CI=0.62-0.85). Within both NCDB and SEER-Medicare, adequacy-based definitions of GCT yielded larger racial and ethnic disparities than receipt-based definitions. Conclusions: The estimated magnitude of racial disparities in guideline-concordant endometrial cancer treatment are sensitive to treatment measurement and patient selection; sources capturing treatment adequacy show larger disparities. Impact: Measuring treatment adequacy provides a more comprehensive assessment of inequities in endometrial cancer care and may improve cancer disparities research, quality measurement, and policy.