Simulating the population impact of interventions to reduce racial gaps in breast cancer treatment

Abstract

Background Inequities in guideline-concordant treatment receipt contribute to worse survival in Black breast cancer (BCa) patients. Inequity-reduction interventions (eg, navigation, bias training, tracking dashboards) can close such treatment gaps. We simulated the population-level impact of statewide implementation of inequity-reduction interventions on racial BCa inequities in North Carolina. Methods Using registry-linked multi-payer claims data, we calculated Black/White inequities in endocrine (ET; n = 12,033) and chemotherapy (CTx; n = 1,819) receipt. We then built cohort- (ET and CTx), and race-stratified Markov models to simulate the potential increase in the proportion of patients receiving ET or CTx and subsequent improvements in BCa outcomes if inequity-reducing intervention were implemented statewide. We report uncertainty bounds representing 95% of simulation results. Results 75.6% and 72.1% of Black patients received ET and CTx over the 2006-2015 and 2004-2015 periods (vs 79.3 and 78.9% of White patients, respectively). Inequity-reduction interventions could increase ET and CTx receipt among Black patients to 89.9% (85.3, 94.6%) and 85.7% (80.7, 90.9%). Such interventions could also decrease 5-and 10-year BCa mortality gaps from 3.4 to 3.2 (3.0, 3.3) and from 6.7 to 6.1 (5.9, 6.4) percentage points in the ET cohorts and from 8.6 to 8.1 (7.7, 8.4) and from 8.2 to 7.8 (7.3, 8.1) percentage points in the CTx cohorts. Conclusions Inequity-focused interventions could improve cancer outcomes for Black patients. However, they would not fully close the racial BCa mortality gap. Addressing other inequities along cancer continuum (eg, screening, pre-and post-diagnosis risk factors) is required to achieve full equity in BCa outcomes.