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

J Natl Cancer Inst. 2024 Jun 7;116(6):902-910. doi: 10.1093/jnci/djae019.

Abstract

Background: Inequities in guideline-concordant treatment receipt contribute to worse survival in Black patients with breast cancer. 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 breast cancer inequities in North Carolina.

Methods: Using registry-linked multipayer claims data, we calculated inequities between Black and White patients receiving endocrine therapy (n = 12 033) and chemotherapy (n = 1819). We then built cohort-stratified (endocrine therapy and chemotherapy) and race-stratified Markov models to simulate the potential increase in the proportion of patients receiving endocrine therapy or chemotherapy and subsequent improvements in breast cancer outcomes if inequity-reducing intervention were implemented statewide. We report uncertainty bounds representing 95% of simulation results.

Results: In total, 75.6% and 72.1% of Black patients received endocrine therapy and chemotherapy, respectively, over the 2006-2015 and 2004-2015 periods (vs 79.3% and 78.9% of White patients, respectively). Inequity-reduction interventions could increase endocrine therapy and chemotherapy receipt among Black patients to 89.9% (85.3%, 94.6%) and 85.7% (80.7%, 90.9%). Such interventions could also decrease 5-year and 10-year breast cancer 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 endocrine therapy 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 chemotherapy cohorts.

Conclusions: Inequity-focused interventions could improve cancer outcomes for Black patients, but they would not fully close the racial breast cancer mortality gap. Addressing other inequities along the cancer continuum (eg, screening, pre- and postdiagnosis risk factors) is required to achieve full equity in breast cancer outcomes.

MeSH terms

  • Adult
  • Aged
  • Black or African American* / statistics & numerical data
  • Breast Neoplasms* / ethnology
  • Breast Neoplasms* / mortality
  • Breast Neoplasms* / therapy
  • Female
  • Healthcare Disparities* / ethnology
  • Healthcare Disparities* / statistics & numerical data
  • Humans
  • Middle Aged
  • North Carolina / epidemiology
  • Registries / statistics & numerical data
  • White People / statistics & numerical data
  • White* / statistics & numerical data