Impact of patient demographics, tumor characteristics, and treatment type on treatment delay throughout breast cancer care at a diverse academic medical center.

Abstract

Purpose and objectiveThe aim of this study was to examine the impact of patient demographics, tumor characteristics, and treatment type on time to treatment (TTT) in patients with breast cancer treated at a safety net medical center with a diverse patient population.Patients and methodsA total of 1,130 patients were diagnosed and treated for breast cancer between 2004 and 2014 at our institution. We retrospectively collected data on patient age at diagnosis, race/ethnicity, primary language spoken, marital status, insurance coverage, American Joint Committee on Cancer (AJCC) stage, hormone receptor status, and treatment dates. TTT was determined from the date of breast cancer biopsy to treatment start date. Nonparametric Mann–Whitney U-test (or Kruskal–Wallis test when appropriate) and multivariable quantile regression models were employed to assess for significant differences in TTT associated with each factor.ResultsLonger median TTT was noted for Black (P=0.002) and single (P=0.002) patients. AJCC stage IV patients had shorter TTT (27.5 days) compared to earlier AJCC patients (36, 35, 37, 37 days for stage 0, I, II, III, respectively), P=0.028. Age, primary language spoken, insurance coverage, and hormone receptor status had no significant impact on TTT. On multivariate analysis, race/ethnicity remained the only significant factor with Black reporting longer TTT, P=0.025. However, race was not a significant factor for time from first to second treatment. More Black patients were noted to be single (P<0.0001) and received chemotherapy as first treatment (P=0.008) compared to White, Hispanic, or other race/ethnicity patients.ConclusionIn this retrospective analysis, Black patients had longer TTT, were more likely to receive chemotherapy as first treatment, and have a single marital status. These patient factors will help identify vulnerable patients and guide further research to understand the barriers to care and the impact of treatment delays on outcomes.