Breast cancer survival by molecular subtype: a population-based analysis of cancer registry data

BACKGROUND: The relation between breast cancer molecular subtype and survival has been studied in several jurisdictions, but limited information is available for Ontario. The aim of this study was to determine breast cancer survival by molecular subtype and to assess the effect on survival of selected demographic and tumour-based characteristics. METHODS: We extracted 29 833 breast cancer cases (in 26 538 girls and women aged ≥ 15 yr) diagnosed between 2010 and 2012 from the Ontario Cancer Registry. Cancers were categorized into 4 molecular subtypes: 1) luminal A (estrogen-receptor-positive and/or progesterone-receptor-positive ER+ and/or PR+ and negative for human epidermal growth factor receptor 2 HER2-), 2) luminal B (ER+ and/or PR+/HER2+), 3) HER2-enriched (ER- and PR-/HER2+) and 4) triple-negative (ER- and PR-/HER2-). We estimated associations with predictor variables (age, stage at diagnosis, histologic type, comorbidity and place of residence urban or rural) using a multivariate Cox proportional hazards model. Likelihood ratio testing was used to evaluate differences in risk of death. RESULTS: Luminal A was the most commonly diagnosed subtype (59.0%) and had the greatest survival, whereas triple-negative had the poorest survival. For all subtypes, a dose-response effect was observed between the hazard of death and age and stage at diagnosis, with the greatest effect found for the HER2-enriched subtype (age: hazard ratio HR 7.87 95% confidence interval (CI) 3.68-11.81; stage at diagnosis: HR 37.71 95% CI 34.64-41.27). Moderate comorbidity (Charlson Comorbidity Index score 1 or 2) was associated with increased risk of death for triple-negative cancers (HR 2.42 95% CI 1.36-4.31), and severe comorbidity (Charlson Comorbidity Index score ≥ 3) increased the risk for all molecular subtypes. INTERPRETATION: The results indicate the importance of including molecular subtype, along with age, stage at diagnosis and comorbidity, in assessing breast cancer survival. They highlight the need to address outcomes related to hormone-receptor-negative cancers, for which survival lags behind that for hormone-receptor-positive cancers.