Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. In the elderly (≥70 years old) primary operable (T1-3N0-1M0) TNBC, individualized treatment modalities for this population are pivotal and important, but limited studies are explored.
The clinicopathological features of elderly primary operable TNBC patients were retrospectively selected from the Surveillance, Epidemiology, and End Results (SEER) database between January 2010 and December 2015. Kaplan–Meier curves were used to show the survival patterns in the different subgroups. Multivariate Cox analysis was used to identify independent risk factors in the 3-, 5-, and 7- year overall survival (OS) and cancer-specific survival (CSS) in this subpopulation. The predictive model was further developed and validated for clinical use.
Between 2010 and 2015 years, a total of 4,761 elderly primary operable TNBC patients were enrolled for the study, with a mean age of 76 years and a median follow-up of 56 months. The multivariate Cox analysis showed that age (increased per year: hazard ratio (HR) = 1.05), race (Asian/Pacific Islander and American Indian/Alaska Native, HR = 0.73), differentiation grade (grade II: HR = 2.01; grade III/IV: HR = 2.67), larger tumor size (T1c: HR = 1.83; T2: HR = 2.78; T3: HR = 4.93), positive N stage (N1mi: HR = 1.60; N1: HR = 1.54), receiving radiation therapy (HR = 0.66), and receiving adjuvant chemotherapy (HR = 0.61) were the independent prognostic factors for OS, and a similar prognostic pattern was also determined in CSS. Besides, two nomograms for predicting the 3-, 5-, and 7-year OS and CSS in this population were developed with a favorable concordance index of 0.716 and 0.746, respectively.
The results highlight that both radiation and adjuvant chemotherapy are significantly associated with favorable long-term OS and CSS probability in elderly primary operable TNBC patients. Based on the determined independent prognostic factors, the novel nomograms could assist the oncologists to make individualized clinical decisions for the subpopulation at different risks.