Characteristics of recurrence, predictors for relapse and prognosis of rapid relapse triple-negative breast cancer - Cai, Shuang-Long; Liu, Jing-Jing; Liu, Ying-Xue; Yu, Shao-Hong; Liu, Xu; Lin, Xiu-Quan; Chen, Hong-Dan; Fang, Xuan; Ma, Tao; Li, Ya-Qing; Li, Ying; Li, Chun-Yan; et al. (Frontiers in Oncology, 2023)
Background: The triple-negative breast cancer(TNBC) patients who recurred at different times are associated with distinct biological characteristics and prognoses. The research on rapid-relapse TNBC (RR-TNBC) is sparse. In this study, we aimed to describe characteristics of recurrence, predictors for relapse, and prognosis in rrTNBC patients. Methods Clinicopathological data of 1584 TNBC patients from 2014 to 2016 were retrospectively reviewed. Characteristics of recurrence were compared between patients with RR-TNBC and slow relapse TNBC(SR-TNBC). All TNBC patients were randomly divided into a training set and a validation set to find predictors for rapid relapse. The multivariate logistic regression model was used to analyze the data of the training set. C-index and brier score analysis for predicting rapid relapse in the validation set was used to evaluate the discrimination and accuracy of the multivariate logistic model. Prognostic measurements were analyzed in all TNBC patients. Results Compared with SR-TNBC patients, RR-TNBC patients tended to have a higher T staging, N staging, TNM staging, and low expression of stromal tumor-infiltrating lymphocytes（sTILs）. The recurred characteristics were prone to appear as distant metastasis at the first relapse. The first metastatic site was apt to visceral metastasis and less likely to have chest wall or regional lymph node metastasis. Six predictors (postmenopausal status, metaplastic breast cancer,≥pT3 staging,≥pN1 staging,sTIL intermediate/high expression, and Her2 [1+])were used to construct the predictive model of rapid relapse in TNBC patients. The C-index and brier score in the validation set was 0.861 and 0.095, respectively. This suggested that the predictive model had high discrimination and accuracy. Prognostic data of all TNBC patients showed that RR-TNBC patients had the worst prognosis, followed by SR-TNBC patients. Conclusion RR-TNBC patients were associated with unique biological characteristics and worse outcomes compared to non-RR-TNBC patients.