Establish a Prediction Model for the Recurrence Time of Hormone Receptor Positive /human Epidermal Growth Factor Receptor 2-negative Breast Cancer

Abstract ObjectivesThis study aimed to develop a model to predict recurrence time of hormone receptor-positive (HR+) /human epidermal growth factor receptor 2 negative (HER2-) breast cancer patients. MethodsWe included HR+ HER2- metastatic breast cancer (MBC) female patients who arrived at the Department of Breast Oncology in Peking University Cancer Hospital. Data were collected through consulting medical records. Patients were divided into early recurrence group and late recurrence group according to disease-free survival (DFS). Predictors of recurrence time were identified and a nomogram was developed and validated using concordance index (C-index), AUC (area under the curve), and calibration plots. ResultsA total of 639 patients coming to the hospital between April 2007 and October 2019 were included. Median DFS was 50.0 months. 382 patients (59.8%) were presented with early recurrence (DFS ≤5 years), and 257 patients (40.2%) were presented with late recurrence (DFS >5 years). A nomogram based on potentially associated clinicopathological factors was developed and validation results showed the nomogram was well-calibrated to predict recurrence time (AUC=0.703, C-index=0.697). ConclusionsWe have established a well-calibrated nomogram through 639 patients. HR+/HER2- BC patients with premenopausal status at initial diagnosis, less positive lymph nodes, lower level of Ki-67 were more common in late recurrence. The nomogram can predict the risk of late recurrence. Prospectively designed studies are needed to further validate our model.