Prognostic nomogram for patients with non-metastatic HER2 positive breast cancer in a prospective cohort.

Abstract

A nomogram is a reliable tool to generate individualized risk prediction by combining prognostic factors. We aimed to construct a nomogram for predicting the survival in patients with non-metastatic human epidermal growth factor receptor 2 (HER2) positive breast cancer in a prospective cohort. We analyzed 1304 consecutive patients who were diagnosed with non-metastatic HER2 positive breast cancer between January 2008 and December 2016 in our institution. Independent prognostic factors were identified to build a nomogram using the COX proportional hazard regression model. The prediction of the nomogram was evaluated by concordance index (C-index), calibration and subgroup analysis. External validation was performed in a cohort of 6379 patients from the Surveillance, Epidemiology, and End Results (SEER) database. Through the COX proportional hazard regression model, five independent prognostic factors were identified. The nomogram predicting overall survival achieved a C-index of 0.78 in the training cohort and 0.74 in the SEER cohort. The calibration plot displayed favorable accordance between the nomogram prediction and the actual observation for 3-year overall survival in both cohorts. The quartiles of the nomogram score classified patients into subgroups with distinct overall survival. We developed and validated a novel nomogram for predicting overall survival in patients with non-metastatic HER2 positive breast cancer, which presented a favorable discrimination ability. This model may assist clinical decision making and patient-clinician communication in clinical practice.