Development and validation of a nomogram for predicting survival of advanced breast cancer patients in China.

Abstract

e13064 Background: The prognosis of patients with advanced breast cancer (ABC) varied according to different prognostic factors. This study aimed to establish a nomogram to predict the overall survival (OS) of ABC patients in China. Methods: Data from the China National Cancer Center database that recorded 4039 patients diagnosed with breast cancer between 1987 and 2019 were extracted and a total of 2263 ABC patients with complete relevant information were included in this study, which were further randomized 3:1 and divided into training ( n = 1706) and validation ( n = 557) cohorts. The nomogram was built based on independent predictors identified by univariate and multivariate analyses. Harrell′s concordance index (C-index) and calibration plots were used to assessed the discriminatory and predictive capacities of the nomogram. Results: With a median OS of 45.4 months, the 2-year and 3-year OS rates of ABC patients were 75.2% and 60.2%, respectively. Univariate and multivariate analyses found that age, Eastern Cooperative Oncology Group (ECOG) performance status, T-stage, N-stage, tumor subtype, the presence of distant lymph node (DLN)/liver/brain metastasis, local therapy, efficacy of first-line therapy and metastatic-free interval (MFI) were significantly associated with OS (all P < 0.05). These variables were incorporated into a nomogram to predict the 2-year and 3-year OS of ABC patients. The C-indexes of the nomogram were 0.700 (95% confidence interval [CI]: 0.683-0.717) and 0.686 (95% CI: 0.652-0.719) for the training and the validation sets, respectively. The calibration curves revealed satisfactory agreement between actual survival and nomogram prediction in both the internal and external validations. The nomogram was able to stratify patients into different risk groups. Conclusions: We developed and validated a nomogram that might serve as an efficient tool to provide individual prediction for ABC patients and guide the physicians to make personalized treatment decisions for individual ABC patients.