Prognostic nomograms for breast cancer with lung metastasis: a SEER-based population study

Abstract

Abstract Background: Lung metastasis is a significant adverse predictor of prognosis in patients with breast cancer. Accurate estimates for the prognosis of patients with lung metastasis and population-based validation for the models are lacking. In the present study, we aimed to establish nomograms to identify prognostic factors with lung metastases and evaluate individualized survival in patients with lung metastasis based on SEER (Surveillance, Epidemiology, and End Results) database. Methods: We selected 1197 patients diagnosed with breast cancer with lung metastasis (BCLM) from the SEER database and randomly assigned them to the testing group (n=837) and the testing group (n=360). Based on univariate and multivariate Cox regression analysis, we evaluate the effects of multiple variables on survival and prognosis in the training group and constructed a nomogram to predict the 1-, 2-, 3-year survival probability of patients. The nomogram is verified internally and externally by Concordance index (C-index), Net Reclassification (NRI), Integrated Discrimination Improvement (IDI), Decision Curve Analysis (DCA), and calibration plots. Results: According to the results of multi-factor COX regression analysis, age, histopathology, grade, marital status, bone metastasis, brain metastasis, liver metastasis, HER2, ER, PR, surgery, neoadjuvant therapy, and chemotherapy are considered independent prognostic factors for patients with BCLM. The C-index in the training group is 0.719 and the test group is 0.695, respectively. The AUC values of the 1-, 2-, 3-years prognostic nomograms in the training group were 0.798, 0.79 and 0.793, and the corresponding AUC values in testing group were 0.765, 0.761 and 0.762. The calculation results of IDI and NRI are shown, the nomogram significantly improved the risk reclassification for 1-, 2-, and 3-year overall mortality prediction compared with the AJCC 7th staging system. According to the calibration plot, nomogram shows good consistency between predicted and actual OS values for the patients with BCLM. DCA showed that nomogram had better net benefits at different threshold probabilities at different time points compared with the AJCC 7th staging system. Conclusions: Nomograms that predicted 1-, 2-, and 3-year OS for patients with BCLM were successfully constructed and validated to help physicians in evaluating the high risk of mortality in breast cancer patients.