Background Metaplastic breast cancer (MBC) is a rare type of breast cancer with an increasing incidence, we aim to develop clinical nomograms to predict the overall survival and cancer-specific survival for patients with MBC.MethodsPatients data were collected from the SEER database between 1973 and 2015. All included patients were randomly assigned into the training and validation sets. Univariate and multivariate Cox analysis were performed to identify independent prognostic factors of MBC. These essential prognostic variables were combined to construct nomogram models to predict overall survival (OS) and cancer-specific survival (CSS) in patients with MBC. Model performance was evaluated by concordance index (C-index) and calibration plots.ResultsA total of 1129 patients were collected and divided into the training (753) and validation (376) groups. The multivariate Cox model identified age, stage_ajcc, T stage, chemotherapy and radiotherapy as independent covariates associated with OS, while age, race, stage_ajcc, T stage, and radiotherapy were independent prognostic factors of CSS. The nomogram constructed based on these covariates demonstrated excellent accuracy in estimating 3-, and 5-year OS and CSS, with a C-index of 0.744 (95% CI, 0.701-0.787) for OS and 0.746 (95% CI, 0.695-0.797) for CSS in the training cohort. In the validation cohort, the nomogram-predicted C-index was in OS and 0.818 for OS (95% CI, 0.775-0.861) and 0.800 (95% CI, 0.747-0.853) for CSS. All calibration curves exhibited good consistency between predicted and actual survival.ConclusionsThese nomogram models established in this study can help to enhance the accuracy of prognostic prediction, which may thereby improve individualized assessment of survival risks and facilitate to provide constructive therapeutic suggestions.