Prognostic Model for De Novo and Recurrent Metastatic Breast Cancer.

Purpose: Metastatic breast cancer (MBC) has a heterogeneous clinical course. We sought to develop a prognostic model for overall survival (OS) that incorporated contemporary tumor and clinical factors for estimating individual prognosis.
Methods: We identified patients with MBC from our institution diagnosed between 1998 and 2017. We developed OS prognostic models by Cox regression using demographic, tumor, and treatment variables. We assessed model predictive accuracy and estimated annual OS probabilities. We evaluated model discrimination and prediction calibration using an external validation data set from the National Comprehensive Cancer Network.
Results: We identified 10,655 patients. A model using age at diagnosis, race or ethnicity, hormone receptor and human epidermal growth factor receptor 2 subtype, de novo versus recurrent MBC categorized by metastasis-free interval, Karnofsky performance status, organ involvement, frontline biotherapy, frontline hormone therapy, and the interaction between variables significantly improved predictive accuracy (C-index, 0.731; 95% CI, 0.724 to 0.739) compared with a model with only hormone receptor and human epidermal growth factor receptor 2 status (C-index, 0.617; 95% CI, 0.609 to 0.626). The extended Cox regression model consisting of six independent models, for < 3, 3-14, 14-20, 20-33, 33-61, and ≥ 61 months, estimated up to 5 years of annual OS probabilities. The selected multifactor model had good discriminative ability but suboptimal calibration in the group of 2,334 National Comprehensive Cancer Network patients. A recalibration model that replaced the baseline survival function with the average of those from the training and validation data improved predictions across both data sets.
Conclusion: We have generated and validated a robust prognostic OS model for MBC. This model can be used in clinical decision making and stratification in clinical trials.
Competing Interests: Carlos H. BarcenasResearch Funding: Puma Biotechnology Rashmi K. MurthyHonoraria: Puma Biotechnology, Genentech, Seattle Genetics, Novartis, AstraZenecaConsulting or Advisory Role: Genentech/Roche, Puma Biotechnology, Seattle Genetics, AstraZeneca, NovartisResearch Funding: Genentech/Roche, Daiichi Sankyo, Pfizer, EMD Serono, Seattle Genetics, AstraZenecaTravel, Accommodations, Expenses: Seattle Genetics, Genentech Robert W. CarlsonEmployment: Flatiron Health (I)Patents, Royalties, Other Intellectual Property: Patents relating to inventions as employee of NCCNOther Relationship: National Comprehensive Cancer Network Debu TripathyConsulting or Advisory Role: Novartis, Pfizer, GlaxoSmithKline, Genomic Health, AstraZeneca, OncoPepResearch Funding: Novartis, PolyphorTravel, Accommodations, Expenses: Novartis, AstraZeneca Gabriel N. HortobagyiConsulting or Advisory Role: NovartisResearch Funding: NovartisTravel, Accommodations, Expenses: NovartisNo other potential conflicts of interest were reported.