Development and External Validation of Prediction Models for 10-Year Survival of Invasive Breast Cancer. Comparison with PREDICT and CancerMath.

ABSTRACT: Purpose: To compare PREDICT and CancerMath, two widely used prognostic models for invasive breast cancer, taking into account their clinical utility. Furthermore, it is unclear whether these models could be improved.Experimental Design: A dataset of 5,729 women was used for model development. A Bayesian variable selection algorithm was implemented to stochastically search for important interaction terms among the predictors. The derived models were then compared in three independent datasets (n = 5,534). We examined calibration, discrimination, and performed decision curve analysis.Results: CancerMath demonstrated worse calibration performance compared with PREDICT in estrogen receptor (ER)-positive and ER-negative tumors. The decline in discrimination performan

SUBMITTER: Karapanagiotis S 

PROVIDER: S-EPMC5935226 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature