Abstract
Prediction models are combinations of predictors to assess the risks of specific endpoints such as the presence or prognosis of a disease. Many novel predictors have been developed, modelling techniques have been evolving, and prediction models are currently abundant in the medical literature, especially in cardiovascular medicine, but evidence is still lacking regarding how to use them. Recent methodological advances in systematic reviews and meta-analysis have enabled systematic evaluation of prediction model studies and quantitative analysis to identify determinants of model performance. Knowing what is critical to model performance, under what circumstances model performance remains adequate, and when a model might require further adjustment and improvement will facilitate effective utilization of prediction models and will enhance diagnostic and prognostic accuracy in clinical practice. In this review article, we provide a current methodological overview of the attempts to implement evidence-based utilization of prognostic prediction models for all potential model users, including patients and their families, health-care providers, administrators, researchers, guideline developers and policy makers.