Twelve practical recommendations for developing and applying clinical predictive models

Abstract

<p>Prediction models play a pivotal role in medical practice. To ensure their clinical applicability, it is essential to guarantee the quality of predictive models at multiple stages. In this article, we propose twelve recommendations for the development and clinical implementation of prediction models. These include identifying clinical needs, selecting appropriate predictors, performing predictor transformations and binning, specifying suitable models, assessing model performance, evaluating reproducibility and transportability, updating models, conducting impact evaluations, and promoting model adoption. These recommendations are grounded in a comprehensive synthesis of insights from existing literature and our extensive clinical and statistical experience in the development and practical application of prediction models.</p>