A Decision-Analytical Perspective on Incorporating Multiple Outcomes in the Production of Clinical Prediction Models: defining a taxonomy of risk estimands

Background
Clinical prediction models (CPMs) estimate an individual’s risk of current or future outcome events, using information available about the individual at the time of prediction. While most CPMs are developed to predict a single outcome event, many clinical decisions require considering risks of multiple outcome events. For example, decision-making for anticoagulation therapy involves assessing an individual’s risks of both blood clot and bleeding, while decision-making around interventions for multimorbidity prevention requires understanding of the risks of developing multiple long-term conditions. However, determining when and how to incorporate multiple outcomes into CPMs remains challenging. This article aims to raise awareness of multiple outcome prediction, and present clinical examples where such prediction is essential to help inform individual decision-making.