Risk Prediction in Cardio-Oncology: Conceptual and Methodological Considerations

Abstract

Risk prediction models can guide prevention, monitoring, and treatment decisions in cardio-oncology, but their development requires careful attention to methodological challenges unique to cardiovascular disease arising in the context of cancer. In this state-of-the-art review, the authors use case scenarios to illustrate how prediction objectives, index dates, and time horizons must align with specific clinical decisions across the cancer trajectory. They summarize key considerations for data source selection, population definition, sample size, and variable selection and discuss challenges in incorporating treatment data, including immortal time bias and confounding by indication. The auth..