Uncertainty of risk estimates from clinical prediction models: rationale, challenges, and approaches.
Where this comes from
- Record sourced from PubMed, PMID 39947680.
- Also identified by DOI 10.1136/bmj-2024-080749 and PMC identifier 12128882.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Clinical prediction models estimate an individual’s risk (probability) of a health related outcome to help guide patient counselling and clinical decision making. Most models provide a single point estimate of risk but without the associated uncertainty. Riley and colleagues argue that this needs to change, as understanding uncertainty of risk estimates helps to inform critical evaluation of a model and may impact shared decision making. Examples are provided to illustrate uncertainty in risk estimates, and key methods to quantify and present uncertainty are discussed.