Uncertainty of risk estimates from clinical prediction models: rationale, challenges, and approaches

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.

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Publication Details

Journal
BMJ
Published
2025-02-13
DOI
https://doi.org/10.1136/bmj-2024-080749
Citations
20
Primary Topic
Sepsis Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
27.08

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article

Uncertainty of risk estimates from clinical prediction models: rationale, challenges, and approaches

Joseph Edward Alderman, Joie Ensor, Matthew Sperrin, Rebecca Whittle et al.
20 citations
BMJ
Sepsis Diagnosis and Treatment
27.08
article

Uncertainty of risk estimates from clinical prediction models: rationale, challenges, and approaches

Joseph Edward Alderman, Joie Ensor, Matthew Sperrin, Rebecca Whittle, Krishnarajah Nirantharakumar, Glen Philip Martin, Richard D Riley, Xiaoxuan Liu, Frank E. Harrell, Kym I E Snell, Paula Dhiman, Professor Gary S. Collins, Andrew J. Westwood, Maarten van Smeden, Alastair Keith Denniston, Jean‐Baptiste Cazier, Laura Kirton, Lucinda Archer, Karel G. M. Moons, Jay Manson-Whitton
article en
20 citations

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.

BMJVol. 388
Utrecht University (NL), Vanderbilt University (US), University of Cambridge (GB), Manchester Academic Health Science Centre (GB), The Francis Crick Institute (GB), Nuffield Orthopaedic Centre (GB), University of Manchester (GB), University Medical Center Utrecht (NL), University of Oxford (GB), Bone Cancer Research Trust (GB), Cancer Research UK Clinical Trials Unit (GB), NIHR Birmingham Biomedical Research Centre (GB), University of Birmingham (GB)
Medical Research Council, Engineering and Physical Sciences Research Council
Openalex Percentile: Top 0%
Sepsis Diagnosis and Treatment
27.08
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