Journal article
Uncertainty of risk estimates from clinical prediction models: rationale, challenges, and approaches
- Abstract:
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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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, pdf, 1.1MB, Terms of use)
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- Publisher copy:
- 10.1136/bmj-2024-080749
Authors
- Publisher:
- BMJ Publishing Group
- Journal:
- British Medical Journal More from this journal
- Volume:
- 388
- Article number:
- e080749
- Place of publication:
- England
- Publication date:
- 2025-02-13
- Acceptance date:
- 2024-11-28
- DOI:
- EISSN:
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0959-8138
- ISSN:
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1759-2151
- Pmid:
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39947680
- Language:
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English
- Pubs id:
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2086073
- Local pid:
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pubs:2086073
- Deposit date:
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2025-03-17
- ARK identifier:
Terms of use
- Copyright holder:
- Riley et al
- Copyright date:
- 2025
- Rights statement:
- © 2025 The Authors. This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited.
- Licence:
- CC Attribution (CC BY)
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