A decision-analytical perspective on incorporating multiple outcomes in the production of clinical prediction models: defining a taxonomy of risk estimands
Clearly defining and reporting the risk estimand is essential for all prediction model studies. A decision-analytical framework aids in selecting the most appropriate estimand for a given prediction task and in determining when and how to incorporate multiple outcomes into CPM development.
Authors
- Matthew Sperrin (ORCID: https://orcid.org/0000-0002-5351-9960)
- Alexander Pate (ORCID: https://orcid.org/0000-0002-0849-3458)
- Glen Philip Martin (ORCID: https://orcid.org/0000-0002-3410-9472)
- Richard D Riley (ORCID: https://orcid.org/0000-0001-8699-0735)
- Siân Bladon (ORCID: https://orcid.org/0000-0001-9087-6505)
Institutions
- Manchester Academic Health Science Centre (GB)
- University of Manchester (GB)
- University of Birmingham (GB)
Publication Details
- Journal
- BMC Medicine
- Published
- 2025-03-06
- DOI
- https://doi.org/10.1186/s12916-025-03978-3
- Citations
- 4
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 9.92
Funders
- Engineering and Physical Sciences Research Council