van Geloven, N, Giardiello, D, Bonneville, EF, Teece, L, Ramspek, CL, van Smeden, M, Snell, KIE ORCID: https://orcid.org/0000-0001-9373-6591, van Calster, B, Pohar-Perme, M, Riley, RD ORCID: https://orcid.org/0000-0001-8699-0735, Putter, H, Steyerberg, E and initiative, STRATOS (2022) Validation of prediction models in the presence of competing risks: a guide through modern methods. BMJ, 377. e069249 - ?.

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Abstract

Thorough validation is pivotal for any prediction model before it can be advocated for use in medical practice. For time-to-event outcomes such as breast cancer recurrence, death from other causes is a competing risk. Model performance measures must account for such competing events. In this article, we present a comprehensive yet accessible overview of performance measures for this competing event setting, including the calculation and interpretation of statistical measures for calibration, discrimination, overall prediction error, and clinical usefulness by decision curve analysis. All methods are illustrated for patients with breast cancer, with publicly available data and R code.

Item Type: Article
Additional Information: The final version of this accepted manuscript and all relevant information related to it, including copyrights, can be found on the publisher website.
Subjects: R Medicine > R Medicine (General)
Divisions: Faculty of Medicine and Health Sciences > School of Medicine
Related URLs:
Depositing User: Symplectic
Date Deposited: 15 Jul 2022 15:32
Last Modified: 20 Jul 2022 14:02
URI: https://eprints.keele.ac.uk/id/eprint/11091

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