Three myths about risk thresholds for prediction models

• Published in: BMC Medicine
• Main Authors: Wynants, Laure, van Smeden, Maarten, McLernon, David J, Timmerman, Dirk, Steyerberg, Ewout W, Van Calster, Ben
• Other Authors: University of Aberdeen.Other Applied Health Sciences, University of Aberdeen.Grampian Data Safe Haven (DaSH), University of Aberdeen.Institute of Applied Health Sciences, University of Aberdeen.Medical Statistics
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2019
• Subjects: Clinical risk prediction model; Threshold; Decision support techniques; Risk; Data science; Diagnosis; Prognosis; R Medicine; R; DML
• Online Access: https://hdl.handle.net/2164/13490; https://doi.org/10.1186/s12916-019-1425-3

Acknowledgments This work was developed as part of the international initiative of strengthening analytical thinking for observational studies (STRATOS). The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies (http://stratos-initiative.org/). Members of the STRATOS Topic Group ‘Evaluating diagnostic tests and prediction models’ are Gary Collins, Carl Moons, Ewout Steyerberg, Patrick Bossuyt, Petra Macaskill, David McLernon, Ben van Calster, and Andrew Vickers. Funding The study is supported by the Research Foundation-Flanders (FWO) project G0B4716N and Internal Funds KU Leuven (project C24/15/037). Laure Wynants is a post-doctoral fellow of the Research Foundation – Flanders (FWO). The funding bodies had no role in the design of the study, collection, analysis, interpretation of data, nor in writing the manuscript. Contributions LW and BVC conceived the original idea of the manuscript, to which ES, MVS and DML then contributed. DT acquired the data. LW analyzed the data, interpreted the results and wrote the first draft. All authors revised the work, approved the submitted version, and are accountable for the integrity and accuracy of the work. Peer reviewed