Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statementBMJ 2015; 350 doi: https://doi.org/10.1136/bmj.g7594 (Published 07 January 2015) Cite this as: BMJ 2015;350:g7594
- Gary S Collins, associate professor1,
- Johannes B Reitsma, associate professor2,
- Douglas G Altman, professor1,
- Karel G M Moons, professor2
- 1Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Botnar Research Centre, University of Oxford, Oxford OX3 7LD, UK
- 2Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, PO Box 85500, 3508 GA Utrecht, Netherlands
- Correspondence to: G S Collins
- Accepted 7 November 2014
Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web based survey and revised during a three day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).
To encourage dissemination of the TRIPOD Statement, this article is freely accessible on the Annals of Internal Medicine Web site (www.annals.org) and will be also published in BJOG, British Journal of Cancer, British Journal of Surgery, BMC Medicine, The BMJ, Circulation, Diabetic Medicine, European Journal of Clinical Investigation, European Urology, and Journal of Clinical Epidemiology. The authors jointly hold the copyright of this article. An accompanying explanation and elaboration article is freely available only on www.annals.org; Annals of Internal Medicine holds copyright for that article.
Contributors: Conception and design: GSC, JBR, DGA, KGMM; analysis and interpretation of the data: GCS, DGA, KGMM; drafting of the article: GSC, JBR, DGA, KGMM; critical revision of the article for important intellectual content: GSC, JBR, DGA, KGMM; final approval of the article: GSC, JBR, DGA, KGMM; provision of study materials or patients: GSC, KGMM; statistical expertise: GSC, JBR, DGA, KGMM; obtaining of funding: GSC, DGA, KGMM; administrative, technical, or logistic support: GSC, KGMM; collection and assembly of data: GSC, DGA, KGMM.
Funding: There was no explicit funding for the development of this checklist and guidance document. The consensus meeting in June 2011 was partially funded by a National Institute for Health Research Senior Investigator Award held by DGA, Cancer Research UK (grant C5529), and the Netherlands Organization for Scientific Research (ZONMW 918.10.615 and 91208004). GSC and DGA are funded in part by the Medical Research Council (grant G1100513). DGA is a member of the Medical Research Council Prognosis Research Strategy (PROGRESS) Partnership (G0902393/99558).
Competing interests: Authors have disclosed no conflicts of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M14-0697.