Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement
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TLDR
The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used, and is best used in conjunction with the TRIPod explanation and elaboration document.Abstract:
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 3-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).read more
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Radiomics: the bridge between medical imaging and personalized medicine
Philippe Lambin,Ralph T.H. Leijenaar,Timo M. Deist,Jurgen Peerlings,Evelyn E.C. de Jong,Janita E. van Timmeren,Sebastian Sanduleanu,Ruben T. H. M. Larue,Aniek J.G. Even,Arthur Jochems,Yvonka van Wijk,Henry C. Woodruff,Johan van Soest,Tim Lustberg,Erik Roelofs,Wouter van Elmpt,Andre Dekker,Felix M. Mottaghy,Felix M. Mottaghy,Joachim E. Wildberger,Sean Walsh +20 more
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STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies
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TL;DR: STARD 2015 is presented, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study, which incorporates recent evidence about sources of bias and variability in diagnostic accuracy.
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Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer
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