Прозрачная отчётность о многофакторной предсказательной модели для индивидуального прогнозирования или диагностики (TRIPOD): разъяснения и уточнения

Publication date

2022

Authors

Moons, Karel G MISNI 0000000390720943
Altman, Douglas G.
Reitsma, Johannes J BISNI 0000000389855461
Loannidis, John P.A.
Macaskill, Petra
Steyerberg, Ewout WORCID 0000-0002-7787-0122
Vickers, Andrew J.
Ransohoff, David F.
Collins, Gary S.

Editors

Advisors

Supervisors

Document Type

Article
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License

cc_by_nc_nd

Abstract

The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD Statement is explained in detail and accompanied by published examples of good reporting. The document also provides a valuable reference of issues to consider when designing, conducting, and analyzing prediction model studies. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, it is recommended that authors include a completed checklist in their submission. The TRIPOD checklist can also be downloaded from www.tripod-statement.org.

Keywords

Health Informatics, Internal Medicine, Radiology Nuclear Medicine and imaging, Radiological and Ultrasound Technology

Citation

Moons, K G M, Altman, D G, Reitsma, J B, Loannidis, J P A, Macaskill, P, Steyerberg, E W, Vickers, A J, Ransohoff, D F & Collins, G S 2022, 'Прозрачная отчётность о многофакторной предсказательной модели для индивидуального прогнозирования или диагностики (TRIPOD) : разъяснения и уточнения', Digital Diagnostics, vol. 3, no. 3, pp. 232-322. https://doi.org/10.17816/DD110794