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Improvements Are Needed in the Adherence to the TRIPOD Statement for Clinical Prediction Models for Patients With Spinal Pain or Osteoarthritis: A Metaresearch Study - 10/08/24

Doi : 10.1016/j.jpain.2024.104624 
Daniel Feller , , , Roel Wingbermuhle , §, Bjørnar Berg , Ørjan Nesse Vigdal , Tiziano Innocenti ⁎⁎, ††, Margreth Grotle , ‡‡, Raymond Ostelo ⁎⁎, §§, Alessandro Chiarotto
 Department of Rehabilitation, Provincial Agency for Health of the Autonomous Province of Trento, Trento, Italy 
 Department of Human Resources, Provincial Agency for Health of the Autonomous Province of Trento, Trento, Italy 
 Department of General Practice, Erasmus MC, University Medical Center, Rotterdam, the Netherlands 
§ Department of Physiotherapy and Rehabilitation sciences, SOMT University of Physiotherapy, Amersfoort, the Netherlands 
 Centre for Intelligent Musculoskeletal Health, Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway 
 Department of Rehabilitation Science and Health Technology, Faculty of Health Science, OsloMet - Oslo Metropolitan University, Oslo, Norway 
⁎⁎ Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands 
†† GIMBE Foundation, Bologna, Italy 
‡‡ Division of Clinical Neuroscience, Department of Research and Innovation, Oslo University Hospital, Oslo, Norway 
§§ Department of Epidemiology and Data Science, Amsterdam UMC, Vrije Universiteit & Amsterdam Movement Sciences, Musculoskeletal Health, Amsterdam, the Netherlands 

Address reprint requests to Daniel Feller, MSc, PhD student, Via Lungo Leno 27, Rovereto, Trento 38068, Italy.Via Lungo Leno 27, RoveretoTrento38068Italy
Sous presse. Épreuves corrigées par l'auteur. Disponible en ligne depuis le Saturday 10 August 2024

Abstract

This metaresearch study aimed to evaluate the completeness of reporting of prediction model studies in patients with spinal pain or osteoarthritis (OA) in terms of adherence to the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) statement. We searched for prognostic and diagnostic prediction models in patients with spinal pain or OA in MEDLINE, Embase, Web of Science, and CINAHL. Using a standardized assessment form, we assessed the adherence to the TRIPOD of the included studies. Two independent reviewers performed the study selection and data extraction phases. We included 66 studies. Approximately 35% of the studies declared to have used the TRIPOD. The median adherence to the TRIPOD was 59% overall (interquartile range (IQR): 21.8), with the items of the methods and results sections having the worst reporting. Studies on neck pain had better adherence to the TRIPOD than studies on back pain and OA (medians of 76.5%, 59%, and 53%, respectively). External validation studies had the highest total adherence (median: 79.5%, IQR: 12.8) of all the study types. The median overall adherence was 4 points higher in studies that declared TRIPOD use than those that did not. Finally, we did not observe any improvement in adherence over the years. The adherence to the TRIPOD of prediction models in the spinal and OA fields is low, with the methods and results sections being the most poorly reported. Future studies on prediction models in spinal pain and OA should follow the TRIPOD to improve their reporting completeness.

Perspective

This article provides data about adherence to the TRIPOD statement in 66 prediction model studies for spinal pain or OA. The adherence to the TRIPOD statement was found to be low (median adherence of 59%). This inadequate reporting may negatively impact the effective use of the models in clinical practice.

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Highlights

We evaluated the adherence to the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) in 66 spinal pain or osteoarthritis prediction models.
The adherence to the TRIPOD statement was generally low (median adherence of 59%).
An inadequate reporting may hinder the effective application of a model in clinical practice.
Future prediction models must adhere to the TRIPOD reporting guideline.
The use of the TRIPOD should be encouraged by peer reviews and journal editors.

Le texte complet de cet article est disponible en PDF.

Key words : Reporting guidelines, machine learning, reporting, prognosis, diagnosis


Plan


 Supplementary data accompanying this article are available online at www.jpain.org and www.sciencedirect.com.


© 2024  The Authors. Publié par Elsevier Masson SAS. Tous droits réservés.
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