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

Daniel Feller · Roel W. Wingbermühle · Bjørnar Berg · Ørjan Nesse Vigdal · Tiziano Innocenti · Margreth Grotle +2 more

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Meta-analysis and systematic reviews Musculoskeletal pain and rehabilitation Statistical Methods in Epidemiology

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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2016Rayyan—a web and mobile app for systematic reviews 2015Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration 2021Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence 2017Guidelines for reporting meta-epidemiological methodology research 2022Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review 2019Uniformity in measuring adherence to reporting guidelines: the example of TRIPOD for assessing completeness of reporting of prediction model studies 2021Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved 2018Reporting guidelines: doing better for readers

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