{"title":"Which Prognostic Models Best Predict Clinical Disease Progression, Worsening, and Activity in People with Multiple Sclerosis? A Cochrane Review Summary with Commentary.","authors":"Bhasker Amatya, Fary Khan","doi":"10.1177/10538135241303581","DOIUrl":null,"url":null,"abstract":"<p><p>BackgroundPrognostic models have the potential to support people with Multiple Sclerosis (pwMS) and clinicians in treatment decision-making, enable stratified and precise interpretation of interventional trials, and offer insights into disease mechanisms. Despite many researchers being involved in developing these models to predict clinical outcomes in multiple sclerosis (MS), no widely accepted prognostic model is currently used in clinical practice.ObjectiveCommentary on the review by Reeve et al. (2023) to identify and summarise multivariable prognostic models, and their validation studies for quantifying the risk of clinical disease progression, worsening, and activity in pwMS.MethodsThis review included studies evaluating statistically developed multivariable prognostic models aiming to predict clinical disease progression, worsening, and activity, as measured by disability, relapse, conversion to definite MS, conversion to progressive MS, or a composite of these in adult individuals with MS.ResultsThe review included 57 studies, comprising 75 model developments, 15 external validations, and six author-reported validations. Only two models were validated multiple times externally, and none by independent researchers. The outcomes evaluated included disease progression (41%), relapses (8%), conversion to definite MS (18%), and conversion to progressive MS (28%). All models required specialist skills, 59% needed specialized equipment, and 52% lacked sufficient details for application or independent validation. Reporting quality was poor, and most models had a high risk of bias. The findings suggest increases in the number of participants on treatment, diverse diagnostic criteria, the use of biomarkers, and machine learning over time.ConclusionsDespite the development of many prognostic prediction models in pwMS, current evidence is insufficient to recommend any of these models for clinical use due to the high risk of bias, poor reporting, and lack of independent validation. The review's findings necessitate a cautious approach to integrating existing MS prognostic models into rehabilitation practice.</p>","PeriodicalId":19717,"journal":{"name":"NeuroRehabilitation","volume":"56 1","pages":"78-80"},"PeriodicalIF":1.7000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NeuroRehabilitation","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/10538135241303581","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/25 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Which Prognostic Models Best Predict Clinical Disease Progression, Worsening, and Activity in People with Multiple Sclerosis? A Cochrane Review Summary with Commentary.
BackgroundPrognostic models have the potential to support people with Multiple Sclerosis (pwMS) and clinicians in treatment decision-making, enable stratified and precise interpretation of interventional trials, and offer insights into disease mechanisms. Despite many researchers being involved in developing these models to predict clinical outcomes in multiple sclerosis (MS), no widely accepted prognostic model is currently used in clinical practice.ObjectiveCommentary on the review by Reeve et al. (2023) to identify and summarise multivariable prognostic models, and their validation studies for quantifying the risk of clinical disease progression, worsening, and activity in pwMS.MethodsThis review included studies evaluating statistically developed multivariable prognostic models aiming to predict clinical disease progression, worsening, and activity, as measured by disability, relapse, conversion to definite MS, conversion to progressive MS, or a composite of these in adult individuals with MS.ResultsThe review included 57 studies, comprising 75 model developments, 15 external validations, and six author-reported validations. Only two models were validated multiple times externally, and none by independent researchers. The outcomes evaluated included disease progression (41%), relapses (8%), conversion to definite MS (18%), and conversion to progressive MS (28%). All models required specialist skills, 59% needed specialized equipment, and 52% lacked sufficient details for application or independent validation. Reporting quality was poor, and most models had a high risk of bias. The findings suggest increases in the number of participants on treatment, diverse diagnostic criteria, the use of biomarkers, and machine learning over time.ConclusionsDespite the development of many prognostic prediction models in pwMS, current evidence is insufficient to recommend any of these models for clinical use due to the high risk of bias, poor reporting, and lack of independent validation. The review's findings necessitate a cautious approach to integrating existing MS prognostic models into rehabilitation practice.
期刊介绍:
NeuroRehabilitation, an international, interdisciplinary, peer-reviewed journal, publishes manuscripts focused on scientifically based, practical information relevant to all aspects of neurologic rehabilitation. We publish unsolicited papers detailing original work/research that covers the full life span and range of neurological disabilities including stroke, spinal cord injury, traumatic brain injury, neuromuscular disease and other neurological disorders.
We also publish thematically organized issues that focus on specific clinical disorders, types of therapy and age groups. Proposals for thematic issues and suggestions for issue editors are welcomed.