Abstract
The natural history of relapsing remitting multiple sclerosis (RRMS) is variable and prediction of individual prognosis challenging. The inability to reliably predict prognosis at diagnosis has important implications for informed decision making especially in relation to disease modifying therapies. We conducted a systematic review in order to collate, describe and assess the methodological quality of published prediction models in RRMS. We searched Medline, Embase and Web of Science. Two reviewers independently screened abstracts and full text for eligibility and assessed risk of bias. Studies reporting development or validation of prediction models for RRMS in adults were included. Data collection was guided by the checklist for critical appraisal and data extraction for systematic reviews (CHARMS) and applicability and methodological quality assessment by the prediction model risk of bias assessment tool (PROBAST). 30 studies were included in the review. Applicability was assessed as high risk of concern in 27 studies. Risk of bias was assessed as high for all studies. The single most frequently included predictor was baseline EDSS (n = 11). T2 Lesion volume or number and brain atrophy were each retained in seven studies. Five studies included external validation and none included impact analysis. Although a number of prediction models for RRMS have been reported, most are at high risk of bias and lack external validation and impact analysis, restricting their application to routine clinical practice.
Highlights
The natural history of relapsing remitting multiple sclerosis (RRMS) is variable and prediction of individual prognosis is challenging [1]
This review reports on studies that identify predictors of target outcomes, assign weights to each predictor using multivariable analysis, and develop a prediction model for adult patients with RRMS
Database searches from inception to August week three 2019 identified 5193 studies of which 30 studies met the pre-defined inclusion criteria (Fig 1) [22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51]. 23 studies were model development only [22,23,24,26,29,30,31,32,33,34,37,39,40,41,42,43,44,45,46,48,49,50,51], five were model development and external validation in the same study [25,35,36,38,47] and two were external validation studies of the same model [27,28]
Summary
The natural history of relapsing remitting multiple sclerosis (RRMS) is variable and prediction of individual prognosis is challenging [1]. The inability to reliably prognosticate at diagnosis has important implications for informed decision making especially in relation to disease modifying therapy (DMT). Risk stratification at diagnosis into disease severity categories (mild, moderate or severe) could better allow treating physicians and people with RRMS to make treatment decisions, but this is difficult early in the disease process. NM has received honoraria for talks or advisory boards from Biogen, Novartis, Genzyme, Merck and Roche over the same time period. This does not alter our adherence to PLOS ONE policies on sharing data and materials
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