Prognostic models in multiple sclerosis: progress and challenges in clinical integration

Abstract

As a chronic inflammatory disease of the central nervous system, multiple sclerosis (MS) is of great individual health and socio-economic significance. To date, there is no prognostic model that is used in routine clinical care to predict the very heterogeneous course of the disease. Despite several research groups working on different prognostic models using traditional statistics, machine learning and/or artificial intelligence approaches, the use of published models in clinical decision making is limited because of poor model performance, lack of transferability and/or lack of validated models. To provide a systematic overview, we conducted a “Cochrane review” that assessed 75 published prediction models using relevant checklists (CHARMS, PROBAST, TRIPOD). We have summarized the relevant points from this analysis here so that the use of prognostic models for therapy decisions in clinical routine can be successful in the future.