Prognostic models for predicting clinical disease progression, worsening and activity in people with multiple sclerosis

Abstract

Objectives: This is a protocol for a Cochrane Review (prognosis). The objectives are as follows:. Primary objectives To identify and summarize multivariable prognostic models for quantifying the risk of clinical disease progression, worsening, and activity in MS. To this end we will: describe the characteristics of the identified multivariable prognostic models, including prognostic factors considered and evaluation measures used; describe changes in outcome definitions, time frames, prognostic factors and statistical methods over time; qualitatively summarize the validation performance of the models; summarize model performance across external validation studies via meta-analysis, where possible; assess the risk of bias in the models; evaluate moderating effects on model performance by meta-regression, where possible; and make recommendations for future MS prognostic research. Investigation of sources of heterogeneity between studies We expect to find substantial heterogeneity, as diagnostic criteria for MS subtypes and available treatment options, as well as the technology used to assess disease activity, have evolved over time. Heterogeneity is also typically high in prognostic studies. We expect heterogeneity both between development studies and their corresponding validation studies for specific models and also between different development models for the same outcome. Potential sources of heterogeneity related to either or both of these include: case mix (e.g. age, gender, disease duration, treatment status); study design (e.g. follow-up time, source of data, outcome and prognostic factor definitions); and statistical analysis methods and reporting (e.g. number of prognostic factors included, traditional statistics versus machine learning, risk of bias, validation methods). We will extract relevant information and will include a narrative summary of these potential sources of heterogeneity. We will further investigate heterogeneity using meta-regression, as detailed in the protocol.