A proof-of-concept application of a novel scoring approach for personalized medicine in multiple sclerosis. (August 2020)

• Record Type: Journal Article
• Authors: Pellegrini, Fabio; Copetti, Massimiliano; Bovis, Francesca; Cheng, David; Hyde, Robert; de Moor, Carl; Kieseier, Bernd C; Sormani, Maria Pia
• Is Part Of: Multiple sclerosis. Volume 26:Number 9(2020)
• Page Start: 1064
• Page End: 1073
• Publication Date: 2020-08
• Subjects: Multiple sclerosis -- proof-of-concept -- personalized medicine -- individual treatment response -- dimethyl fumarate -- treatment algorithms; Central nervous system -- Diseases -- Periodicals; Myelin sheath -- Diseases -- Periodicals; Inflammation -- Periodicals; Multiple sclerosis -- Periodicals; Central Nervous System Diseases -- Periodicals; Demyelinating Diseases -- Periodicals; Inflammation -- Periodicals; Multiple Sclerosis -- Periodicals; Système nerveux central -- Maladies -- Périodiques; Gaine de myéline -- Maladies -- Périodiques; Inflammation (Pathologie) -- Périodiques; Sclérose en plaques -- Périodiques; Electronic journals; 616.834005
• DOI: 10.1177/1352458519849513
• Languages: English
• ISSNs: 1352-4585

Abstract

Background: Stratified medicine methodologies based on subgroup analyses are often insufficiently powered. More powerful personalized medicine approaches are based on continuous scores. Objective: We deployed a patient-specific continuous score predicting treatment response in patients with relapsing-remitting multiple sclerosis (RRMS). Methods: Data from two independent randomized controlled trials (RCTs) were used to build and validate an individual treatment response (ITR) score, regressing annualized relapse rates (ARRs) on a set of baseline predictors. Results: The ITR score for the combined treatment groups versus placebo detected differential clinical response in both RCTs. High responders in one RCT had a cross-validated ARR ratio of 0.29 (95% confidence interval (CI) = 0.13–0.55) versus 0.62 (95% CI = 0.47–0.83) for all other responders (heterogeneity p = 0.038) and were validated in the other RCT, with the corresponding ARR ratios of 0.31 (95% CI = 0.18–0.56) and 0.61 (95% CI = 0.47–0.79; heterogeneity p = 0.036). The strongest treatment effect modifiers were the Short Form-36 Physical Component Summary, age, Visual Function Test 2.5%, prior MS treatment and Expanded Disability Status Scale. Conclusion: Our modelling strategy detects and validates an ITR score and opens up avenues for building treatment response calculators that are also applicable in routine clinical practice.