A 2-stage model of heterogenous treatment effects for brain atrophy in multiple sclerosis utilizing the MS PATHS research network

Abstract

BackgroundTwo-stage models of heterogenous treatment effects (HTE) may advance personalized medicine in multiple sclerosis (MS). Brain atrophy is a relatively objective outcome measure that has strong relationships to MS prognosis and treatment effects and is enabled by standardized MRI. ObjectivesTo predict brain atrophy outcomes for patients initiating disease-modifying therapies (DMT) with different efficacies, considering the patients’ baseline brain atrophy risk measured via brain parenchymal fraction (BPF). MethodsAnalyses included patients enrolled in the Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS) network who started DMT and had complete baseline data and ≥ 6-month brain MRI follow-up. All brain MRIs were acquired using standardized acquisition sequences on Siemens 3T scanners. BPF change risk was derived by linear mixed effects models using baseline covariates. Model performance was assessed by predicted versus actual BPF change R2. Propensity score (PS) weighting was used to balance covariates between groups defined by DMT efficacy (high: natalizumab, alemtuzumab, ocrelizumab, and rituximab; moderate: dimethyl fumarate, fingolimod, and cladribine; low: teriflunomide, interferons, and glatiramer acetate). HTE models predicting 1 year change in BPF were built using a weighted linear mixed effects model with low-efficacy DMT as the reference. ResultsAnalyses included 581 high-, 183 moderate-, and 106 low-efficacy DMT-treated patients. The mean and median number of brain MRI observations per treatment period were 2.9 and 3.0, respectively. Risk model performance R2=0.55. After PS weighting, covariate standardized mean differences were <10 %, indicating excellent balance across measured variables. Changes in BPF between baseline and follow-up were found to be statistically significant (p < 0.001), suggesting a pathological change. Patients with low brain atrophy risk had a similar outcome regardless of DMT selection. In patients with high brain atrophy risk, high- and moderate-efficacy DMTs performed similarly, while a 2-fold worse BPF change was predicted for patients selecting low-efficacy DMTs (p < 0.001). Similar results were observed in a sensitivity analysis adjusting for pseudoatrophy effects in a sub-population of patients treated with natalizumab. ConclusionsThe relative benefit of selecting higher efficacy treatments may vary depending on patients’ baseline brain atrophy risk. Poor outcomes are predicted in individuals with high baseline risk who are treated with low-efficacy DMTs.