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[Preprint]. 2025 Dec 30:2025.12.01.25341331. Originally published 2025 Dec 2. [Version 2] doi: 10.64898/2025.12.01.25341331

Ocrelizumab versus Natalizumab in Relapsing-Remitting Multiple Sclerosis: A Registry-Linked Electronic Health Records Study

Feiqing Huang, Wen Zhu, Jue Hou, Sara Morini Sweet, Yunqing Han, Jun Wen, Katherine P Liao, Tianrun Cai, Tanuja Chitnis, Florence Bourgeois, Zongqi Xia, Tianxi Cai
PMCID: PMC12706613  PMID: 41409680

Abstract

Background: Ocrelizumab and natalizumab are commonly prescribed high-effectiveness disease-modifying therapies (DMTs) for relapsing-remitting multiple sclerosis (RRMS). However, no randomized clinical trial and few real-world studies have directly compared their effectiveness in reducing disability progression. Subtype classification and disability status are critical for multiple sclerosis (MS) research, but these data are often missing in electronic health records (EHRs), limiting robust real-world evidence generation. Objective: To compare the effectiveness of ocrelizumab and natalizumab in two-year rater-assessed disability progression among RRMS patients using longitudinal registry-linked EHR data. Design: Retrospective cohort study. Setting: A large healthcare system that includes both academic and community practices. Participants: Patients diagnosed with MS who initiated ocrelizumab or natalizumab between 2012 and 2020, with at least 6-month EHR data before treatment initiation and no prior exposure to other high-effectiveness DMTs. Exposures: Treatment with ocrelizumab vs natalizumab. Measurements: We developed an ensemble machine learning model to impute RRMS subtype and disability outcomes using structured and narrative EHR data. The primary outcome was moderate/severe rater-assessed disability at 2 years (observed or imputed Expanded Disability Status Scale [EDSS]≥4) after treatment initiation. We estimated the average treatment effects using semi-supervised doubly robust approach with comprehensive confounder adjustment and calibration to mitigate imputation bias. Covariates included standard demographic and clinical features such as baseline disability as well as knowledge graph-selected features. Sensitivity analyses used observed EDSS scores in registry-derived RRMS patients. Exploratory analyses included rituximab, another B-cell-depleting therapy, with adjustments for differences in patient profiles. Results: Among RRMS patients, those treated with ocrelizumab (n=543) had a significantly lower two-year risk of moderate/severe disability compared with those treated with natalizumab (n=205) based on imputed outcomes (risk difference, -5.87%; 95% CI: -11.28% to -0.46%; p=0.033) after confounder adjustment. Sensitivity analyses yielded consistent findings using imputed or observed EDSS outcomes in registry-derived RRMS patients. Conclusion and relevance: In this real-world comparative effectiveness study using a novel semi-supervised doubly-robust framework, ocrelizumab was associated with a lower risk of disability progression than natalizumab among RRMS patients. This approach provides a roadmap for generating robust large-scale real-world evidence in settings of missing key inclusion features and outcomes.

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