Effect of Disease-Modifying Therapy on Disability in Relapsing-Remitting Multiple Sclerosis Over 15 Years

Tomas Kalincik 1, Ibrahima Diouf 2, Sifat Sharmin 2, Charles Malpas 2, Tim Spelman 2, Dana Horakova 2, Eva Kubala Havrdova 2, Maria Trojano 2, Guillermo Izquierdo 2, Alessandra Lugaresi 2, Alexandre Prat 2, Marc Girard 2, Pierre Duquette 2, Pierre Grammond 2, Vilija Jokubaitis 2, Anneke van der Walt 2, Francois Grand'Maison 2, Patrizia Sola 2, Diana Ferraro 2, Vahid Shaygannejad 2, Raed Alroughani 2, Raymond Hupperts 2, Murat Terzi 2, Cavit Boz 2, Jeannette Lechner-Scott 2, Eugenio Pucci 2, Vincent Van Pesch 2, Franco Granella 2, Roberto Bergamaschi 2, Daniele Spitaleri 2, Mark Slee 2, Steve Vucic 2, Radek Ampapa 2, Pamela McCombe 2, Cristina Ramo-Tello 2, Julie Prevost 2, Javier Olascoaga 2, Edgardo Cristiano 2, Michael Barnett 2, Maria Laura Saladino 2, Jose Luis Sanchez-Menoyo 2, Suzanne Hodgkinson 2, Csilla Rozsa 2, Stella Hughes 2, Fraser Moore 2, Cameron Shaw 2, Ernest Butler 2, Olga Skibina 2, Orla Gray 2, Allan Kermode 2, Tunde Csepany 2, Bhim Singhal 2, Neil Shuey 2, Imre Piroska 2, Bruce Taylor 2, Magdolna Simo 2, Carmen-Adella Sirbu 2, Attila Sas 2, Helmut Butzkueven 2; MSBase Study Group

Affiliations

02 February 2021

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doi: 10.1212/WNL.0000000000011242

Abstract

Objective: To test the hypothesis that immunotherapy prevents long-term disability in relapsing-remitting multiple sclerosis (MS), we modeled disability outcomes in 14,717 patients.

Methods: We studied patients from MSBase followed for ≥1 year, with ≥3 visits, ≥1 visit per year, and exposed to MS therapy, and a subset of patients with ≥15-year follow-up. Marginal structural models were used to compare the cumulative hazards of 12-month confirmed increase and decrease in disability, Expanded Disability Status Scale (EDSS) step 6, and the incidence of relapses between treated and untreated periods. Marginal structural models were continuously readjusted for patient age, sex, pregnancy, date, disease course, time from first symptom, prior relapse history, disability, and MRI activity.

Results: A total of 14,717 patients were studied. During the treated periods, patients were less likely to experience relapses (hazard ratio 0.60, 95% confidence interval [CI] 0.43-0.82, p = 0.0016), worsening of disability (0.56, 0.38-0.82, p = 0.0026), and progress to EDSS step 6 (0.33, 0.19-0.59, p = 0.00019). Among 1,085 patients with ≥15-year follow-up, the treated patients were less likely to experience relapses (0.59, 0.50-0.70, p = 10-9) and worsening of disability (0.81, 0.67-0.99, p = 0.043).

Conclusion: Continued treatment with MS immunotherapies reduces disability accrual by 19%-44% (95% CI 1%-62%), the risk of need of a walking aid by 67% (95% CI 41%-81%), and the frequency of relapses by 40-41% (95% CI 18%-57%) over 15 years. This study provides evidence that disease-modifying therapies are effective in improving disability outcomes in relapsing-remitting MS over the long term.

Classification of evidence: This study provides Class IV evidence that, for patients with relapsing-remitting MS, long-term exposure to immunotherapy prevents neurologic disability.

Figures

Figure 1. Patient Disposition The data quality procedure excluded 147 patient records: 95 from centers with less than 10 enrolled patients, 49 with missing birth date or date of MS onset, and 3 with erroneous information about disease progression. The inclusion criteria were applied so that patients' follow-up is of sufficient duration to enable evaluation of at least short-term disability outcomes (≥1 year), with a minimum number of data points to ensure that individual hazard of confirmed disability worsening is non-zero (≥3 EDSS scores), sufficient data density to minimize the risk of disability events that were not captured, and to minimize recall bias (≥1 EDSS score per year). The minimum data set was required for calculation of the inverse probability of treatment weights and outcomes. Patients had to be exposed to an MS immunotherapy at least once in order to eliminate treatment indication bias, which is significant for untreated patients in countries where immunotherapies are commonly available. One third of patients excluded from the analysis due to insufficient data were enrolled in MSBase during the recent 2 years and did not yet accumulate sufficient follow-up information.

Figure 1. Patient Disposition The data quality procedure excluded 147 patient records: 95 from centers with less than 10 enrolled patients, 49 with missing birth date or date of MS onset, and 3 with erroneous information about disease progression. The inclusion criteria were applied so that patients' follow-up is of sufficient duration to enable evaluation of at least short-term disability outcomes (≥1 year), with a minimum number of data points to ensure that individual hazard of confirmed disability worsening is non-zero (≥3 EDSS scores), sufficient data density to minimize the risk of disability events that were not captured, and to minimize recall bias (≥1 EDSS score per year). The minimum data set was required for calculation of the inverse probability of treatment weights and outcomes. Patients had to be exposed to an MS immunotherapy at least once in order to eliminate treatment indication bias, which is significant for untreated patients in countries where immunotherapies are commonly available. One third of patients excluded from the analysis due to insufficient data were enrolled in MSBase during the recent 2 years and did not yet accumulate sufficient follow-up information.

Figure 2. Incidence of Relapses, Disability Accumulation, and Improvement in the Treated and Untreated Pseudocohorts (A) Relapses. (B) Disability accumulation. (C) Disability Improvement. Cumulative hazards for unadjusted models (dotted) and marginal structural models adjusted with inverse probability of treatment weights (solid) are shown. Dashed lines show 95% confidence intervals (CIs). Numbers of patients contributing to the treated and untreated pseudocohorts are shown at multiple time points. HR = hazard ratio.

Figure 2. Incidence of Relapses, Disability Accumulation, and Improvement in the Treated and Untreated Pseudocohorts (A) Relapses. (B) Disability accumulation. (C) Disability Improvement. Cumulative hazards for unadjusted models (dotted) and marginal structural models adjusted with inverse probability of treatment weights (solid) are shown. Dashed lines show 95% confidence intervals (CIs). Numbers of patients contributing to the treated and untreated pseudocohorts are shown at multiple time points. HR = hazard ratio.

Figure 3. The Risk of Expanded Disability Status Scale (EDSS) 6 The risk of reaching EDSS 6 (patients use a single-point walking aid to walk ≥100 meters) in the treated and untreated pseudocohorts. Cumulative hazards for unadjusted models (dotted) and marginal structural models adjusted with inverse probability of treatment weights (solid) are shown. Dashed lines show 95% confidence intervals (CIs). Numbers of patients contributing to the treated and untreated pseudocohorts are shown at multiple time points. HR = hazard ratio.

Figure 3. The Risk of Expanded Disability Status Scale (EDSS) 6 The risk of reaching EDSS 6 (patients use a single-point walking aid to walk ≥100 meters) in the treated and untreated pseudocohorts. Cumulative hazards for unadjusted models (dotted) and marginal structural models adjusted with inverse probability of treatment weights (solid) are shown. Dashed lines show 95% confidence intervals (CIs). Numbers of patients contributing to the treated and untreated pseudocohorts are shown at multiple time points. HR = hazard ratio.

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