4.7 Article

Predictors of relapse rate in MS clinical trials

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NEUROLOGY
卷 65, 期 11, 页码 1769-1773

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LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1212/01.wnl.0000187122.71735.1f

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Background: The annual relapse rate has been commonly used as a primary efficacy endpoint in phase III multiple sclerosis ( MS) clinical trials. The aim of this study was to determine the relative contribution of different possible prognostic factors available at baseline to the on-study relapse rate in MS. Methods: A total of 821 patients from the placebo arms of the Sylvia Lawry Centre for Multiple Sclerosis Research (SLCMSR) database were available for this analysis. The univariate relationships between on-study relapse rate and the baseline demographic, clinical, and MRI-based predictors were assessed. The multiple relationships were then examined using a Poisson regression model. Two predictor subsets were selected. Subset 1 included age at disease onset, disease duration, sex, Expanded Disability Status Scale ( EDSS) at baseline, number of relapses in the last 24 months prior to baseline, and the disease course ( relapsing remitting [RR] and secondary progressive [SP]). Subset 2 consisted of Subset 1 plus gadolinium enhancement status in MRI. The number of patients for developing the models with no missing values was 727 for Subset 1 and 306 for Subset 2. Results: The univariate relationships show that the on-study relapse rate was higher for younger and for female patients, for RR patients than for SP patients, and for patients with positive enhancement status at entry ( Wilcoxon test, p < 0.05). A higher on-study relapse rate was associated with a shorter disease duration, lower entry EDSS, more pre-study relapses, and more enhancing lesions in T1 at entry. The fitted Poisson model shows that disease duration ( estimate = -0.02) and previous relapse number ( estimate = 0.59 for one, 0.91 for two, and 1.45 for three or more relapses vs no relapses) remain. The authors were able to confirm these findings in a second, independent dataset. Conclusions: The relapse number prior to entry into clinical trials together with disease duration are the best predictors for the on-study relapse rate. Disease course did not contribute independently because its effect is covered by the pre-study relapse rate. Gadolinium enhancement status, given the other covariates, has no significant influence on the on-study relapse rate.

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