Predictors of relapse rate in MS clinical trials
- 13 December 2005
- journal article
- Published by Wolters Kluwer Health in Neurology
- Vol. 65 (11) , 1769-1773
- https://doi.org/10.1212/01.wnl.0000187122.71735.1f
Abstract
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.Keywords
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