Trends in annualized relapse rates in relapsing–remitting multiple sclerosis and consequences for clinical trial design

Abstract

Background: Sample size calculation is a key aspect in the planning of any trial. Planning a randomized placebo-controlled trial in relapsing–remitting multiple sclerosis (RRMS) requires knowledge of the annualized relapse rate (ARR) in the placebo group. Objectives: This paper aims (i) to characterize the uncertainty in ARR by conducting a systematic review of placebo-controlled, randomized trials in RRMS and by modelling the ARR over time; and (ii) to assess the feasibility and utility of blinded sample size re-estimation (BSSR) procedures in RRMS. Methods: A systematic literature review was carried out by searching PubMed, Ovid Medline and the Cochrane Register of Controlled Trials. The placebo ARRs were modelled by negative binomial regression. Computer simulations were conducted to assess the utility of BSSR in RRMS. Results: Data from 26 placebo-controlled randomized trials were included in this analysis. The placebo ARR decreased by 6.2% per year (p < 0.0001; 95% CI (4.2%; 8.1%)) resulting in substantial uncertainty in the planning of future trials. BSSR was shown to be feasible and to maintain power at a prespecified level also if the ARR was misspecified in the planning phase. Conclusions: Our investigations confirmed previously reported trends in ARR. In this context adaptive strategies such as BSSR designs are recommended for consideration in the planning of future trials in RRMS.