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Updated: May 19, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Time to first relapse as an endpoint in multiple sclerosis clinical trials
M P Sormani1, A Signori, P Siri
1Department of Health Sciences (DISSAL), University of Genova, Via Pastore 1, Genova, 16132, Italy. mariapia.sormani@unige.it
Background:
The increasing number of effective therapies to treat multiple sclerosis (MS) raises ethical concerns for the use of placebo in clinical trials, suggesting that new clinical trial design strategies are needed.
Objectives:
To evaluate time to first relapse as an endpoint for MS clinical trials.
Methods:
A recently-developed model fitting the distribution of time to first relapse in MS was used for simulations estimating the sample sizes of trials using this as an outcome, and for comparison with the size of trials using the annualized relapse rate (ARR) as the primary outcome.
Results:
Trials based on time to first relapse were feasible, requiring sample sizes that were similar or even smaller than if the study was based on ARR instead. In the case of low ARR (0.4 relapses/year), as is expected in future trials, the 1-year trials designed to detect a treatment effect of 30%, with 90% power, require fewer patients when based on time to first relapse (470 patients/arm) than if based on ARR (540 patients/arm).
Conclusions:
Our simulations show that time to first relapse is not less powerful than ARR in MS trials; thus, this measure would be a potentially useful primary outcome offering the advantage of an ethically sound design, as the patients randomized to placebo can then switch to the active drug, once they relapse. A potential drawback is the loss of information for other endpoints collected at fixed time points.
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