In the absence of controlled, parallel-group studies, statistical methods developed to estimate treatment effects in patients receiving alternative/rescue treatment in clinical trials may be used to estimate the effects of switching multiple sclerosis (MS) therapy. The method was illustrated using available clinical trial data. Dr. Gary Cutter, professor in the department of biostatistics at the University of Alabama at Birmingham, recently collaborated with a team of researchers using data from theTrial Assessing Injectable Interferon Versus Fingolimod Oral in Relapsing–Remitting Multiple Sclerosis (TRANSFORMS) Study. The research involved using parametric models to assess the time to first confirmed relapse in MS patients who switched from intramuscular (IM) interferon β-1a (IFNβ-1a IM) 30 μg/mL once weekly to oral fingolimod 0.5 or 1.25 mg once daily versus remaining on IFNβ-1a IM. Post hoc analyses were conducted using data from the intent-to-treat population. The Branson and Whitehead switch model with iterative parameter estimation was used to estimate the ratio of the observed time to first confirmed relapse over the estimated time. This ratio provides an estimate of the impact of switching under the model assumptions.
In the specific example, the model suggested that during the extension phase of the trial, the time to first confirmed relapse was approximately doubled in patients switching from IFNβ-1a IM to fingolimod. The researchers determined that these analytic methods may be useful in evaluating treatment switch effects in clinical trials with extension data.
“Effect of Switching from Intramuscular Interferon β-1a to Oral Fingolimod on Time to Relapse in Patients with Relapsing-Remitting Multiple Sclerosis Enrolled in a 1-Year Extension of TRANSFORMS” was published in December 2014 in the journal Contemporary Clinical Trials.