Abstract
Objectives
Statistical methods to adjust for treatment switching are commonly applied to randomized controlled trials (RCTs) in oncology. Nevertheless, RCTs with extension studies incorporating nonrandomized dropout require consideration of alternative adjustment methods. The current study used a recognized method and a novel method to adjust for treatment switching in relapsing–remitting multiple sclerosis (MS).
Methods
The Cladribine Tablets Treating Multiple Sclerosis Orally (CLARITY) RCT evaluated the efficacy of cladribine versus placebo over 96 weeks. Many (but not all) CLARITY participants enrolled in the 96-week CLARITY extension study; placebo-treated patients from CLARITY received cladribine (PP→LL), and cladribine-treated patients were re-randomized to placebo (LL→PP) or continued cladribine (LL→LL). End points were time to first qualifying relapse (FQR) and time to 3-month and 6-month confirmed disability progression (3mCDP, 6mCDP). We aimed to estimate the effectiveness of the LL→PP treatment strategy compared with a counterfactual (unobserved) PP→PP strategy. We applied the commonly used rank-preserving structural failure time model (RPSFTM) and a novel approach that combined propensity score matching (PSM) with inverse probability of censoring weights (IPCW).
Results
The RPSFTM resulted in LL→PP versus PP→PP hazard ratios (HRs) of 0.48 (95% confidence interval [CI] 0.36-0.62) for FQR, 0.62 (95% CI 0.46-0.84) for 3mCDP, and 0.62 (95% CI 0.44-0.88) for 6mCDP. The PSM+IPCW resulted in HRs of 0.47 (95% CI 0.38-0.63) for FQR, 0.61 (95% CI 0.43-0.86) for 3mCDP, and 0.63 (95% CI 0.40-0.87) for 6mCDP.
Conclusions
The PSM+IPCW HRs were consistent with those from the RPSFTM, suggesting that the results were not substantially biased by informative dropout, assuming that all relevant confounders were controlled for. There was no statistical evidence of a reduction in the cladribine treatment effect during the extension period.
Authors
Helen Bell Gorrod Nicholas R. Latimer Doris Damian Robert Hettle Gerard T. Harty Schiffon L. Wong