Efficient use of open label extension data to support additional evidence of efficacy and disease modification hypotheses

Abstract

AbstractBackgroundMany clinical trials have open label extension (OLE) phases in which all patients from the randomized controlled study go onto active treatment for some period of time. These OLEs provide the opportunity for placebo patients to have access to active treatment. Trial sponsors also want to get meaningful information from the OLE data.MethodWe evaluate the types of hypotheses that can be tested with OLE data in degenerative diseases and propose analyses aligned with these hypotheses. Challenges with OLE data are also enumerated and discussed. For these analyses, and for simplicity of examples, we are assuming that the randomized phase and the OLE phase are each 1 year in duration.Result6 key hypotheses can be addressed with OLE data. 1. Treatment effects differ during the randomized phase and the OLE, 2. Treatment groups differ at the end of the OLE, 3. The slope for placebo patients in the randomized phase differs from their slope during the OLE, 4. The slope over the entire duration of the randomized phase and the OLE phase differs between groups, 5. The slope of decline during the first 12 months of treatment combined across the original active patients and the placebo patients during the OLE phase differs from the placebo slope of decline during the original 12 month randomized phase. 6. The slope of the original placebo group differs from the original active group during the OLE phase. If a significant treatment effect is seen during the randomized phase, then hypotheses 2 and 6 can demonstrate disease modification in a pseudo staggered start analysis if they demonstrate that the treatment groups also differ at the end of the OLE phase, and are not converging during the OLE. Challenges with OLE analyses include high dropout rates, differential dropout between groups, ceiling and floor effects resulting in differing slopes (nonlinearity) during the randomized and OLE phases.ConclusionOLE phases can add to the weight of evidence for efficacy in clinical trials and can identify disease modifying effects as long as issues such as dropout and non‐linearity are accounted for.