Design and evaluation of an external control arm using prior clinical trials and real-world data - Ventz, Steffen (Clin Cancer Res, 2019)
IMPORTANCE: The use of existing data (real world data or prior trials) to design and analyze clinical studies has the potential to accelerate drug development processes and can contribute to rigorous examination of new treatments. OBJECTIVE: We discuss designs and interpretable metrics of bias and statistical efficiency of “externally controlled” trials (ECTs) and compare ECTs performance to randomized and single arm designs. SETTING: We specify an ECT design that leverages information from real world data (RWD) and prior clinical trials, to reduce bias associated with inter-study variations of the enrolled populations. We then used a collection of clinical studies in glioblastoma (GBM) and RWD from patients treated with the current standard of care to evaluate ECTs. Validation is based on a “leave one out” scheme, with iterative selection of a single arm from one of the studies, for which we estimate treatment effects using the remaining studies as external control. This produces interpretable and robust estimates on ECTs bias and type I errors. RESULTS: We developed a model-free approach to evaluate ECTs based on collections of clinical trials and RWD. For GBM we verified that inflated false positive error rates of standard single-arm trials can be considerably reduced (up to 30%) by using external control data. CONCLUSIONS: The use of ECT designs in GBM, with adjustments for the clinical profiles of the enrolled patients, should be preferred to single arm studies with fixed efficacy thresholds extracted from published results on the current standard of care.