ABSTRACT
This article provides a summary of discussions from the American Statistical Association (ASA) Biopharmaceutical (BIOP) Section Open Forum organized by the ASA BIOP Statistical Methods in Oncology Scientific Working Group in coordination with the US FDA Oncology Center of Excellence and LUNGevity Foundation on January 14, 2021, and February 8, 2021. Diverse stakeholders including oncologists, patient advocates, experts from international regulatory agencies, academicians, and representatives of the pharmaceutical industry engaged in a discussion on how best to incorporate lessons learned during the COVID-19 pandemic into the design of future oncology trials. While recognizing that decentralized or hybrid cancer trials may increase variability associated with measurement error and potentially increase bias in treatment effect estimation, panel discussions highlighted the importance of flexibility for decreasing patient burden, which has the potential to increase access to and retention in cancer clinical trials and may broaden the representation of real-world patients in the trial setting. [ FROM AUTHOR] Copyright of Statistics in Biopharmaceutical Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Randomized controlled trials (RCTs) are the gold standard for evaluation of new medical products. However, RCTs may not always be ethical or feasible. In cases where the investigational product is available outside the trial (e.g., through accelerated approval), patients may fail to enroll in clinical trials or drop out early to take the investigational product. These challenges to enrolling or maintaining a concurrent control arm may compromise timely recruitment, retention, or compliance. This can threaten the study's integrity, including the validity of results. External control arms (ECAs) may be a promising augmentation to RCTs when encountered with challenges that threaten the feasibility and reliability of a randomized controlled clinical trial. Here, we propose the use of ECAs created from patient-level data from previously conducted clinical trials or real-world data in the same indication. Propensity score methods are used to balance observed disease characteristics and demographics in the previous clinical trial or real-world data with those of present-day trial participants assigned to receive the investigational product. These methods are explored in a case study in non-small cell lung cancer (NSCLC) derived from multiple previously conducted open label or blinded phase 2 and 3 multinational clinical trials initiated between 2004 and 2013. The case study indicated that when balanced for baseline characteristics, the overall survival estimates from the ECA were very similar to those of the target randomized control, based on Kaplan-Meier curves and hazard ratio and confidence interval estimates. This suggests that in the future, a randomized control may be able to be augmented by an ECA without compromising the understanding of the treatment effect, assuming sufficient knowledge, measurement, and availability of all or most of the important prognostic variables.