Use of Non-concurrent Common Control in Master Protocols in Oncology Trials: Report of an American Statistical Association Biopharmaceutical Section Open Forum Discussion
Rajeshwari Sridhara, Olga Marchenko, Qi Jiang, Richard Pazdur, Martin, Posch, Scott Berry, Marc Theoret, Yuan Li Shen, Thomas Gwise, Lorenzo Hess,, Andrew Raven, Khadija Rantell, Kit Roes, Richard Simon, Mary Redman, Yuan Ji,, Cindy Lu

TL;DR
This paper reports on a discussion about the use of non-concurrent control groups in oncology master protocols, highlighting the potential benefits and challenges, especially in rare diseases with recruitment difficulties.
Contribution
It provides insights from diverse stakeholders on the statistical considerations and practical justifications for employing non-concurrent controls in oncology trials.
Findings
Non-concurrent controls can increase power in detecting treatment effects.
Concerns exist about bias due to temporal confounders.
Justification for non-concurrent controls is stronger in rare disease trials.
Abstract
This article summarizes the discussions from the American Statistical Association (ASA) Biopharmaceutical (BIOP) Section Open Forum that took place on December 10, 2020 and was organized by the ASA BIOP Statistical Methods in Oncology Scientific Working Group, in coordination with the US FDA Oncology Center of Excellence. Diverse stakeholders including experts from international regulatory agencies, academicians, and representatives of the pharmaceutical industry engaged in a discussion on the use of non-concurrent control in Master Protocols for oncology trials. While the use of non-concurrent control with the concurrent control may increase the power of detecting the therapeutic difference between a treatment and the control, the panelists had diverse opinion on the statistical approaches for modeling non-concurrent and concurrent controls. Some were more concerned about the…
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