Impervious to Randomness: Confounding and Selection Biases in Randomized Clinical Trials

Abstract

The random allocation of therapies in randomized clinical trials is a powerful tool that removes all confounding biases that can affect treatment assignment. However, confounders influencing mediators of the treatment effect are unaffected by randomization and should be considered during trial design and statistical modeling.

Examples of such mediators include biomarkers predictive of response to targeted therapies in oncology. Patient selection for such biomarkers is prudent in clinical trials. Conversely, prognostic information on outcome heterogeneity can be derived from observational datasets that include more representative populations. The fusion of experimental and observational data can then allow patient-specific inferences.

Keywords:

• Confounding
• directed acyclic graphs
• mediation analysis
• representativeness
• selection bias

Acknowledgements

The author would like to thank Dr. Bora Lim (Associate Professor, Baylor College of Medicine, Houston, TX, USA) for helpful conversations, as well as Sarah Townsend (Senior Technical Writer; Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA) for editorial assistance.

Declaration of interest

Pavlos Msaouel has received honoraria for service on a scientific advisory board for Mirati Therapeutics and BMS, non-branded educational programs supported by Exelixis and Pfizer, and research funding for clinical trials from Takeda, BMS, Mirati Therapeutics, Gateway for Cancer Research, and UT MD Anderson Cancer Center, all outside of the submitted work. The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the article.

Additional information

Funding

Pavlos Msaouel is supported by a Career Development Award by the American Society of Clinical Oncology, a Research Award by KCCure, the MD Anderson Khalifa Scholar Award, the Andrew Sabin Family Foundation Fellowship, and the MD Anderson Physician-Scientist Award.