Impervious to Randomness: Confounding and Selection Biases in Randomized Clinical Trials
- 13 September 2021
- journal article
- research article
- Published by Taylor & Francis Ltd in Cancer Investigation
- Vol. 39 (10), 783-788
- https://doi.org/10.1080/07357907.2021.1974030
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
Funding Information
- American Society of Clinical Oncology
- KCCure
- MD Anderson Khalifa Scholar Award
- Andrew Sabin Family Foundation Fellowship
- MD Anderson Physician-Scientist Award
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