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FDA issues final guidance on adjusting for covariates in randomized clinical trials

Today, FDA issued the Adjusting for Covariates in Randomized Clinical Trials for Drugs and Biological Products Final Guidance for Industry. This final guidance describes the agency’s current recommendations regarding adjusting for covariates in the statistical analysis of randomized clinical trials in drug and biological product development programs.

Covariate adjustment refers to the use of information measured on a subject before the time of randomization (e.g., demographic factors, disease characteristics) for estimating and testing treatment effects between randomized groups. It is desirable to study a population in clinical trials that reflects the variability of the target population but doing so may make it harder to detect a treatment effect. Covariate adjustment allows for incorporation of prespecified prognostic factors, or factors that predict the likely outcome of a disease or ailment, in the statistical analysis and can result in narrower confidence intervals and a greater statistical power to detect treatment effects.

This guidance discusses general recommendations for performing covariate adjustment, selection of covariates, change from baseline analysis, performing covariate adjustment using linear models, and performing covariate adjusting using nonlinear models. It finalizes the draft guidance of the same title that FDA issued on May 21, 2021. Changes from the draft to the final guidance include updated and clarified recommendations on computing standard errors, stratified randomization, treatment by covariate interactions, and additional methods. 

Please review the Guidance Snapshot and listen to the corresponding Guidance Recap Podcast episode with Dr. Dan Rubin, a statistician in CDER’s Office of Biostatistics, for more information about the guidance.

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