Stratification of randomization is not required for a pre-specified subgroup analysis

Area of Science:

• Clinical Trials Methodology
• Biostatistics
• Pharmacogenomics

Background:

• Conflicting recommendations exist regarding the necessity of stratified randomization for subgroup analyses in clinical trials.
• Subgroup analyses are crucial for demonstrating drug efficacy, particularly for companion diagnostic development.

Purpose of the Study:

• To evaluate the validity of subgroup analyses using typical randomization methods without subgroup stratification.
• To assess the impact of unstratified randomization on treatment balance and covariate distribution within subgroups.

Main Methods:

• Analysis of typical randomization methods to determine patient fractions within subgroups.
• Examination of covariate balance between treatment arms within subgroups.
• Application of analysis of variance to assess treatment effect estimators.

Main Results:

• The fraction of patients receiving experimental treatment in subgroups closely matches the target fraction.
• Covariate values are balanced on average between treatment arms within subgroups.
• Variance in covariate imbalance is only slightly increased compared to stratified randomization.
• Least-squares treatment effect estimators within subgroups are unbiased regardless of stratification.

Conclusions:

• Stratified randomization is not a prerequisite for valid subgroup analyses.
• Current randomization methods adequately support subgroup analyses, ensuring treatment balance and unbiased estimates.
• Requiring subgroup stratification poses an unnecessary barrier to innovation in personalized healthcare and drug development.