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A Statistical Method for Benefit-Risk Assessment in Clinical Trials
Yinuo Zhang1, Shein-Chung Chow1
1Duke University School of Medicine, Durham, North Carolina, USA.
Statistics in Medicine
|August 7, 2025
Summary
A new confidence ellipse approach enhances benefit-risk assessment (BRA) for clinical trials. This robust method offers visual and quantitative insights, improving regulatory decision-making for investigational treatments.
Area of Science:
- * Clinical trial methodology
- * Regulatory science
- * Biostatistics
Background:
- * Benefit-risk assessment (BRA) is vital for regulatory decisions on new treatments.
- * Existing BRA frameworks have limitations in handling clinical trial data uncertainties.
- * The FDA has issued guidance emphasizing the importance of BRA.
Purpose of the Study:
- * To develop a statistically robust confidence ellipse approach for BRA.
- * To introduce novel indices (Net Benefit Index, Relative Benefit Index, Success Rate Index) for comprehensive treatment evaluation.
- * To compare the confidence ellipse method with existing BRA techniques.
Main Methods:
- * Development of a confidence ellipse approach integrating safety and efficacy indices.
- * Introduction of three novel indices: NBI, RBI, and SRI.
- * Comparison via simulations against Global Benefit-Risk (GBR), MCDA, and SMAA.
Main Results:
- * The confidence ellipse method demonstrated robustness, especially with larger sample sizes.
- * Method sensitivity decreased with increasing sample sizes, indicating enhanced stability.
- * A hypothetical Phase 2 trial showed the method's practical application in nuanced BRA.
Conclusions:
- * The confidence ellipse method is a robust, adaptable, and interpretable tool for BRA.
- * It provides valuable visual and quantitative insights for clinical trial decision-making.
- * The approach effectively incorporates uncertainties and heterogeneities in trial data.
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