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Characterizing Treatment Effect Heterogeneity Using Real-World Data
1Department of Biostatistics, Epidemiology and Informatics, Center for Real-World Effectiveness and Safety of Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Clinical Pharmacology and Therapeutics
|March 6, 2025
Summary
Understanding heterogeneity of treatment effects (HTE) is crucial for personalized medicine. This review explores methods like subgroup analysis, disease risk scores, and effect modeling using real-world data (RWD) to identify why drugs vary in effectiveness across patients.
Area of Science:
- Pharmacoepidemiology
- Real-world data analysis
- Personalized medicine
Background:
- Heterogeneity of treatment effects (HTE) explains differential medication efficacy across patient populations.
- Real-world data (RWD) offers advantages over clinical trials for studying HTE due to larger, diverse populations.
- Characterizing HTE is fundamental for optimizing pharmacotherapy.
Purpose of the Study:
- To review and compare state-of-the-art methods for studying HTE using RWD.
- To define HTE and discuss its measurement.
- To examine the strengths and limitations of subgroup analysis, disease risk score (DRS) methods, and effect modeling.
Main Methods:
- Review of leading methodologies for HTE analysis in pharmacoepidemiology.
- Comparative analysis of subgroup analysis, DRS methods, and effect modeling.
- Discussion of HTE measurement and characterization using RWD.
Main Results:
- Subgroup analysis offers transparency but struggles with multiple effect modifiers.
- DRS methods summarize risk but may obscure mechanistic insights.
- Effect modeling allows precise HTE prediction but faces challenges in model misspecification.
Conclusions:
- Each HTE study method (subgroup analysis, DRS, effect modeling) has distinct advantages and limitations.
- Understanding these tradeoffs is essential for selecting appropriate methods when using RWD.
- Accurate HTE characterization using RWD is vital for advancing personalized treatment strategies and improving patient outcomes.
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