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Graphing and reporting heterogeneous treatment effects through reference classes.

James A Watson1,2, Chris C Holmes3,4

  • 1Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, 10400, Thailand. jwatowatson@gmail.com.

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Summary
This summary is machine-generated.

This study introduces a two-stage method to explore heterogeneous treatment effects in randomized controlled trials (RCTs). This approach uses risk scores to analyze treatment effectiveness across different patient risk groups, improving precision medicine insights.

Keywords:
Heterogeneous treatment effectsPrognostic risk scoreRandomised controlled trialsReference class forecasting

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Area of Science:

  • Clinical Trials Methodology
  • Precision Medicine
  • Biostatistics

Background:

  • Heterogeneous treatment effects (HTE) are crucial for precision medicine in randomized controlled trials (RCTs).
  • Estimating HTE often involves complex predictive models prone to overfitting and multiple testing issues.
  • Existing methods may require outcome transformation, complicating interpretation on the original scale.

Purpose of the Study:

  • To present a novel two-stage approach for exploring HTE in RCTs.
  • To bypass interaction searches and multiple testing by using risk scores.
  • To enable HTE exploration on the original outcome scale.

Main Methods:

  • A two-stage approach using reference classes derived from baseline covariates.
  • Stage 1: Estimate a risk score to capture outcome heterogeneity.
  • Stage 2: Explore HTE using reweighting schemes along the risk score axis.

Main Results:

  • The approach was illustrated using a large trial in severe falciparum malaria.
  • Demonstrated that treatment effect (absolute mortality risk reduction) increased in higher-risk strata.
  • The method effectively explores HTE on the original outcome scale.

Conclusions:

  • 'Local' and 'tilting' reweighting schemes based on baseline risk ranking are effective.
  • This provides a generalizable method for exploring, graphing, and reporting HTE in RCTs.
  • Enhances the utility of RCTs for personalized treatment strategies.