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Published on: October 23, 2020
Semi-parametric regression models for cost-effectiveness analysis: improving the efficiency of estimation from
Eleanor M Pullenayegum1, Andrew R Willan
1Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, Canada.
Statistics in Medicine
|February 20, 2007
Summary
This study introduces new statistical methods for cost-effectiveness analysis, improving precision in estimating treatment differences. These efficient estimators significantly reduce variance in cost contrasts, aiding clinical trial interpretation.
Area of Science:
- Health Economics
- Biostatistics
- Clinical Trial Analysis
Background:
- Cost-effectiveness analysis (CEA) requires precise estimates of treatment differences in cost and effectiveness.
- Handling censored data in CEA is crucial, with inverse-probability weighting (IPW) being a common method.
- IPW, while versatile for regression models, may lack statistical efficiency.
Purpose of the Study:
- To derive semi-parametrically efficient estimators for regression models of mean cost and effectiveness (quality-adjusted survival time, survival time).
- To evaluate the performance of these new estimators compared to existing methods, particularly IPW.
- To provide practical guidance on selecting appropriate estimators for CEA.
Main Methods:
- Development of semi-parametrically efficient estimators based on existing efficiency theory.
- Application of these estimators to regression models for mean cost, mean quality-adjusted survival time, and mean survival time.
- A simulation study to assess the performance of the new estimators.
- Application to data from the EVALUATE trial.
Main Results:
- The new semi-parametrically efficient estimators were derived.
- Simulation studies indicated favorable performance of the new estimators.
- Application to the EVALUATE trial data showed the new estimators halved the variance of the estimated treatment contrast for cost.
Conclusions:
- The developed semi-parametrically efficient estimators offer improved precision for cost-effectiveness analyses.
- These estimators provide a valuable alternative to IPW, particularly when efficiency is a concern.
- The findings offer practical recommendations for choosing estimators in clinical trial cost-effectiveness studies.
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