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Beyond the intention-to-treat in comparative effectiveness research
Miguel A Hernán1, Sonia Hernández-Díaz
1Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA. miguel_hernan@post.harvard.edu
Clinical Trials (London, England)
|September 28, 2011
Summary
Intention-to-treat (ITT) analysis in randomized trials may not reflect true treatment effectiveness due to adherence issues. Alternative methods like inverse probability weighting are recommended for accurate comparative effectiveness research.
Area of Science:
- Clinical Trials Methodology
- Biostatistics
- Comparative Effectiveness Research
Background:
- Intention-to-treat (ITT) analysis is a standard approach in randomized clinical trials (RCTs).
- However, ITT has limitations, particularly in estimating true treatment effects.
- This review focuses on issues relevant to comparative effectiveness research.
Purpose of the Study:
- To critically evaluate the limitations of intention-to-treat analyses.
- To examine the shortcomings of 'as treated' and 'per protocol' analyses as commonly implemented.
- To emphasize problems particularly relevant for comparative effectiveness research.
Main Methods:
- Review of existing literature on analytical approaches in RCTs.
- Analysis of bias introduced by nonadherence and loss to follow-up.
- Discussion of advanced statistical methods like inverse probability weighting, g-estimation, and instrumental variable estimation.
Main Results:
- ITT analyses can underestimate treatment effects in placebo-controlled trials, impacting safety and noninferiority assessments.
- In trials with active comparators, ITT may overestimate effects if adherence differs between groups.
- Standard ITT does not guarantee estimation of clinical treatment effectiveness.
- Advanced methods can mitigate bias from nonadherence and loss to follow-up in 'as treated' and 'per protocol' analyses.
Conclusions:
- Current analytical methods for RCTs often rely on untestable assumptions.
- Substantial nonadherence or loss to follow-up necessitates alternative analytical strategies.
- Recommend using ITT for assigned treatment effects and adjusted 'as treated'/'per protocol' analyses for treatment effects in RCTs.
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