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Defining and Identifying Per-protocol Effects in Randomized Trials.
Jacqueline E Rudolph1, Ashley I Naimi1, Daniel J Westreich2
1From the Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA.
Epidemiology (Cambridge, Mass.)
|August 3, 2020
Summary
Researchers can estimate per-protocol effects, comparing outcomes based on treatment adherence, not just assignment. This study defines per-protocol effects and discusses their identification in trials with noncompliance.
Area of Science:
- Causal inference in clinical trials
- Epidemiology
- Biostatistics
Background:
- Noncompliance to assigned treatment is common in clinical trials.
- Estimating treatment effects under noncompliance requires careful consideration of causal definitions.
- Per-protocol effect estimation is of interest when adherence to a treatment protocol is crucial.
Purpose of the Study:
- To provide a general counterfactual definition of a per-protocol effect.
- To illustrate substantive and methodologic examples of per-protocol effects.
- To clarify that per-protocol effects extend beyond simple comparisons of always-treated groups.
Main Methods:
- Development of a general counterfactual framework for per-protocol effects.
- Discussion of identifiability conditions for causal per-protocol effects.
- Identification of potential violations of these conditions in practice.
Main Results:
- A formal definition of per-protocol effects is presented.
- Examples demonstrate the broader applicability of per-protocol effect estimation.
- Conditions for the causal identification of per-protocol effects are outlined.
Conclusions:
- Per-protocol effects offer a valuable tool for analyzing trials with noncompliance.
- Understanding the counterfactual definition is key to accurate estimation.
- Awareness of identifiability conditions and their violations is crucial for valid causal inference.
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