Targeting a hypothetical estimand based on adherence with the parametric g-formula: A post hoc secondary analysis of the MET-PREVENT randomised controlled trial
Abstract
Abstract Background We conducted a post hoc secondary analysis of the MET-PREVENT randomised placebo-controlled trial to target a hypothetical estimand – the mean difference in physical performance, as measured by the 4-metre walk speed at four months after randomisation, between treatment arms – under the hypothetical scenario that all participants adhered to assigned treatment. Methods We viewed the targeting of this hypothetical estimand as a type of causal mediation problem, where randomisation is a binary exposure, adherence is a binary mediator, there is an exposure-mediator interaction, and mediator-outcome confounders that are caused by the exposure (e.g., gastrointestinal symptoms) are present. We used the parametric g-formula to estimate the average controlled direct effect (CDE) of metformin (versus placebo) on 4-metre walk speed, which is interpreted as the average treatment effect under the hypothetical scenario that all trial participants adhered to assigned treatment. Variables identified as confounders were informed by a literature review and discussions with an expert; assumptions about the causal structure were represented in a directed acyclic graph. We applied a probabilistic bias analysis (PBA) to understand the potential for bias assuming adherence had been misclassified; observed adherence based on returned tablet count may be an inaccurate version of “true adherence” based on actual consumption. Results Our sample size was 70 trial participants (34…
How strong is the evidence?
Evidence Hub reads this as a secondary / pooled analysis, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 70 participants or records.
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