An IV for the RCT: using instrumental variables to adjust for treatment contamination in randomised controlled trials

Jeremy B Sussman, Rodney A Hayward, Jeremy B Sussman, Rodney A Hayward

Abstract

Although the randomised controlled trial is the "gold standard" for studying the efficacy and safety of medical treatments, it is not necessarily free from bias. When patients do not follow the protocol for their assigned treatment, the resultant "treatment contamination" can produce misleading findings. The methods used historically to deal with this problem, the "as treated" and "per protocol" analysis techniques, are flawed and inaccurate. Intention to treat analysis is the solution most often used to analyse randomised controlled trials, but this approach ignores this issue of treatment contamination. Intention to treat analysis estimates the effect of recommending a treatment to study participants, not the effect of the treatment on those study participants who actually received it. In this article, we describe a simple yet rarely used analytical technique, the "contamination adjusted intention to treat analysis," which complements the intention to treat approach by producing a better estimate of the benefits and harms of receiving a treatment. This method uses the statistical technique of instrumental variable analysis to address contamination. We discuss the strengths and limitations of the current methods of addressing treatment contamination and the contamination adjusted intention to treat technique, provide examples of effective uses, and discuss how using estimates generated by contamination adjusted intention to treat analysis can improve clinical decision making and patient care.

Conflict of interest statement

Competing interests: Both authors have completed the Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: (1) No financial support for the submitted work from anyone other than their employer; (2) No financial relationships with commercial entities that might have an interest in the submitted work; (3) No spouses, partners, or children with relationships with commercial entities that might have an interest in the submitted work; (4) No non-financial interests that may be relevant to the submitted work.

Figures

https://www.ncbi.nlm.nih.gov/pmc/articles/instance/4788341/bin/susj686048.f1_default.jpg
Fig 1 Analysis of randomised controlled trials. In per protocol and as treated analyses (A), random assignment is ignored, creating less reliable results. In intention to treat analyses (B), only the effect of randomisation is assessed, not the effect of receiving the intervention. The two stage contamination adjusted intention to treat approach (C) uses assignment and intervention received to calculate the effect of receiving the treatment

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Source: PubMed

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