Abstract

Masking (or blinding) of treatment assignment is routinely implemented in classical randomized clinical trials (RCTs) to isolate the effect of the intervention itself and to minimize the potential for bias that could occur with traditional trials. Such biases could be introduced with the conduct, assessment of endpoints, management of conditions, analysis, and reporting when the treatment assignments are known. However, masking of treatments is not only complex but it hinders how generalizable the findings are to the "real world" clinical setting. Pragmatic RCTs (pRCTs) are intended to evaluate the effects of interventions within routine medical care, and as such, do not typically mask treatment groups; moreover, pRCTs assess comparators that are available in routine medical practice, not masked placebos. Whether pRCTs should be masked if intended for regulatory or other purposes has recently been questioned. The literature on pRCTs, while extensive, does not address how much actual benefit is gained from masking outcomes and how masking may affect the "real world" nature of a study. Here, we propose an approach to evaluate sources of bias, describe stakeholders in the conduct of pRCTs who are most likely affected, and offer a framework for considering how masking may be implemented effectively while maintaining generalizability.

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