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Enough is enough: does trial sequential analysis tell us when we don't need to do any more studies?

“The answer is 17 years, what is the question”? So begins the title of a 2011 review by Morris et al. which explored the natural lag within health research translation [1]. These 17 years between the research phase and practice implementation of new health interventions seems to be consistent across analyses of knowledge translation [2]. Such a delay before patients routinely benefit from the new knowledge that we create seems outrageous and yet the entire field of implementation science is dedicated to strategies for improving that timeline. However, what if that intervention is not benefiting patients the way we think? The refinement of practice after those 17 years sometimes feels like the process of a lifetime and presents the difficult challenge of finding the truth in the contradictory evidence that we so often find. In this issue, Desai at al. have pushed forward the refinement of pain management for abdominal surgery with an extremely well-designed systemic review and meta-analysis [3]. There is good reason that, since hierarchies of evidence became a core foundation of evidence-based practice [4], meta-analysis has sat at the apex of the pyramid. The ability of this analytic strategy to bring together disparate small trials into digestible evidence is both intuitively and statistically attractive. Presumably, this explains the widespread popularity of the approach; and it is attractive indeed. In the last 10 years, a cursory literature search reveals at least 28 meta-analyses examining the effectiveness of the transversus abdominis plane (TAP) block alone. However, what if our most trustworthy analysis technique is not benefiting us with the answers that we think? The optimisation of statistical approaches also feels like the process of a lifetime and as Shakespeare wrote in Hamlet, “there’s the rub”.