ArticleBMC research notes2017
Can testing clinical significance reduce false positive rates in randomized controlled trials? A snap review.
Article in BMC research notes, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe use of minimum clinically important difference in the hypothesis formulation for superiority trials is similar in principle to the concept of non-inferiority or equivalence trial. However, most clinical trials are analysed testing zero clinical difference. Since the minimum clinically important difference is pre-defined for power calculation, it is important to incorporate it in both the hypothesis testing and the interpretation of findings from clinical trials.
resultsWe reviewed a set of 50 publications (25 with binary outcome, and 25 with survival time outcome). 20% of the 50 published trials that were statistically significant, were also clinically significant based on the minimum clinically important risk differences (or hazard ratio) used for their power calculations. This snap review seems to suggest that most published trials with statistically significant results were less likely to be clinically significant, which may partly explain the high false positive findings associated with findings from superiority trials. Furthermore, none of the reviewed publications explicitly used minimum clinically important difference in the interpretation of their findings. However, a systematic review is needed to critically appraise the impact of the current practice on false positive rate in published trials with significant findings.
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