Evidence map›Paper›PMID 29282120›Full record

ArticleBMC research notes2017

Can testing clinical significance reduce false positive rates in randomized controlled trials? A snap review.

Theophile Bigirumurame, Adetayo S Kasim

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Theophile BigirumurameDurham University, University boulevard, Stockton-on-Tees, TS17 6BH, UK. theophile.bigirumurame@durham.ac.uk.ORCID http://orcid.org/0000-0003-2387-4918
Adetayo S KasimDurham University, University boulevard, Stockton-on-Tees, TS17 6BH, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

BiasModels, StatisticalData Interpretation, StatisticalHumansRandomized Controlled Trials as TopicFalse discoveryMinimum clinically important differenceNull hypothesis testingSample size calculation

Identifiers

PMID29282120
PMCPMC5745896

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.