Evidence map›Paper›PMID 20429873›Full record

ArticleCritical care (London, England)2010

Delta inflation: a bias in the design of randomized controlled trials in critical care medicine.

Scott K Aberegg, D Roxanne Richards, James M O'Brien

Abstract read
In one paragraph

Article in Critical care (London, England), 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 7 pooled it
–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

36 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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  3. Between-trial heterogeneity in ARDS research.Intensive care medicine · 2021
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  16. Interpreting frequentist hypothesis tests: insights from Bayesian inference.Canadian journal of anaesthesia = Journal canadien d'anesthesie · 2023
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  17. Article
  18. Elements of Statistical Power in Pediatric Critical Care Trials.Annals of the American Thoracic Society · 2023
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  19. Fooled by Significance Testing: An Analysis of the LOVIT Vitamin C Trial.The journal of extra-corporeal technology · 2022
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  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Scott K AbereggDepartment of Critical Care, Jordan Valley Medical Center, 3580 West 9000 South, West Jordan, Utah 84088, USA. scottaberegg@gmail.com
D Roxanne Richards
James M O'Brien

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMortality is the most widely accepted outcome measure in randomized controlled trials of therapies for critically ill adults, but most of these trials fail to show a statistically significant mortality benefit. The reasons for this are unknown.

methodsWe searched five high impact journals (Annals of Internal Medicine, British Medical Journal, JAMA, The Lancet, New England Journal of Medicine) for randomized controlled trials comparing mortality of therapies for critically ill adults over a ten year period. We abstracted data on the statistical design and results of these trials to compare the predicted delta (delta; the effect size of the therapy compared to control expressed as an absolute mortality reduction) to the observed delta to determine if there is a systematic overestimation of predicted delta that might explain the high prevalence of negative results in these trials.

resultsWe found 38 trials meeting our inclusion criteria. Only 5/38 (13.2%) of the trials provided justification for the predicted delta. The mean predicted delta among the 38 trials was 10.1% and the mean observed delta was 1.4% (P < 0.0001), resulting in a delta-gap of 8.7%. In only 2/38 (5.3%) of the trials did the observed delta exceed the predicted delta and only 7/38 (18.4%) of the trials demonstrated statistically significant results in the hypothesized direction; these trials had smaller delta-gaps than the remainder of the trials (delta-gap 0.9% versus 10.5%; P < 0.0001). For trials showing non-significant trends toward benefit greater than 3%, large increases in sample size (380% - 1100%) would be required if repeat trials use the observed delta from the index trial as the predicted delta for a follow-up study.

conclusionsInvestigators of therapies for critical illness systematically overestimate treatment effect size (delta) during the design of randomized controlled trials. This bias, which we refer to as "delta inflation", is a potential reason that these trials have a high rate of negative results."Absence of evidence is not evidence of absence."

Indexed as

BiasCritical CareEndpoint DeterminationHumansMortalityRandomized Controlled Trials as TopicResearch DesignReview Literature as Topic

Identifiers

PMID20429873
PMCPMC2887200

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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.