ArticleCritical care (London, England)2010
Delta inflation: a bias in the design of randomized controlled trials in critical care medicine.
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.
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Who cites it
36 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Accuracy of Event Rate and Effect Size Estimation in Major Cardiovascular Trials: A Systematic Review.JAMA network open · 2024Pooled it
- Are treatment effect assumptions in orthodontic studies overoptimistic?European journal of orthodontics · 2021Pooled it
- Between-trial heterogeneity in ARDS research.Intensive care medicine · 2021Pooled it
- Measuring and Analyzing Length of Stay in Critical Care Trials.Medical care · 2019Pooled it
- Effect sizes in ongoing randomized controlled critical care trials.Critical care (London, England) · 2017Pooled it
- Pooled it
- The acute management of trauma hemorrhage: a systematic review of randomized controlled trials.Critical care (London, England) · 2011Pooled it
- Use of days alive without life support and similar count outcomes in randomised clinical trials - an overview and comparison of methodological choices and analysis methods.BMC medical research methodology · 2023Trial
- Metabolomic basis for response to high dose vitamin D in critical illness.Clinical nutrition (Edinburgh, Scotland) · 2021Trial
- Covariate adjustment increased power in randomized controlled trials: an example in traumatic brain injury.Journal of clinical epidemiology · 2012Trial
- The added value of ordinal analysis in clinical trials: an example in traumatic brain injury.Critical care (London, England) · 2011Trial
- Simulation study of frailty as a baseline confounder: the need to improve reporting intensive care trials.Critical care (London, England) · 2026Review
- Effect size and event rate estimation in neurocritical care randomised clinical trials: a protocol for a systematic review.BMJ open · 2025Article
- Trial Sequential Analysis for dichotomous outcomes - a practical guide for systematic review protocols.BMC medical research methodology · 2025Article
- Statistical Power in Musculoskeletal Research: A Meta-Review of 266 Randomised Controlled Trials.Sports medicine - open · 2025Review
- Interpreting frequentist hypothesis tests: insights from Bayesian inference.Canadian journal of anaesthesia = Journal canadien d'anesthesie · 2023Article
- Observed intervention effects for mortality in randomised clinical trials: a methodological study protocol.BMJ open · 2023Article
- Elements of Statistical Power in Pediatric Critical Care Trials.Annals of the American Thoracic Society · 2023Article
- Fooled by Significance Testing: An Analysis of the LOVIT Vitamin C Trial.The journal of extra-corporeal technology · 2022Article
- Causal inference for planning randomised critical care trials: Protocol for a scoping review.Acta anaesthesiologica Scandinavica · 2022Article
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3 authors.
Funding
No grant is acknowledged in the PubMed record.
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."
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