Trial reportTrials2016
Advantages of Bayesian monitoring methods in deciding whether and when to stop a clinical trial: an example of a neonatal cooling trial.
Trial report in Trials, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01192776 (Optimizing Cooling Strategies at < 6 Hours of Age for Neonatal Hypoxic-Ischemic Encephalopathy), which is not on this map. Cited by 9 papers, 2 of them syntheses that pooled it.
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.
Optimizing Cooling Strategies at < 6 Hours of Age for Neonatal Hypoxic-Ischemic Encephalopathy
Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Developing a Bayesian hierarchical model for a prospective individual patient data meta-analysis with continuous monitoring.BMC medical research methodology · 2023Pooled it
- Prospective individual patient data meta-analysis: Evaluating convalescent plasma for COVID-19.Statistics in medicine · 2021Pooled it
- Hospital Consultation From Outpatient Clinicians for Medically Complex Children: A Randomized Clinical Trial.JAMA pediatrics · 2021Trial
- Trial
- Translational Potential of Stem Cell-based Therapies in the Treatment of Neonatal Hypoxic-ischemic Brain Injury.Stem cell reviews and reports · 2025Review
- Does prefusion F protein-based respiratory syncytial virus immunization in pregnancy safely promote transplacental transfer of neutralizing antibodies?Journal of perinatology : official journal of the California Perinatal Association · 2024Article
- Overview of the neonatal research network: History, contributions, challenges, and future.Seminars in perinatology · 2022Review
- Automated cot-side tracking of functional brain age in preterm infants.Annals of clinical and translational neurology · 2020Article
- Mining multi-site clinical data to develop machine learning MRI biomarkers: application to neonatal hypoxic ischemic encephalopathy.Journal of translational medicine · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundDecisions to stop randomized trials are often based on traditional P value thresholds and are often unconvincing to clinicians. To familiarize clinical investigators with the application and advantages of Bayesian monitoring methods, we illustrate the steps of Bayesian interim analysis using a recent major trial that was stopped based on frequentist analysis of safety and futility.
methodsWe conducted Bayesian reanalysis of a factorial trial in newborn infants with hypoxic-ischemic encephalopathy that was designed to investigate whether outcomes would be improved by deeper (32 °C) or longer cooling (120 h), as compared with those achieved by standard whole body cooling (33.5 °C for 72 h). Using prior trial data, we developed neutral and enthusiastic prior probabilities for the effect on predischarge mortality, defined stopping guidelines for a clinically meaningful effect, and derived posterior probabilities for predischarge mortality.
resultsBayesian relative risk estimates for predischarge mortality were closer to 1.0 than were frequentist estimates. Posterior probabilities suggested increased predischarge mortality (relative risk > 1.0) for the three intervention groups; two crossed the Bayesian futility threshold.
conclusionsBayesian analysis incorporating previous trial results and different pre-existing opinions can help interpret accruing data and facilitate informed stopping decisions that are likely to be meaningful and convincing to clinicians, meta-analysts, and guideline developers.
trial registrationClinicalTrials.gov NCT01192776 . Registered on 31 August 2010.
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Registered trials
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.