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Advantages of Bayesian monitoring methods in deciding whether and when to stop a clinical trial: an example of a neonatal cooling trial. Trials 2016 07 22;17(1):335

Date

07/28/2016

Pubmed ID

27450203

Pubmed Central ID

PMC4957277

DOI

10.1186/s13063-016-1480-4

Scopus ID

2-s2.0-84979021974   6 Citations

Abstract

BACKGROUND: Decisions 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.

METHODS: We 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.

RESULTS: Bayesian 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.

CONCLUSIONS: Bayesian 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 REGISTRATION: ClinicalTrials.gov NCT01192776 . Registered on 31 August 2010.

Author List

Pedroza C, Tyson JE, Das A, Laptook A, Bell EF, Shankaran S, Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network

Author

Jeffrey L. Segar MD Professor in the Pediatrics department at Medical College of Wisconsin




MESH terms used to index this publication - Major topics in bold

Age Factors
Bayes Theorem
Body Temperature Regulation
Clinical Protocols
Early Termination of Clinical Trials
Hospital Mortality
Humans
Hypothermia, Induced
Hypoxia-Ischemia, Brain
Infant
Infant Mortality
Infant, Newborn
Medical Futility
Research Design
Risk Assessment
Risk Factors
Time Factors
Treatment Outcome
United States
jenkins-FCD Prod-478 d1509cf07a111124a2d122fd3df854cc0b993c00