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Bayesian Analysis of Time-To-Event Data in a Cluster-Randomized Trial: Major Outcomes With Personalized Dialysate
Yongdong Ouyang1,2,3, Bin Luo4,5, Stephanie N Dixon4,5,6
1Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada.
Personalized cooler dialysate in hemodialysis did not show significant cardiovascular benefits compared to standard temperature. Bayesian analysis confirmed no substantial difference in reducing cardiovascular deaths or hospitalizations in the MyTEMP trial.
Area of Science:
- Nephrology
- Cardiovascular Medicine
- Clinical Trials
Background:
- The MyTEMP trial investigated personalized cooler dialysate versus standard temperature dialysate for cardiovascular benefits in hemodialysis patients.
- Maintenance hemodialysis patients in Ontario, Canada, were included in this cluster-randomized trial.
Purpose of the Study:
- To determine if a center-wide policy of personalized cooler dialysate is superior to standard 36.5°C dialysate.
- To reduce the risk of a composite outcome including cardiovascular deaths or hospitalizations.
Main Methods:
- Bayesian cause-specific parametric Weibull methods were used for survival time analysis.
- Six pre-defined reference priors were applied to model the treatment effect (hazard ratio).
- Posterior means, percentiles, and 96% credible intervals were reported for treatment effects.
Main Results:
- Bayesian analysis consistently showed no substantial difference between personalized cooler dialysate and standard temperature.
- The hazard ratio posterior distribution was concentrated between 0.95 and 1.05, indicating similar outcomes.
- Results were consistent across various prior distributions, from skeptical to enthusiastic.
Conclusions:
- Implementing personalized cooler dialysate as a center-wide policy is unlikely to provide meaningful cardiovascular benefits.
- The study suggests no significant reduction in cardiovascular deaths or hospitalizations with cooler dialysate.
- Formal elicitation of prior expert opinion is recommended for future Bayesian trials.
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