| Bayesian meta-analyses for comparative effectiveness and informing coverage decisions. | |
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MedLine Citation:
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PMID: 20473185 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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BACKGROUND: Evidence-based medicine is increasingly expected in health care decision-making. The Centers for Medicare and Medicaid have initiated efforts to understand the applicability of Bayesian techniques for synthesizing evidence. As a case study, a Bayesian analysis of clinical trials of implantable cardioverter defibrillators was undertaken using patient-level data not typically available for analysis. PURPOSE: Conduct Bayesian meta-analyses of the defibrillator trials using published results to demonstrate a Bayesian approach useful to policy makers. DATA SOURCES, STUDY SELECTION, DATA EXTRACTION: We reconsidered trials in a 2007 systematic review by Ezekowitz et al (Ann Intern Med. 2007;147:251-262) and extracted information from the original published articles. Employing a Bayesian hierarchical approach, we developed a base model and 2 variants, and modeled hazard ratios separately within each year of follow-up. We considered sequential meta-analyses over time and found the predictive distribution of the results of the next trial, given its sample size. DATA SYNTHESIS: For the most robust of 3 models, the probability that the mean defibrillator effect (in the population of trials) is beneficial is greater than 0.999. In that model, about 5% of trials in the population of trials would have a detrimental effect. Despite the moderate amount of heterogeneity across the trials, there was stability of conclusions after the first 3 of the 12 total trials had been conducted. This stability enabled reasonable predictions for the results of future trials. LIMITATIONS: Inability to assess treatment effects within subsets of patients. CONCLUSIONS: Bayesian meta-analyses based on literature surveys can effectively inform coverage decisions. Bayesian modeling for endpoints such as mortality can elucidate treatment effects over time. The Bayesian approach used in a sequential manner over time can predict results and help assess the utility of future clinical trials. |
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Authors:
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Scott M Berry; K Jack Ishak; Bryan R Luce; Donald A Berry |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Medical care Volume: 48 ISSN: 1537-1948 ISO Abbreviation: Med Care Publication Date: 2010 Jun |
Date Detail:
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Created Date: 2010-05-20 Completed Date: 2010-06-18 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0230027 Medline TA: Med Care Country: United States |
Other Details:
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Languages: eng Pagination: S137-44 Citation Subset: IM |
Affiliation:
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Berry Consultants, College Station, TX 77845, USA. scott@berryconsultants.com |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Bayes Theorem* Centers for Medicare and Medicaid Services (U.S.) / organization & administration* Clinical Trials as Topic Comparative Effectiveness Research / methods* Defibrillators, Implantable Humans Insurance Coverage / organization & administration* Meta-Analysis as Topic* United States |
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