A Bayesian Meta-analysis Method for Estimating Risk Difference of Rare Events.
J Biopharm Stat
; 28(3): 550-561, 2018.
Article
em En
| MEDLINE
| ID: mdl-29053049
ABSTRACT
Bayesian meta-analysis has been more frequently utilized for synthesizing safety and efficacy information to support landmark decision-making due to its flexibility of incorporating prior information and availability of computing software. However, when the outcome is binary and the events are rare, where event counts can be zero, conventional meta-analysis methods including Bayesian methods may not work well. Several methods have been proposed to tackle this issue but the prior knowledge of event rate was not utilized to increase precision of risk difference estimates. To better estimate risk differences, we propose a new Bayesian method, Beta prior BInomial model for Risk Differences (B-BIRD), which takes into account the prior information of rare events. B-BIRD is illustrated using a real data set of 48 clinical trials about a type 2 diabetes drug. In simulation studies, it performs well in low event rate settings.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Metanálise como Assunto
/
Ensaios Clínicos como Assunto
Tipo de estudo:
Etiology_studies
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Prognostic_studies
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Risk_factors_studies
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Systematic_reviews
Limite:
Humans
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article