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A Bayesian approach to sequential meta-analysis.
Spence, Graeme T; Steinsaltz, David; Fanshawe, Thomas R.
Afiliação
  • Spence GT; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, U.K.
  • Steinsaltz D; Department of Statistics, University of Oxford, Oxford, U.K.
  • Fanshawe TR; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, U.K.
Stat Med ; 35(29): 5356-5375, 2016 12 20.
Article em En | MEDLINE | ID: mdl-27481499
As evidence accumulates within a meta-analysis, it is desirable to determine when the results could be considered conclusive to guide systematic review updates and future trial designs. Adapting sequential testing methodology from clinical trials for application to pooled meta-analytic effect size estimates appears well suited for this objective. In this paper, we describe a Bayesian sequential meta-analysis method, in which an informative heterogeneity prior is employed and stopping rule criteria are applied directly to the posterior distribution for the treatment effect parameter. Using simulation studies, we examine how well this approach performs under different parameter combinations by monitoring the proportion of sequential meta-analyses that reach incorrect conclusions (to yield error rates), the number of studies required to reach conclusion, and the resulting parameter estimates. By adjusting the stopping rule thresholds, the overall error rates can be controlled within the target levels and are no higher than those of alternative frequentist and semi-Bayes methods for the majority of the simulation scenarios. To illustrate the potential application of this method, we consider two contrasting meta-analyses using data from the Cochrane Library and compare the results of employing different sequential methods while examining the effect of the heterogeneity prior in the proposed Bayesian approach. Copyright © 2016 John Wiley & Sons, Ltd.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Metanálise como Assunto / Teorema de Bayes Tipo de estudo: Prognostic_studies / Systematic_reviews Limite: Humans Idioma: En Revista: Stat Med Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Metanálise como Assunto / Teorema de Bayes Tipo de estudo: Prognostic_studies / Systematic_reviews Limite: Humans Idioma: En Revista: Stat Med Ano de publicação: 2016 Tipo de documento: Article