A multivariate model for the meta-analysis of study level survival data at multiple times.

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  • Additional Information
    • Source:
      Publisher: Wiley Blackwell Country of Publication: England NLM ID: 101543738 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1759-2887 (Electronic) Linking ISSN: 17592879 NLM ISO Abbreviation: Res Synth Methods Subsets: MEDLINE
    • Publication Information:
      Publication: : Chichester : Wiley Blackwell
      Original Publication: Malden, MA : John Wiley & Sons, 2010-
    • Subject Terms:
    • Abstract:
      Motivated by our meta-analytic dataset involving survival rates after treatment for critical leg ischemia, we develop and apply a new multivariate model for the meta-analysis of study level survival data at multiple times. Our data set involves 50 studies that provide mortality rates at up to seven time points, which we model simultaneously, and we compare the results to those obtained from standard methodologies. Our method uses exact binomial within-study distributions and enforces the constraints that both the study specific and the overall mortality rates must not decrease over time. We directly model the probabilities of mortality at each time point, which are the quantities of primary clinical interest. We also present I(2) statistics that quantify the impact of the between-study heterogeneity, which is very considerable in our data set.
      (© 2014 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.)
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    • Grant Information:
      MC_U105260558 United Kingdom MRC_ Medical Research Council; MR/J013595/1 United Kingdom MRC_ Medical Research Council; U105260558 United Kingdom MRC_ Medical Research Council
    • Contributed Indexing:
      Keywords: Bayesian modelling; critical leg ischemia; multivariate meta-analysis; random effects models; survival analysis
    • Publication Date:
      Date Created: 20150609 Date Completed: 20160224 Latest Revision: 20210925
    • Publication Date:
      20221216
    • Accession Number:
      PMC4433770
    • Accession Number:
      10.1002/jrsm.1112
    • Accession Number:
      26052851