Inconsistent results in meta-analyses for the prevention of falls are found between study-level data and patient-level data

Terry P. Haines, Anne Marie Hill

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Objective: This study seeks to examine whether existing study-level data meta-analysis approaches can be used to produce unbiased and precise effect estimates relative to meta-analyses conducted using patient-level data, where a recurrent event is the outcome of interest. Study Design and Setting: Data from two studies focusing on the prevention of falls in the hospital setting (N = 1,838 total) was divided into the three hospital sites from which data were collected. Outcome data were considered as recurrent event survival data, single event survival data, count data, rate data, and binary data. A range of analysis approaches were considered. Results: Andersen-Gill, negative binomial, bootstrap resampling, and modified relative risk analysis approaches produced congruous point estimates of effect, whereas modified relative risk analysis produced considerably smaller standard errors. Pooled effect point estimates derived from these approaches were not consistent when using study-level data as opposed to patient-level data, and 95% confidence intervals were excessively wide when between-study heterogeneity was present. Conclusion: Conducting meta-analysis using patient-level data (if possible) or presenting results from individual trials without pooling of effect estimates may be preferable to presenting pooled effect estimates from meta-analysis of study-level data, where the outcome is a recurrent event.

Original languageEnglish
Pages (from-to)154-162
Number of pages9
JournalJournal of Clinical Epidemiology
Volume64
Issue number2
DOIs
Publication statusPublished - Feb 2011
Externally publishedYes

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