A Comparison of Statistical Methods for Identifying Out-of-Date Systematic Reviews

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Abstract
Systematic reviews (SRs) can provide accurate and reliable evidence, typically about the effectiveness of health interventions. Evidence is dynamic, and if SRs are out-of-date this information may not be useful; it may even be harmful. This study aimed to compare five statistical methods to identify out-of-date SRs. A retrospective cohort of SRs registered in the Cochrane Pregnancy and Childbirth Group (CPCG), published between 2008 and 2010, were considered for inclusion. For each eligible CPCG review, data were extracted and “3-years previous” meta-analyses were assessed for the need to update, given the data from the most recent 3 years. Each of the five statistical methods was used, with random effects analyses throughout the study. Eighty reviews were included in this study; most were in the area of induction of labour. The numbers of reviews identified as being out-of-date using the Ottawa, recursive cumulative meta-analysis (CMA), and Barrowman methods were 34, 7, and 7 respectively. No reviews were identified as being out-of-date using the simulation-based power method, or the CMA for sufficiency and stability method. The overall agreement among the three discriminating statistical methods was slight (Kappa = 0.14; 95% CI 0.05 to 0.23). The recursive cumulative meta-analysis, Ottawa, and Barrowman methods were practical according to the study criteria. Our study shows that three practical statistical methods could be applied to examine the need to update SRs.