A Systematic Review and Meta-Analysis of Interventions to Prevent Hepatitis C Virus Infection in People Who Inject Drugs

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Abstract

High rates of hepatitis C virus (HCV) transmission are found in samples of people who inject drugs (PWID) throughout the world. The objective of this paper was to meta-analyze the effects of risk-reduction interventions on HCV seroconversion and identify the most effective intervention types. We performed a systematic review and meta-analysis of published and unpublished studies. Eligible studies reported on the association between participation in interventions intended to reduce unsafe drug injection and HCV seroconversion in samples of PWID. The meta-analysis included 26 eligible studies of behavioral interventions, substance-use treatment, syringe access, syringe disinfection, and multicomponent interventions. Interventions using multiple combined strategies reduced risk of seroconversion by 75% (pooled relative risk, .25; 95% confidence interval, .07-.83). Effects of single-method interventions ranged from .6 to 1.6. Interventions using strategies that combined substance-use treatment and support for safe injection were most effective at reducing HCV seroconversion. Determining the effective dose and combination of interventions for specific subgroups of PWID is a research priority. However, our meta-analysis shows that HCV infection can be prevented in PWID.

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Quantifying heterogeneity in a meta-analysis.

Julian P T Higgins, Simon G Thompson (2002)

The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.