Exploring the variability in Behçet's disease prevalence: a meta-analytical approach

Abstract

Background: Surveys of Behçet's disease (BD) have shown substantial geographic variations in prevalence, but some of these differences may result from methodological inconsistencies. This meta-analysis explored the effect of geographic location and study methodology on the prevalence of BD.

Methods: We systematically searched the literature in electronic databases and by handsearching to identify population-based prevalence surveys of BD. Studies were eligible if they provided an original population-based prevalence estimate for BD with the number of prevalent cases identified in the study area. Pooled prevalence proportions across all studies were computed by using random effects models based on a Poisson normal distribution. Pre-defined subgroup analyses and meta-regression were used to investigate the effect of covariates on the prevalence proportions.

Results: We included 45 reports published from 1974 to 2015 and covering worldwide areas. The pooled estimates of prevalence proportions (expressed as cases/100 000 inhabitants) were 10.3 (95% CI 6.1, 17.7) for all studies and 119.8 (59.8, 239.9) for Turkey, 31.8 (12.9, 78.4) for the Middle East, 4.5 (2.2, 9.4) for Asia and 3.3 (2.1, 5.2) for Europe. Subgroup analyses showed a strikingly greater prevalence for studies with a sample survey design than a census design [82.5 (95% CI 47.3, 143.9) vs 3.6 (2.6, 5.1)]. Metaregression identified study design as an independent covariate significantly affecting BD prevalence proportions.

Conclusions: Differences in BD prevalence proportions likely reflect a combination of true geographic variation and methodological artefacts. In particular, use of a sample or census study design may strongly affect the estimated prevalence.

Keywords: Behçet’s disease; epidemiology; meta-analysis; prevalence.