The predictive accuracy of anti-Müllerian hormone for live birth after assisted conception: a systematic review and meta-analysis of the literature

Anti-Müllerian hormone (AMH) is an established marker of ovarian reserve and a good predictor of poor or excessive ovarian response after controlled hyperstimulation. However, it is unclear whether it can predict the ultimate outcome of assisted conception, live birth. We undertook a systematic review and meta-analysis to examine whether AMH is a predictor of live birth in women undergoing assisted conception. The study was conducted according to the PRISMA guidelines. PubMed, Embase, Medline, Web of Knowledge and the Cochrane trial register and unpublished literature were searched. Studies fulfilling the eligibility criteria were included in the systematic review and those with extractable data were included in the meta-analysis. Quality assessment was performed with the QUADAS 2 checklist. A summary estimate of diagnostic odds ratio (DOR) was derived using the random effects model for binary data. A hierarchical summary receiver operating characteristic model provided pooled estimates before and after adjusting for age and AMH assay as covariates. Out of 361 non-duplicate studies, 47 were selected; 17 met the eligibility criteria and 13 had extractable data and thus were included in the meta-analysis. Three out of the 13 studies included only women with expected low ovarian reserve and were analysed individually from the remaining 10 to minimize heterogeneity. The DOR for women with unknown ovarian reserve (n = 5764 women) was 2.39 (95% confidence interval (CI): 1.85-3.08). After adjustment for age the DOR was little changed at 2.48 (95% CI: 1.81-3.22) and the DOR adjusted for AMH assay was almost identical at 2.42 (95% CI: 1.86-3.14). For women with expected low ovarian reserve (n = 542 women) the DOR was 4.63 (95% CI: 2.75-7.81). AMH, independently of age, has some association with predicting live birth after assisted conception and may be helpful when counselling couples before undergoing fertility treatment. However, its predictive accuracy is poor.