New Insights Into the Relationship of Antimullerian Hormone With Polycystic Ovary Syndrome and Its Diagnostic Accuracy: An Updated and Extended Meta-Analysis Using a Marginal Beta-Binomial Model Publisher Pubmed



Barghi M^{1, 2} ; Heidari Z¹ ; Haghighatdoost F³ ; Feizi A¹ ; Hashemipour M^{4, 5} Show Affiliations
Source: American Journal of Obstetrics and Gynecology Published:2025

Abstract

Objective: This study aimed to investigate the diagnostic role of antimullerian hormone in polycystic ovary syndrome using an advanced marginal beta-binomial statistical model, and present the optimal cutoff by different age groups, geographical locations, body mass indexes, and other relevant factors. Data Sources: A comprehensive and systematic literature search was conducted in Web of Science, PubMed/Medline, Scopus, Cochrane Library, Embase, and ProQuest until August 2024. Study Eligibility Criteria: Epidemiologic studies that used the Androgen Excess and Polycystic Ovary Syndrome Society, National Institutes of Health, or Rotterdam diagnostic criteria for polycystic ovary syndrome were included in this meta-analysis. Studies were eligible for inclusion if they provided information on the sensitivity and specificity of antimullerian hormone or related data that allowed for the calculation of these parameters, and/or data on odds ratios and means. Methods: The diagnostic efficacy of antimullerian hormone was assessed using the marginal beta-binomial statistical model and the summary receiver operating characteristic method in terms of pooled sensitivity, specificity, and diagnostic odds ratio with 95% confidence interval. Pooled weighted mean difference and pooled odds ratios with 95% confidence interval were estimated using a random effects model. Results: A total of 202 observational studies were included in the pooled analysis, of which 106 studies (including 19,465 cases and 29,318 controls) were used for meta-analysis of sensitivity/specificity and 186 studies (including 30,656 cases and 34,360 controls) for meta-analysis of mean difference. The pooled sensitivity, specificity, and diagnostic odds ratio for antimullerian hormone were 0.79 (95% confidence interval, 0.52–0.97), 0.82 (95% confidence interval, 0.64–0.99), and 17.12 (95% confidence interval, 14.37–20.32), respectively. The area under the curve based on the summary receiver operating characteristic model was 0.90 (95% confidence interval, 0.87–0.93). Antimullerian hormone levels were significantly higher in women with polycystic ovary syndrome than in control women (weighted mean difference, 4.91; 95% confidence interval, 4.57–5.27). In addition, individuals with higher antimullerian hormone levels were more likely to be affected by polycystic ovary syndrome (odds ratio, 23.17; 95% confidence interval, 18.74–28.66; I2=94%; P<.001). A serum antimullerian hormone concentration of >5.39 ng/mL was associated with polycystic ovary syndrome (sensitivity, 88.6%; specificity, 92.75%; likelihood ratio for a positive test result, 12.21; likelihood ratio for a negative test result, 0.12). Conclusion: According to the results of this meta-analysis, serum antimullerian hormone concentration is a valuable biomarker for the diagnosis of polycystic ovary syndrome. The cutoff points suggested by the current meta-analysis need to be evaluated and validated by future studies before their implementation into clinical practice. © 2024