Can we use serum Anti-Mullerian hormone to differentiate the diagnosis between polycystic ovary syndrome patients and healthy women with polycystic ovarian morphology and regular menstrual cycles

New insights into the relationship of antimüllerian hormone with polycystic ovary syndrome and its diagnostic accuracy: an updated and extended meta-analysis using a marginal beta-binomial model

OBJECTIVE

This study aimed to investigate the diagnostic role of antimüllerian 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 antimüllerian 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 antimüllerian 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 antimüllerian 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). Antimüllerian 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 antimüllerian 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 antimüllerian 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 antimüllerian 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.

Anti-müllerian hormone as a diagnostic biomarker for polycystic ovary syndrome and polycystic ovarian morphology: a systematic review and meta-analysis

IMPORTANCE

As part of the 2023 international evidence-based polycystic ovary syndrome (PCOS) guideline, this meta-analysis investigated the inclusion of Anti-Müllerian hormone (AMH) levels in the diagnostic criteria for PCOS.

OBJECTIVE

To answer the following three questions: 1) Are AMH levels effective in diagnosing PCOS in adult women? 2) Are AMH levels effective in diagnosing PCOS in adolescents? Are AMH levels effective in diagnosing polycystic ovarian morphology (PCOM)?

DATA SOURCES

Searches were conducted in six databases until July 31, 2023.

STUDY SELECTION AND SYNTHESIS

Eligible studies were those conducted in humans, published in English, and reporting sensitivity, specificity, and/or area under the curve values. Extracted data included study population, age, body mass index, AMH assay, cut-off value of AMH levels, sensitivity, specificity, and area under the curve values. The risk of bias was assessed using the quality assessment of diagnostic accuracy studies tool. A random effects model was used to test diagnostic accuracy.

MAIN OUTCOMES

Pooled sensitivity and specificity to use AMH levels for PCOS diagnosis in adults as well as adolescents and for detecting PCOM in adults.

RESULTS

Eighty-two studies were included. The adult AMH-PCOS meta-analyses (n = 68) showed a pooled sensitivity and specificity of 0.79 (95% confidence interval [CI], 0.76-0.82; I2 = 86%) and 0.87 (95% CI, 0.84-0.89; I2 = 91%). The adolescent AMH-PCOS meta-analysis (n = 11) showed a pooled sensitivity and specificity of 0.66 (95% CI, 0.58-0.73; I2 = 74%) and 0.78 (95% CI, 0.71-0.83; I2 = 45%). The adult AMH-PCOM meta-analysis (n = 7) showed a pooled sensitivity and specificity of 0.79 (95% CI, 0.72-0.85; I2 = 94%) and 0.87 (95% CI, 0.78-0.93; I2 = 94%). CONCLUSION AND RELEVANCE: This study investigated the most profound change in the 2023 international evidence-based PCOS guideline, which now recommends AMH levels for defining PCOM in adults in accordance with the diagnostic algorithm. Antimüllerian hormone levels alone are insufficient for PCOS diagnosis and are nonspecific for PCOM in adolescents. Multiple factors influence AMH levels and cause heterogeneity as well as limitations in this study. Consequently, no international cut-off value could be recommended, emphasizing the need for research on more individualized cut-off values.

Updated meta-analysis on the diagnostic accuracy of serum anti-Mullerian hormone in poly cystic ovary syndrome involving 13 509 subjects

AIM

To determine the diagnostic accuracy of anti-Mullerian hormone (AMH) in the diagnosis of polycystic ovary syndrome (PCOS).

METHODS

Two independent reviewers searched the electronic databases and search engines using PubMed, Cochrane library, and Google Scholar systematically to retrieve relevant articles published from inception to September 2021. The diagnostic efficacy of AMH was computed using the random-effects model in terms of pooled sensitivity, specificity, and diagnostic odds ratio (DOR) with 95% confidence interval (CI). A meta-regression and subgroup analysis were performed to check for any source which could explain possible heterogeneity. Risk of bias assessment was conducted using the QUADAS-2 tool recommended by Cochrane Library.

RESULTS

This meta-analysis included a total of 41 studies involving 13 509 subjects. We observed promising pooled sensitivity 0.78 (95% CI 0.74 to 0.81), specificity 0.87 (95% CI 0.84 to 0.90), and diagnostic odds ratio (DOR) 24 (95% CI 15 to 37), for AMH in detecting PCOS and discriminatory power (summary receiver operating characteristic [SROC] curves, 0.89 [95% CI 0.86-0.92]). The most prominent bias was noted in the patient selection and index test assessment.

CONCLUSIONS

With the findings of this current meta-analysis, we conclude serum AMH to be a promising biomarker for the diagnosis of PCOS, however, substantial heterogeneity among studies needs individual patient data analysis in order to identify an optimal cut-off value and homogenous findings.

REGISTRATION NUMBER AND GUIDELINES

This meta-analysis was performed according to constructed protocol registered in the PROSPERO database with registration number CRD42021246910.

Mutational Analysis of the Putative Anti-Müllerian Hormone (AMH) Binding Interface on its Type II Receptor, AMHR2

Anti-Müllerian hormone (AMH) or Müllerian inhibiting substance is a unique member of the TGF-β family responsible for development and differentiation of the reproductive system. AMH signals through its own dedicated type II receptor, anti-Müllerian hormone receptor type II (AMHR2), providing an exclusive ligand-receptor pair within the broader TGF-β family. In this study, we used previous structural information to derive a model of AMH bound to AMHR2 to guide mutagenesis studies to identify receptor residues important for AMH signaling. Nonconserved mutations were introduced in AMHR2 and characterized in an AMH-responsive cell-based luciferase assay and native PAGE. Collectively, our results identified several residues important for AMH signaling within the putative ligand binding interface of AMHR2. Our results show that AMH engages AMHR2 at a similar interface to how activin and BMP class ligands bind the type II receptor, ACVR2B; however, there are significant molecular differences at the ligand interface of these 2 receptors, where ACVR2B is mostly hydrophobic and AMHR2 is predominately charged. Overall, this study shows that although the location of ligand binding on the receptor is similar to ACVR2A, ACVR2B, and BMPR2; AMHR2 uses unique ligand-receptor interactions to impart specificity for AMH.