抗苗勒氏管激素与多囊卵巢综合征的关系及其诊断准确性的新见解：使用边际β-二项式模型的最新扩展荟萃分析。

IF 8.7 1区医学 Q1 OBSTETRICS & GYNECOLOGY

American journal of obstetrics and gynecology Pub Date : 2025-02-01 DOI:10.1016/j.ajog.2024.10.004

Mostafa Barghi MSc , Zahra Heidari PhD , Fahimeh Haghighatdoost PhD , Awat Feizi PhD , Mahin Hashemipour MD

{"title":"抗苗勒氏管激素与多囊卵巢综合征的关系及其诊断准确性的新见解：使用边际β-二项式模型的最新扩展荟萃分析。","authors":"Mostafa Barghi MSc , Zahra Heidari PhD , Fahimeh Haghighatdoost PhD , Awat Feizi PhD , Mahin Hashemipour MD","doi":"10.1016/j.ajog.2024.10.004","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><div>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.</div></div><div><h3>Data Sources</h3><div>A comprehensive and systematic literature search was conducted in Web of Science, PubMed/Medline, Scopus, Cochrane Library, Embase, and ProQuest until August 2024.</div></div><div><h3>Study Eligibility Criteria</h3><div>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.</div></div><div><h3>Methods</h3><div>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.</div></div><div><h3>Results</h3><div>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; I<sup>2</sup>=94%; <em>P</em><.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).</div></div><div><h3>Conclusion</h3><div>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.</div></div>","PeriodicalId":7574,"journal":{"name":"American journal of obstetrics and gynecology","volume":"232 2","pages":"Pages 164-187.e31"},"PeriodicalIF":8.7000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"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\",\"authors\":\"Mostafa Barghi MSc , Zahra Heidari PhD , Fahimeh Haghighatdoost PhD , Awat Feizi PhD , Mahin Hashemipour MD\",\"doi\":\"10.1016/j.ajog.2024.10.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><div>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.</div></div><div><h3>Data Sources</h3><div>A comprehensive and systematic literature search was conducted in Web of Science, PubMed/Medline, Scopus, Cochrane Library, Embase, and ProQuest until August 2024.</div></div><div><h3>Study Eligibility Criteria</h3><div>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.</div></div><div><h3>Methods</h3><div>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.</div></div><div><h3>Results</h3><div>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; I<sup>2</sup>=94%; <em>P</em><.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).</div></div><div><h3>Conclusion</h3><div>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.</div></div>\",\"PeriodicalId\":7574,\"journal\":{\"name\":\"American journal of obstetrics and gynecology\",\"volume\":\"232 2\",\"pages\":\"Pages 164-187.e31\"},\"PeriodicalIF\":8.7000,\"publicationDate\":\"2025-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American journal of obstetrics and gynecology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0002937824010524\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"OBSTETRICS & GYNECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of obstetrics and gynecology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0002937824010524","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OBSTETRICS & GYNECOLOGY","Score":null,"Total":0}

引用次数: 0

摘要

目的使用高级边际β-二项式统计模型研究抗苗勒氏管激素（AMH）在多囊卵巢综合征（PCOS）中的诊断作用，并根据不同年龄组、地理位置、体重指数（BMI）和其他相关因素提出最佳临界值：数据来源：在 ISI Web of Science、PubMed/Medline、Scopus、Cochrane Library、Embase 和 ProQuest 中进行了全面系统的文献检索，直至 2024 年 8 月：本次荟萃分析纳入了以雄激素过多协会（AES）或美国国立卫生研究院（NIH）或鹿特丹为多囊卵巢综合症诊断标准的流行病学研究。如果研究中包含有关 AMH 敏感性和特异性的信息或相关数据，我们可以据此计算出这些参数和/或有关几率和平均值的数据，则符合纳入条件：方法：采用边际β-二叉统计模型和接收者操作特征概要（SROC）方法，从集合敏感性、特异性和诊断几率比（DOR）及95%置信区间（CI）的角度评估AMH的诊断作用。使用随机效应模型估算了汇总加权平均差（WMD）和汇总几率比（ORs）及 95% 置信区间（CI）：共有 202 项观察性研究被纳入汇总分析，其中 106 项研究（包括 19465 例病例和 29318 例对照）用于敏感性/特异性荟萃分析，186 项研究（包括 30656 例病例和 34360 例对照）用于平均差荟萃分析。AMH的集合敏感性、特异性和DOR分别为0.79（95% CI：0.52至0.97）、0.82（95% CI：0.64至0.99）和17.12（95% CI：14.37至20.32）。基于 SROC 模型的曲线下面积（AUC）为 0.90（95% CI：0.87 至 0.93）。多囊卵巢综合症妇女的 AMH 水平明显高于对照组妇女（WMD= 4.91；95% CI：4.57-5.27）。此外，AMH水平较高的个体更有可能患有多囊卵巢综合症（OR=23.17；95% CI：18.74-28.66；I2=94%；P5.39 ng/mL），与多囊卵巢综合症相关（灵敏度=88.6%；特异性=92.75%；检测结果呈阳性的似然比（LR+）=12.21；检测结果呈阴性的似然比（LR-）=0.12）：根据这项荟萃分析的结果，血清AMH浓度是诊断多囊卵巢综合征的重要生物标志物。目前的荟萃分析所建议的临界点需要在今后的研究中进行评估和验证，然后才能在临床实践中应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

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.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

American journal of obstetrics and gynecology 医学-妇产科学

CiteScore

15.90

自引率

7.10%

发文量

2237

审稿时长

47 days

期刊介绍： The American Journal of Obstetrics and Gynecology, known as "The Gray Journal," covers the entire spectrum of Obstetrics and Gynecology. It aims to publish original research (clinical and translational), reviews, opinions, video clips, podcasts, and interviews that contribute to understanding health and disease and have the potential to impact the practice of women's healthcare. Focus Areas: Diagnosis, Treatment, Prediction, and Prevention: The journal focuses on research related to the diagnosis, treatment, prediction, and prevention of obstetrical and gynecological disorders. Biology of Reproduction: AJOG publishes work on the biology of reproduction, including studies on reproductive physiology and mechanisms of obstetrical and gynecological diseases. Content Types: Original Research: Clinical and translational research articles. Reviews: Comprehensive reviews providing insights into various aspects of obstetrics and gynecology. Opinions: Perspectives and opinions on important topics in the field. Multimedia Content: Video clips, podcasts, and interviews. Peer Review Process: All submissions undergo a rigorous peer review process to ensure quality and relevance to the field of obstetrics and gynecology.