Padala Ravi Kumar, Radha Krishna Telagareddy, Deepak Kumar Dash, Debasish Patro
{"title":"各种激素在不同多囊卵巢综合征表型中的诊断效用:一项横断面研究。","authors":"Padala Ravi Kumar, Radha Krishna Telagareddy, Deepak Kumar Dash, Debasish Patro","doi":"10.4103/jhrs.jhrs_152_24","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Polycystic ovary syndrome (PCOS) presents a complex diagnostic challenge due to its heterogeneous nature.</p><p><strong>Aim: </strong>This study aimed to examine the diagnostic utility of various hormones across different PCOS phenotypes.</p><p><strong>Settings and design: </strong>This cross-sectional study was carried out in 187 newly diagnosed PCOS women (18-40 years) attending the outdoor clinics of the department of endocrinology and obstetrics and gynaecology of a tertiary care centre in India.</p><p><strong>Materials and methods: </strong>One hundred and eighty-seven PCOS women based on revised Rotterdam 2003 criteria were recruited. Ninety-four age-matched healthy females were taken as controls. All PCOS women were categorised into four phenotypes (A, B, C and D) based on the National Institute of Health (2012) criteria. Detailed clinical examination and hormonal investigations including testosterone, androstenedione, dehydroepiandrosterone sulphate (DHEAS) and anti-Müllerian hormone (AMH) were performed.</p><p><strong>Statistical analysis used: </strong>The receiver operating characteristic curve (ROC) was generated to find the diagnostic utility of various hormones by using SPSS version 26.0 software.</p><p><strong>Results: </strong>The largest PCOS group was phenotype A (33.15%, <i>n</i> = 61) followed by phenotype B (28.6%, <i>n</i> = 52), phenotype D (23.9%, <i>n</i> = 44) and phenotype C (16.3%, <i>n</i> = 30). In ROC analysis, AMH and testosterone (except phenotype D) were good diagnostic parameters for PCOS. AMH cutoffs varied from 4.4 to 5.6 ng/mL with sensitivities and specificities ranging from 86% to 97% and 85% to 100%, respectively, across all PCOS phenotypes. In the entire PCOS cohort, AMH at an optimal cutoff of 5.28 ng/mL had sensitivity and specificity of 87% and 97%, respectively, for the diagnosis of PCOS. Optimal testosterone cutoffs were 29.3, 25.1 and 23.1 ng/dL for phenotypes A, B and C, respectively, with reasonable sensitivities and specificities but not in phenotype D. Luteinising hormone (LH), follicle-stimulating hormone (FSH), LH/FSH ratio, androstenedione and DHEAS had low-to-moderate sensitivity across all phenotypes.</p><p><strong>Conclusion: </strong>AMH is a useful hormonal diagnostic marker for PCOS across all phenotypes.</p>","PeriodicalId":15975,"journal":{"name":"Journal of Human Reproductive Sciences","volume":"17 4","pages":"275-283"},"PeriodicalIF":0.0000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11741125/pdf/","citationCount":"0","resultStr":"{\"title\":\"Diagnostic Utility of Various Hormones across Different Polycystic Ovary Syndrome Phenotypes: A Cross-sectional Study.\",\"authors\":\"Padala Ravi Kumar, Radha Krishna Telagareddy, Deepak Kumar Dash, Debasish Patro\",\"doi\":\"10.4103/jhrs.jhrs_152_24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Polycystic ovary syndrome (PCOS) presents a complex diagnostic challenge due to its heterogeneous nature.</p><p><strong>Aim: </strong>This study aimed to examine the diagnostic utility of various hormones across different PCOS phenotypes.</p><p><strong>Settings and design: </strong>This cross-sectional study was carried out in 187 newly diagnosed PCOS women (18-40 years) attending the outdoor clinics of the department of endocrinology and obstetrics and gynaecology of a tertiary care centre in India.</p><p><strong>Materials and methods: </strong>One hundred and eighty-seven PCOS women based on revised Rotterdam 2003 criteria were recruited. Ninety-four age-matched healthy females were taken as controls. All PCOS women were categorised into four phenotypes (A, B, C and D) based on the National Institute of Health (2012) criteria. Detailed clinical examination and hormonal investigations including testosterone, androstenedione, dehydroepiandrosterone sulphate (DHEAS) and anti-Müllerian hormone (AMH) were performed.</p><p><strong>Statistical analysis used: </strong>The receiver operating characteristic curve (ROC) was generated to find the diagnostic utility of various hormones by using SPSS version 26.0 software.</p><p><strong>Results: </strong>The largest PCOS group was phenotype A (33.15%, <i>n</i> = 61) followed by phenotype B (28.6%, <i>n</i> = 52), phenotype D (23.9%, <i>n</i> = 44) and phenotype C (16.3%, <i>n</i> = 30). In ROC analysis, AMH and testosterone (except phenotype D) were good diagnostic parameters for PCOS. AMH cutoffs varied from 4.4 to 5.6 ng/mL with sensitivities and specificities ranging from 86% to 97% and 85% to 100%, respectively, across all PCOS phenotypes. In the entire PCOS cohort, AMH at an optimal cutoff of 5.28 ng/mL had sensitivity and specificity of 87% and 97%, respectively, for the diagnosis of PCOS. Optimal testosterone cutoffs were 29.3, 25.1 and 23.1 ng/dL for phenotypes A, B and C, respectively, with reasonable sensitivities and specificities but not in phenotype D. 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Diagnostic Utility of Various Hormones across Different Polycystic Ovary Syndrome Phenotypes: A Cross-sectional Study.
Background: Polycystic ovary syndrome (PCOS) presents a complex diagnostic challenge due to its heterogeneous nature.
Aim: This study aimed to examine the diagnostic utility of various hormones across different PCOS phenotypes.
Settings and design: This cross-sectional study was carried out in 187 newly diagnosed PCOS women (18-40 years) attending the outdoor clinics of the department of endocrinology and obstetrics and gynaecology of a tertiary care centre in India.
Materials and methods: One hundred and eighty-seven PCOS women based on revised Rotterdam 2003 criteria were recruited. Ninety-four age-matched healthy females were taken as controls. All PCOS women were categorised into four phenotypes (A, B, C and D) based on the National Institute of Health (2012) criteria. Detailed clinical examination and hormonal investigations including testosterone, androstenedione, dehydroepiandrosterone sulphate (DHEAS) and anti-Müllerian hormone (AMH) were performed.
Statistical analysis used: The receiver operating characteristic curve (ROC) was generated to find the diagnostic utility of various hormones by using SPSS version 26.0 software.
Results: The largest PCOS group was phenotype A (33.15%, n = 61) followed by phenotype B (28.6%, n = 52), phenotype D (23.9%, n = 44) and phenotype C (16.3%, n = 30). In ROC analysis, AMH and testosterone (except phenotype D) were good diagnostic parameters for PCOS. AMH cutoffs varied from 4.4 to 5.6 ng/mL with sensitivities and specificities ranging from 86% to 97% and 85% to 100%, respectively, across all PCOS phenotypes. In the entire PCOS cohort, AMH at an optimal cutoff of 5.28 ng/mL had sensitivity and specificity of 87% and 97%, respectively, for the diagnosis of PCOS. Optimal testosterone cutoffs were 29.3, 25.1 and 23.1 ng/dL for phenotypes A, B and C, respectively, with reasonable sensitivities and specificities but not in phenotype D. Luteinising hormone (LH), follicle-stimulating hormone (FSH), LH/FSH ratio, androstenedione and DHEAS had low-to-moderate sensitivity across all phenotypes.
Conclusion: AMH is a useful hormonal diagnostic marker for PCOS across all phenotypes.
期刊介绍:
The Journal of Human Reproductive Sciences (JHRS) (ISSN:0974-1208) a Quarterly peer-reviewed international journal is being launched in January 2008 under the auspices of Indian Society of Assisted Reproduction. The journal will cover all aspects human reproduction including Andrology, Assisted conception, Endocrinology, Physiology and Pathology, Implantation, Preimplantation Diagnosis, Preimplantation Genetic Diagnosis, Embryology as well as Ethical, Legal and Social issues. The journal will publish peer-reviewed original research papers, case reports, systematic reviews, meta-analysis, and debates.