The PCOS Phenotypes in Unselected Populations (P-PUP) study: participant clinical features and data harmonization on analysis of individual participant data

Abstract Background Polycystic ovary syndrome (PCOS) is a multifaceted condition with diagnostic challenges and clinical heterogeneity across populations. Research priorities include enhanced accuracy in defining cut-offs for diagnostic features. Here, we aim to describe participant clinical feature...

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Main Authors: Asmamaw Demis Bizuneh, Sylvia Kiconco, Arul Earnest, Mahnaz Bahri Khomami, Raja Ram Dhungana, Ricardo Azziz, Larisa V. Suturina, Xiaomiao Zhao, Alessandra Gambineri, Fahimeh Ramezani Tehrani, Bulent O. Yildiz, Jin Ju Kim, Liangzhi Xu, Christian Chigozie Makwe, Helena J. Teede, Anju E. Joham, Chau Thien Tay
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Language:English
Published: BMC 2025-07-01
Series:BMC Medicine
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Online Access:https://doi.org/10.1186/s12916-025-04221-9
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author Asmamaw Demis Bizuneh
Sylvia Kiconco
Arul Earnest
Mahnaz Bahri Khomami
Raja Ram Dhungana
Ricardo Azziz
Larisa V. Suturina
Xiaomiao Zhao
Alessandra Gambineri
Fahimeh Ramezani Tehrani
Bulent O. Yildiz
Jin Ju Kim
Liangzhi Xu
Christian Chigozie Makwe
Helena J. Teede
Anju E. Joham
Chau Thien Tay
author_facet Asmamaw Demis Bizuneh
Sylvia Kiconco
Arul Earnest
Mahnaz Bahri Khomami
Raja Ram Dhungana
Ricardo Azziz
Larisa V. Suturina
Xiaomiao Zhao
Alessandra Gambineri
Fahimeh Ramezani Tehrani
Bulent O. Yildiz
Jin Ju Kim
Liangzhi Xu
Christian Chigozie Makwe
Helena J. Teede
Anju E. Joham
Chau Thien Tay
author_sort Asmamaw Demis Bizuneh
collection DOAJ
description Abstract Background Polycystic ovary syndrome (PCOS) is a multifaceted condition with diagnostic challenges and clinical heterogeneity across populations. Research priorities include enhanced accuracy in defining cut-offs for diagnostic features. Here, we aim to describe participant clinical features and data harmonization in the international PCOS Phenotype in Unselected Populations (P-PUP) study. Methods We searched EMBASE and Medline (Ovid) from 1990 to October 2, 2020, in population-based, medically unbiased study cohorts. Included studies had ≥ 300 participants, directly assessed PCOS-related features, and provided Individual Participant Data (IPD). Risk of bias was assessed using the AXIS tool. Data integrity was ensured via cross-referencing, identifying outliers/implausible data, and variable harmonization. Reporting follows PRISMA-IPD guidelines, summarizing findings with frequencies and proportions. Results The study included 9979 reproductive-age women from 12 studies across eight countries (China, Iran, Italy, Nigeria, Russia, South Korea, Turkey, and the USA), representing 11 ethnicities. Ovulatory dysfunction was variably recorded, from mean menstrual cycle length, minimum or maximum cycle length, number of cycles per year, or urinary progesterone measurements. Clinical hyperandrogenism was assessed via modified Ferriman–Gallwey (mFG) scores, with a few also including acne and alopecia. Biochemical hyperandrogenism thresholds varied (95th, 97.5th, or 98th percentile of healthy controls). Polycystic ovary morphology was assessed via transvaginal, transabdominal, or transrectal approaches. Harmonization adhered to International PCOS Guidelines for ovulatory dysfunction, ethnicity-specific cut-offs for hirsutism (via k-means clustering), and 95th percentile thresholds for biochemical hyperandrogenism. PCOS prevalence ranged from 3.3 to 19.8% in the original studies and was 11.0% overall after harmonization. Conclusions The P-PUP study offers an unprecedented, ethnically diverse, medically unbiased population-based cohort, an extraordinarily valuable tool to enhance knowledge and research in PCOS. However, variability in data collection methods and definitions of PCOS diagnostic features across studies limited the ability to fully integrate data for analysis. Despite these limitations, we optimized harmonization in this IPD, and the findings provided valuable insights into the challenges of data harmonization and established a foundation for future collaborative research. Future research should focus on standardizing data collection, establishing normative cut-offs based on true natural groupings, and linking diagnostic clusters to outcomes in diverse populations. Protocol registration CRD42021267847.
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spelling doaj-art-3fdd5ec73ef9494a82e9014cc4d6c6f62025-08-20T03:43:22ZengBMCBMC Medicine1741-70152025-07-0123111910.1186/s12916-025-04221-9The PCOS Phenotypes in Unselected Populations (P-PUP) study: participant clinical features and data harmonization on analysis of individual participant dataAsmamaw Demis Bizuneh0Sylvia Kiconco1Arul Earnest2Mahnaz Bahri Khomami3Raja Ram Dhungana4Ricardo Azziz5Larisa V. Suturina6Xiaomiao Zhao7Alessandra Gambineri8Fahimeh Ramezani Tehrani9Bulent O. Yildiz10Jin Ju Kim11Liangzhi Xu12Christian Chigozie Makwe13Helena J. Teede14Anju E. Joham15Chau Thien Tay16Monash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences, Monash UniversityMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences, Monash UniversitySchool of Public Health and Preventive Medicine, Monash UniversityMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences, Monash UniversityMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences, Monash UniversityDepartments of Obstetrics and Gynecology, and Medicine, University of Alabama at BirminghamDepartment of Reproductive Health Protection, Scientific Center for Family Health and Human Reproduction ProblemsDepartment of Reproductive Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical UniversityDepartment of Medical and Surgical Science-DIMEC, Division of Endocrinology and Diabetes Prevention and Care, IRCCS Azienda Ospedaliero-Universitaria Di BolognaReproductive Endocrinology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical SciencesDivision of Endocrinology and Metabolism, Department of Internal Medicine, Hacettepe University School of MedicineDivision of Reproductive Endocrinology, Department of Obstetrics and Gynecology, Healthcare System Gangnam Center, Seoul National University HospitalDepartment of Obstetrics and Gynecology, West China Second University Hospital, Sichuan UniversityDepartment of Obstetrics and Gynaecology, College of Medicine, University of Lagos, Idi-Araba, Lagos, NigeriaMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences, Monash UniversityMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences, Monash UniversityMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences, Monash UniversityAbstract Background Polycystic ovary syndrome (PCOS) is a multifaceted condition with diagnostic challenges and clinical heterogeneity across populations. Research priorities include enhanced accuracy in defining cut-offs for diagnostic features. Here, we aim to describe participant clinical features and data harmonization in the international PCOS Phenotype in Unselected Populations (P-PUP) study. Methods We searched EMBASE and Medline (Ovid) from 1990 to October 2, 2020, in population-based, medically unbiased study cohorts. Included studies had ≥ 300 participants, directly assessed PCOS-related features, and provided Individual Participant Data (IPD). Risk of bias was assessed using the AXIS tool. Data integrity was ensured via cross-referencing, identifying outliers/implausible data, and variable harmonization. Reporting follows PRISMA-IPD guidelines, summarizing findings with frequencies and proportions. Results The study included 9979 reproductive-age women from 12 studies across eight countries (China, Iran, Italy, Nigeria, Russia, South Korea, Turkey, and the USA), representing 11 ethnicities. Ovulatory dysfunction was variably recorded, from mean menstrual cycle length, minimum or maximum cycle length, number of cycles per year, or urinary progesterone measurements. Clinical hyperandrogenism was assessed via modified Ferriman–Gallwey (mFG) scores, with a few also including acne and alopecia. Biochemical hyperandrogenism thresholds varied (95th, 97.5th, or 98th percentile of healthy controls). Polycystic ovary morphology was assessed via transvaginal, transabdominal, or transrectal approaches. Harmonization adhered to International PCOS Guidelines for ovulatory dysfunction, ethnicity-specific cut-offs for hirsutism (via k-means clustering), and 95th percentile thresholds for biochemical hyperandrogenism. PCOS prevalence ranged from 3.3 to 19.8% in the original studies and was 11.0% overall after harmonization. Conclusions The P-PUP study offers an unprecedented, ethnically diverse, medically unbiased population-based cohort, an extraordinarily valuable tool to enhance knowledge and research in PCOS. However, variability in data collection methods and definitions of PCOS diagnostic features across studies limited the ability to fully integrate data for analysis. Despite these limitations, we optimized harmonization in this IPD, and the findings provided valuable insights into the challenges of data harmonization and established a foundation for future collaborative research. Future research should focus on standardizing data collection, establishing normative cut-offs based on true natural groupings, and linking diagnostic clusters to outcomes in diverse populations. Protocol registration CRD42021267847.https://doi.org/10.1186/s12916-025-04221-9Data harmonizationAndrogensPolycystic ovary syndromePCOSHirsutismAcne
spellingShingle Asmamaw Demis Bizuneh
Sylvia Kiconco
Arul Earnest
Mahnaz Bahri Khomami
Raja Ram Dhungana
Ricardo Azziz
Larisa V. Suturina
Xiaomiao Zhao
Alessandra Gambineri
Fahimeh Ramezani Tehrani
Bulent O. Yildiz
Jin Ju Kim
Liangzhi Xu
Christian Chigozie Makwe
Helena J. Teede
Anju E. Joham
Chau Thien Tay
The PCOS Phenotypes in Unselected Populations (P-PUP) study: participant clinical features and data harmonization on analysis of individual participant data
BMC Medicine
Data harmonization
Androgens
Polycystic ovary syndrome
PCOS
Hirsutism
Acne
title The PCOS Phenotypes in Unselected Populations (P-PUP) study: participant clinical features and data harmonization on analysis of individual participant data
title_full The PCOS Phenotypes in Unselected Populations (P-PUP) study: participant clinical features and data harmonization on analysis of individual participant data
title_fullStr The PCOS Phenotypes in Unselected Populations (P-PUP) study: participant clinical features and data harmonization on analysis of individual participant data
title_full_unstemmed The PCOS Phenotypes in Unselected Populations (P-PUP) study: participant clinical features and data harmonization on analysis of individual participant data
title_short The PCOS Phenotypes in Unselected Populations (P-PUP) study: participant clinical features and data harmonization on analysis of individual participant data
title_sort pcos phenotypes in unselected populations p pup study participant clinical features and data harmonization on analysis of individual participant data
topic Data harmonization
Androgens
Polycystic ovary syndrome
PCOS
Hirsutism
Acne
url https://doi.org/10.1186/s12916-025-04221-9
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