Evidence map›Paper›PMID 40660246›Full record

ArticleBMC medicine2025

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

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 and 7 more

Abstract read
In one paragraph

Article in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Observational
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Asmamaw Demis BizunehMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, 3168, Australia.
Sylvia KiconcoMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, 3168, Australia.
Arul EarnestSchool of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia.
Mahnaz Bahri KhomamiMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, 3168, Australia.
Raja Ram DhunganaMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, 3168, Australia.
Ricardo AzzizDepartments of Obstetrics and Gynecology, and Medicine, University of Alabama at Birmingham, Birmingham, AL, 35294, USA.
Larisa V SuturinaDepartment of Reproductive Health Protection, Scientific Center for Family Health and Human Reproduction Problems, Irkutsk, 664003, Russian Federation.
Xiaomiao ZhaoDepartment of Reproductive Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 106 Zhongshan 2 Road, Guangzhou, 510080, China.
Alessandra GambineriDepartment of Medical and Surgical Science-DIMEC, Division of Endocrinology and Diabetes Prevention and Care, IRCCS Azienda Ospedaliero-Universitaria Di Bologna, Via Massarenti 9, Bologna, 40138, Italy.
Fahimeh Ramezani TehraniReproductive Endocrinology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, 24 Parvaneh, Yaman Street, Velenjak, Tehran, 19395-4763, Iran.
Bulent O YildizDivision of Endocrinology and Metabolism, Department of Internal Medicine, Hacettepe University School of Medicine, Ankara, 06100, Turkey.
Jin Ju KimDivision of Reproductive Endocrinology, Department of Obstetrics and Gynecology, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, 06236, Republic of Korea.
Liangzhi XuDepartment of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
Christian Chigozie MakweDepartment of Obstetrics and Gynaecology, College of Medicine, University of Lagos, Idi-Araba, Lagos, Nigeria, P.M.B. 12003, Surulere, Lagos, Nigeria.
Helena J TeedeMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, 3168, Australia.
Anju E Joham *Monash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, 3168, Australia.
Chau Thien Tay *Monash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, 3168, Australia. jillian.tay@monash.edu.

Funding

NHMRC fellowships #2009326
6 · The paper itself

Abstract

backgroundPolycystic 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.

methodsWe 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.

resultsThe 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.

conclusionsThe 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.

Indexed as

Polycystic Ovary SyndromeAdultFemaleHumansPhenotypeYoung AdultAcneAndrogensData harmonizationFemale pattern hair lossHirsutismIndividual participant dataIPDPCOSPhenotypePolycystic ovaryPolycystic ovary syndrome

Identifiers

PMID40660246
PMCPMC12261540

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.