Objective: Hirsutism, a diagnostic feature of polycystic ovary syndrome (PCOS), is often defined using arbitrary percentile cut-offs, rather than normative cut-offs from population-based data. We aimed to define normative cut-offs for hirsutism in diverse populations. Design: Unselected population-based cluster analysis of individual participant data (IPD). Methods: The PCOS Phenotype in Unselected Populations (P-PUP) study IPD asset of community-based studies, underwent k-means cluster analysis, of directly assessed hirsutism, using the modified Ferriman-Gallwey (mFG) visual scale. The primary outcome was ethnicity-specific normative cut-offs for the mFG score. Medians and cut-offs were compared across ethnic groups. Results: We included 9829 unselected, medically unbiased participants, aged 18 to 45 years from 12 studies conducted across eight countries including China, Iran, Italy, Nigeria, Russia, South Korea, Turkey, and the United States. The mFG cut-off scores for hirsutism on cluster analysis varied across ethnicities, ranging from 4 to 8. White Iranians had the highest cut-off score of 8, followed by White Italians and Black Africans of 7. Asian Han Chinese, White Russian, Turkish, and Black Americans shared a cut-off of 5; White Americans, Asian Koreans, Asian Russians, and Mixed Russians shared a cut-off of 4. Comparing medians and mFG cut-offs across ethnicities confirmed the same differences. Conclusion: This study confirms the 2023 International PCOS Guidelines recommendations defining hirsutism as an mFG score between 4-6 for the majority of populations studied, with few exceptions. However, we also highlight ethnic variation in mFG cut-off scores, suggesting that clinicians consider ethnicity in optimal diagnosis and personalised interventions.
Bizuneh, A.D., Joham, A.E., Tay, C.T., Kiconco, S., Earnest, A., Dhungana, R.R., et al. (2025). The PCOS Phenotype in Unselected Populations (P-PUP) study: Ethnic variation in population-based normative cut-offs for defining hirsutism. EUROPEAN JOURNAL OF ENDOCRINOLOGY, 192(3), 228-239 [10.1093/ejendo/lvaf030].
The PCOS Phenotype in Unselected Populations (P-PUP) study: Ethnic variation in population-based normative cut-offs for defining hirsutism
Gambineri, Alessandra;
2025
Abstract
Objective: Hirsutism, a diagnostic feature of polycystic ovary syndrome (PCOS), is often defined using arbitrary percentile cut-offs, rather than normative cut-offs from population-based data. We aimed to define normative cut-offs for hirsutism in diverse populations. Design: Unselected population-based cluster analysis of individual participant data (IPD). Methods: The PCOS Phenotype in Unselected Populations (P-PUP) study IPD asset of community-based studies, underwent k-means cluster analysis, of directly assessed hirsutism, using the modified Ferriman-Gallwey (mFG) visual scale. The primary outcome was ethnicity-specific normative cut-offs for the mFG score. Medians and cut-offs were compared across ethnic groups. Results: We included 9829 unselected, medically unbiased participants, aged 18 to 45 years from 12 studies conducted across eight countries including China, Iran, Italy, Nigeria, Russia, South Korea, Turkey, and the United States. The mFG cut-off scores for hirsutism on cluster analysis varied across ethnicities, ranging from 4 to 8. White Iranians had the highest cut-off score of 8, followed by White Italians and Black Africans of 7. Asian Han Chinese, White Russian, Turkish, and Black Americans shared a cut-off of 5; White Americans, Asian Koreans, Asian Russians, and Mixed Russians shared a cut-off of 4. Comparing medians and mFG cut-offs across ethnicities confirmed the same differences. Conclusion: This study confirms the 2023 International PCOS Guidelines recommendations defining hirsutism as an mFG score between 4-6 for the majority of populations studied, with few exceptions. However, we also highlight ethnic variation in mFG cut-off scores, suggesting that clinicians consider ethnicity in optimal diagnosis and personalised interventions.| File | Dimensione | Formato | |
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