Publication date: 7 Jun 2023
What is already known about this subject:
- The diagnosis of polycystic ovary syndrome (PCOS) remains challenging with International guidelines prioritising accurate cut-offs for individual diagnostic features. These diagnostic cut-offs are currently based on arbitrary percentiles, often from poorly characterised cohorts, and are dependent on variable laboratory ranges defined by assay manufacturers, limiting diagnostic accuracy. Cluster analysis is the recommended approach for defining normative cut-offs within populations for clinical syndromes. Few PCOS adult studies have applied cluster analysis, with no studies in adolescents. We aimed to define normative cut-offs for individual PCOS diagnostic features in a community-based population of adolescents using cluster analysis.
What this study adds
- This analysis utilised data from the Menstruation in Teenagers Study, a sub-group of the Raine Study, which is a population based prospective cohort of 244 adolescents whose mean age at PCOS assessment was 15.2 years.
- K-means cluster analysis and receiver operating characteristics curves were used to define normative cut-offs for Ferriman Gallwey score (mFG), free testosterone (free T), free androgen index (FAI) and menstrual cycle length.
- Normative cut-offs for mFG, free T, FAI and menstrual cycle lengths were 1.0, 23.4 pmol/l, 3.6 and 29 days respectively. These corresponded to the 65th, 71st, 70th and 59th population percentiles respectively.
- We defined the normative diagnostic criteria cut-offs in this unselected adolescent population and showed that these cut-offs correspond to lower percentiles than conventional cut-offs. These findings highlight the pertinent need to re-define PCOS diagnostic cut-offs in adolescents. Validation is required in larger, multi-ethnic and well characterised adolescent cohorts.