Understanding Androgen Excess and Metabolic Issues in Women with PCOS

Dissecting Androgen Excess and Metabolic Dysfunction for an Integrated Systems Approach to Polycystic Ovary Syndrome Through the Assessment of Detailed Phenome and Metabolome Data

Observational Imperial College London · NCT03911297

This study is trying to find out how to predict metabolic problems in women with PCOS by looking at their health data and grouping them based on similar traits.

Quick facts

Study typeObservational
Enrollment1000 (estimated)
Ages18 Years to 70 Years
SexFemale
SponsorImperial College London Academic / other
Locations1 site (Birmingham, West Midlands)
Trial IDNCT03911297 on ClinicalTrials.gov

What this trial studies

This study focuses on women diagnosed with polycystic ovary syndrome (PCOS), a condition that affects 10% of women and is associated with metabolic disorders. The researchers aim to identify measurable parameters that can predict the risk of future metabolic diseases in these women by collecting and analyzing phenome and metabolome data. Using machine learning techniques, the study will categorize PCOS patients into distinct subsets based on shared characteristics, which may help in understanding their metabolic risks. The findings could lead to better risk assessment and management strategies for women with PCOS.

Who should consider this trial

Good fit: Ideal candidates for this study are women aged 18-70 with a suspected diagnosis of polycystic ovary syndrome.

Not a fit: Patients who are pregnant, breastfeeding, or have significant renal or hepatic impairment may not benefit from this study.

Why it matters

Potential benefit: If successful, this study could provide a way to identify women with PCOS who are at higher risk for metabolic diseases, allowing for earlier intervention and personalized treatment.

How similar studies have performed: Previous studies have successfully used similar approaches to identify distinct metabolic markers in other conditions, suggesting potential for success in this novel application.

Eligibility criteria

Show full inclusion / exclusion criteria
Inclusion Criteria:

* Women with a suspected diagnosis of polycystic ovary syndrome
* Age range 18-70 years
* Ability to provide informed consent

Exclusion Criteria:

* Pregnancy or breastfeeding at the time of planned recruitment
* History of significant renal (eGFR\<30) or hepatic impairment (AST or ALT \>two-fold above ULN; pre-existing bilirubinaemia \>1.2 ULN)
* Any other significant disease or disorder that, in the opinion of the Investigator, may either put the participant at risk because of participation in the study, or may influence the result of the study, or the participant's ability to participate in the study.
* Participants who have participated in another research study involving an investigational medicinal product in the 12 weeks preceding the planned recruitment
* Glucocorticoid use via any route within the last six months
* Current intake of drugs known to impact upon steroid or metabolic function or intake of such drugs during the six months preceding the planned recruitment
* Use of oral or transdermal hormonal contraception in the three months preceding the planned recruitment
* Use of contraceptive implants in the twelve months preceding the planned recruitment

Where this trial is running

Birmingham, West Midlands

Study contacts

How to participate

  1. Review the eligibility criteria above with your treating physician.
  2. Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
  3. Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions Polycystic Ovary Syndromepolycystic ovary syndromeandrogenssteroidsmetabolic riskpredictionstratified medicine
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.