Use of cyproterone acetate/ethinylestradiol in polycystic ovary syndrome: rationale and practical aspects
Bibliographic record
Abstract
INTRODUCTION: Polycystic ovary syndrome (PCOS) is a common, heterogeneous disorder characterised by hyperandrogenic skin symptoms, irregular menstruation and subfertility, increased risk of endometrial malignancy, and increased risk of preventable diseases associated with metabolic syndrome. Cyproterone acetate (CPA) 2 mg, combined with ethinylestradiol (EE) 35 μg, is indicated for the treatment of moderate to severe acne related to androgen-sensitivity (with or without seborrhea) and/or hirsutism, in women of reproductive age. OBJECTIVES: To review the present knowledge about PCOS and summarize the role of CPA/EE in the care of patients suffering from this condition for the practitioner. METHODS: Experts with clinical interest and experience in treating symptoms of androgen excess performed a non-systematic review to provide updated information regarding the use of CPA/EE in patients with PCOS. RESULTS: Polycystic ovary-related hyperandrogenic skin symptoms are effectively treated by CPA/EE, reducing not only the symptoms but also their negative impact on quality of life and mental health. Proven additional benefits for these patients include the treatment of menstrual irregularities and reduction in endometrial cancer risk. Possible benefits include preservation of fertility. Treatment increases the risk for venous thromboembolic complications. The nature of other metabolic and cardiovascular long-term effects i.e., whether positive or negative, are still to be investigated. CONCLUSIONS: Cyproterone acetate/ethinylestradiol provides effective treatment for PCO-related hyperandrogenic skin symptoms. This efficacy and additional benefits related to menstrual irregularities and endometrial cancer risk, have to be weighed against the risk of venous thromboembolic complications based on an individual benefit/risk evaluation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".