Are There Any Sensitive and Specific Sex Steroid Markers for Polycystic Ovary Syndrome?
Bibliographic record
Abstract
CONTEXT: Despite the high prevalence of hyperandrogenemia, the principal biochemical abnormality in women with polycystic ovary syndrome (PCOS), a definitive endocrine marker for PCOS has so far not been identified. OBJECTIVE: To identify a tentative diagnostic marker for PCOS, we compared serum levels of sex steroids, their precursors, and main metabolites in women with PCOS and controls. DESIGN AND METHODS: In this cross-sectional study of 74 women with PCOS and 31 controls, we used gas and liquid chromatography/mass spectrometry to analyze serum sex steroid precursors, estrogens, androgens, and glucuronidated androgen metabolites; performed immunoassays of SHBG, LH, and FSH; and calculated the LH/FSH ratio. RESULTS: Androgens and estrogens, sex steroid precursors, and glucuronidated androgen metabolites were higher in women with PCOS than in controls. In multivariate logistic regression analyses, estrone and free testosterone were independently associated with PCOS. The odds ratios per sd increase were 24.2 for estrone [95% confidence interval (CI), 4.0-144.7] and 12.8 for free testosterone (95% CI, 3.1-53.4). In receiver operating characteristic analyses, the area under curve was 0.93 for estrone (95% CI, 0.88-0.98) and 0.91 for free testosterone (95% CI, 0.86-0.97), indicating high sensitivity and specificity. CONCLUSION: Women with PCOS have elevated levels of sex steroid precursors, estrogens, androgens, and glucuronidated androgen metabolites as measured with a specific and sensitive mass spectrometry-based technique. The combination of elevated estrone (>50 pg/ml) and free testosterone (>3.3 pg/ml) appeared to discriminate with high sensitivity and specificity between women with and without PCOS.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".