Follicle-Stimulating Hormone (FSH) Levels During Androgen Deprivation Therapy Are Not Associated With Survival or Development of Castration-Resistant Prostate Cancer
Bibliographic record
Abstract
Background Follicle-stimulating hormone (FSH) dysregulation plays a potential role in prostate cancer progression. The objective of this study was to evaluate whether higher FSH levels during androgen deprivation therapy (ADT) for recurrent prostate cancer could predict the development of castration-resistant prostate cancer (CRPC), prostate cancer-specific survival (CSS), and overall survival (OS). Methods Serum FSH levels were measured in cryopreserved samples of the continuous ADT arm of the PR.7 trial, supplemented with analogous samples from a large contemporaneous biobank. Univariate and multivariate analyses assessed the relationship between FSH tertiles and time to CRPC, as well as CSS, and OS. Results A total of 172 patients were included in our analysis. Of these, 54 patients (31%) developed CRPC during the 9-year follow-up. Median FSH for the tertiles was 4.35, 6.13, and 11.32 mIU/mL. FSH tertiles were not significantly associated with the time to CRPC, or with CSS or OS. FSH levels were not a significant prognostic factor for these oncologic outcomes. Conclusion As previously reported, the use of gonadotropin-releasing hormone (GnRH) antagonists for ADT has significantly more suppression of FSH levels than GnRH agonists. Our results do not suggest that differences in circulating FSH 1 year following ADT initiation influence long-term oncologic outcomes or development of CRPC.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".