Switching from a GnRH agonist to a GnRH antagonist in prostate cancer patients: A systematic review and meta-analysis
Bibliographic record
Abstract
Introduction: We sought to address whether there are clinical responses when patients who are failing gonadotropin-releasing hormone (GnRH) agonist therapy are switched to degarelix. Androgen-deprivation therapy remains the backbone of treatment for disseminated prostate cancer and may be achieved with orchiectomy, GnRH agonists, or degarelix, a GnRH antagonist. Methods: To perform a systematic review and meta-analysis, a search of the BIOSIS Previews, Embase, International Pharmaceutical Abstracts, MEDLINE, and Google Scholar databases was performed using key terms. Quantitative meta-analysis was performed to provide a pooled estimate of prostate-specific antigen (PSA) response at three months. Results: Thirteen studies were identified, eight of which were included in the qualitative and quantitative analyses. Patient characteristics were broadly similar between the studies. Out of 155 patients across all included studies, 20 had stable PSA after the switch (12.9%), 14 had between 10‒30% decrease in PSA (9.0%), three had between 30‒50% decrease (1.9%), and 13 had more than 50% decrease (8.4%). Random effects meta-analysis of these data demonstrated a pooled response rate of 27.75 (95% confidence interval 18.9‒36.5%; I2=7.9%). Changes in testosterone levels following the switch could not be quantitatively assessed due to lack of sufficient data. Conclusions: Our results suggest that a switch to GnRH antagonist following progression on a GnRH agonist may result in a stable or decreased PSA at three months in about 30% of patients. This information should be considered among the potential options to discuss with patients with a rising PSA on GnRH agonist therapy.
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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 | 0.016 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.037 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".