Testosterone Suppression with Luteinizing Hormone‐Releasing Hormone (<scp>LHRH</scp>) Agonists in Patients Receiving Radiotherapy for Prostate Cancer
Bibliographic record
Abstract
OBJECTIVES: To characterize the probability of testosterone escape during a course of radiotherapy and androgen deprivation (ADT) in patients with prostate cancer, and examine predictors of testosterone escape, the prostate specific antigen (PSA) levels during testosterone escape, and the impact of testosterone escape on outcome. PATIENTS AND METHODS: To participate in the database review, necessary data included: (i) type of luteinizing hormone-releasing hormone agonist (LHRHa) administered, date of initiation, and date of cessation or duration of therapy, (ii) radiotherapy information (start date and dose) with at least 6 months of follow-up after radiotherapy, (iii) radiotherapy to the prostate or prostate bed, and (iv) at least one serum testosterone and PSA measurement. RESULTS: Five hundred sixty patients in the database were identified as being treated with radiotherapy and ADT. Three hundred seventy-five patients had at least one measurement of testosterone and PSA, and the type of LHRHa used could be determined in 361 patients. Median follow-up of patients still living was 4.7 years. The median number of testosterone measurements per patient was six. The incidence of testosterone escape per patient course of treatment was buserelin, 9.3%; goserelin, 10.5%; intramuscular leuprolide, 11.5%; leuprolide subcutaneous, 23.9%; and triptorelin, 6.7% (p = 0.02). There was no difference in either biochemical failure-free survival or overall survival in patients stratified by testosterone escape. The modal PSA level during a testosterone escape was an undetectable PSA. CONCLUSIONS: An undetectable PSA does not rule out the presence of higher than desired levels of testosterone during ADT. In this cohort of patients, there appears to be no impact of testosterone escape on either biochemical relapse-free survival or overall survival.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".