Cryosurgery Versus Primary Androgen Deprivation Therapy for Locally Recurrent Prostate Cancer After Primary Radiotherapy: A Propensity-Matched Survival Analysis
Bibliographic record
Abstract
Background Optimal management of isolated local recurrence of prostate cancer after primary radiotherapy remains to be defined. Up-front androgen deprivation therapy (ADT) is widely used but may adversely affect the quality of life and is essentially a palliative treatment. Local salvage carries a different side-effect profile and is potentially curative, but it has not been compared to ADT. Materials and methods We conducted a propensity-matched analysis of cohorts of men treated with either whole gland cryotherapy (CRYO) or primary ADT following the diagnosis of locally recurrent prostate cancer. Our specific objectives were to compare overall survival (OS) and prostate cancer-specific mortality (PCSM) between CRYO vs. ADT. Results After a one-to-one matching, 169 patients from each cohort were included in comparisons. Median follow-up time was 6.7 years (ADT) vs. 18 years (CRYO). The 10-year PCSM was 18.5% (ADT) vs. 16.2% (CRYO), which was not statistically different [hazard ratioo (HR): 0.69, 95% CI: 0.36-1.34, p=0.27]. The median OS was 12.3 years (CRYO) versus 10.2 years (ADT) (HR: 0.63, 95% CI: 0.42-0.95, p=0.03). Conclusions While PCSM was similar between the two strategies, CRYO was associated with a longer OS compared to primary ADT. Given the retrospective nature of the trial, these results should be considered hypothesis-generating, and phase III trials comparing these two options are required to further explore these findings.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".