RESULTS OF SALVAGE CRYOABLATION OF THE PROSTATE AFTER RADIATION: IDENTIFYING PREDICTORS OF TREATMENT FAILURE AND COMPLICATIONS
Bibliographic record
Abstract
PURPOSE: We conduct a critical evaluation of cryoablation of prostate cancer after failure of full dose radiotherapy to identify predictors of treatment failure and complications. MATERIALS AND METHODS: A total of 125 cryoablation procedures were performed in 118 patients with proved local recurrence after full dose radiotherapy. Followup includes serial prostate specific antigen (PSA) and biopsy at 6,12 and 24 months. Kaplan-Meier plots were constructed for different PSA cutoffs. We separately analyzed different cohorts based on T stage, Gleason score, PSA before cryoablation and endocrine therapy status. RESULTS: Of the 118 patients 114 had serum PSA nadir less than 0.5 ng./ml. Median followup was 18.6 months (range 3 to 54). Of the biopsy cores 3.1% (23 of 745) from 7 patients contained persistent viable cancer. Kaplan-Meier plots showed patients free of histological failure leveling at 87% and free from biochemical failure at 68%, 55% and 34%, respectively, with PSA greater than 4, 2 and 0.5 ng./ml. PSA greater than 10 ng./ml. before cryoablation, Gleason score 8 or greater before radiation and stage T3/T4 disease appeared to predict an unfavorable biochemical outcome. Serious complications included 4 rectourethral fistulas (3.3%) and severe incontinence (6.7%). Strong predictors of complications included bulky disease for fistulas and prior transurethral surgery. CONCLUSIONS: Salvage cryoablation after radiation can achieve reasonable biochemical and histological results with acceptable morbidity. Cryoablation appears to be a reasonable treatment option for this patient population with few viable therapeutic options, provided vigorous patient selection criteria are adhered to.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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".