Primary cryoablation for Gleason 8, 9, or 10 localized prostate cancer: Biochemical and local control outcomes from the Cryo OnLine database registry
Bibliographic record
Abstract
INTRODUCTION AND OBJECTIVE: The increased use of cryoablation as an initial treatment for localized high-grade prostate cancer has been due to many factors including reports that cell kill from exposure to cryogenic temperatures is independent of cellular dedifferentiation and Gleason score. The objective of this study is to report the outcomes of primary cryoablation when used to treat Gleason 8, 9, or 10 localized prostate cancer at a large number of centers. MATERIALS AND METHODS: Data from 1608 patients who underwent primary cryoablation at 27 centers were collected using the Cryo OnLine Database (COLD) registry. This analysis considers only the 77 patients who had a Gleason score of at least 8 and a minimum of 24 months of follow-up. Biochemical failure was defined according to both the original ASTRO definition (three rises) and the 2006 updated ASTRO (Phoenix) definition of nadir + 2. Biopsy was performed at the physician's discretion, but most commonly if a patient had a rising or suspicious prostate specific antigen (PSA). RESULTS: The average age at treatment was 69.6 +/- 8.2 years. Pretreatment PSA was 16.2 +/- 17.9 ng/ml and the average Gleason was 8.5 +/- 0.6. Patients were followed for 39.0 +/- 18.8 months (range: 24-120 months) and 5-year follow-up was available for 12 patients. Eight-seven percent of the patients achieved a PSA nadir < 0.4 ng/ml. Five-year actuarial biochemical survivals was 64.4 +/- 6.0% and 44.6 +/- 8.0% for the ASTRO and Phoenix definitions, respectively. A total of 47 underwent posttreatment biopsy. Of these, 12 showed evidence of disease resulting in a positive biopsy rate for those who underwent biopsy of 25.5%. This yields a positive biopsy rate of the entire population of 15.6% (12/77). CONCLUSIONS: Cryoablation, as a primary treatment for high-grade Gleason prostate cancer practiced over a wide spectrum of users provides definable biochemical and local control for a hard to manage patient population with aggressive disease.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".