Long-term results of salvage cryotherapy for prostate cancer.
Bibliographic record
Abstract
108 Background: The optimum treatment of Prostate cancer recurrence following external bean radiation therapy (EBRT) remains a controversial topic. The primary problem with comparing salvage techniques following EBRT is the lack of long term data. We reviewed the long- term overall survival, disease-specific survival and disease free survival of patients who have undergone salvage cryotherapy to the prostate gland. Methods: A retrospective analysis was performed on all patients undergoing salvage cryotherapy for locally recurrent prostate cancer after EBRT by a single surgeon at a single institution from 1995-2004. Patients preoperative, perioperative and postoperative data was reviewed and recorded. Should a patient no longer be followed by the urology service the Patients and the patient's primary care physician or urologist were contacted. Mortality data, PSA results, bone scan results and any details of hormone therapy were recorded for this study. Results: 187 patients were included in the current study from which 176 patients had records available for follow up giving a follow up rate of 94%. Mean follow up was 7.46 years (1-14 years). 52 patients were followed for greater than 10 years. Average time to prostate cancer recurrence in patients who developed recurred was 2.3 years and average time to hormone therapy in these patients was 2.8 years. Overall survival at 10 years was high at 87%. Risk factors for recurrence of tumour identified were presalvage PSA, preradiation and presalvage gleason score. Preradiation gleason score had little impact on survival. PSA nadir of >1.0ng/mL was highly predictive of early recurrence. Disease-free survival rates of between 39 and 64% depending on risk factors. Conclusions: Cryotherapy has a definite role in the management of prostate cancer, representing a minimally invasive salvage treatment with acceptable 10 year disease free survival (DFS) of upwards of 39% and specific groups attaining 10 year DFS of 64%. Presalvage PSA and Gleason score are the best predictors of disease recurrence, whilst preradiation gleason score did not correlate with risk of disease recurrence. A PSA Nadir greater than 1 ng/mL indicates a poor prognosis in which early ADT should be strongly considered. No significant financial relationships to disclose.
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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 | 0.001 |
| 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) | 0.002 | 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".