Thermal ablation of small renal masses: intermediate outcomes from a Canadian center.
Bibliographic record
Abstract
INTRODUCTION: Cryoablation (CA) and radio frequency ablation (RFA) are nephron sparing procedures that destroy renal tissue in situ rather than by surgical removal. Both thermal ablative techniques are advocated in select patient population with a small renal mass and multiple comorbidities which may preclude major surgery. Unfortunately long term oncologic outcomes of these procedures are unknown. MATERIALS AND METHODS: We report oncologic outcomes following CA and RFA in patients with small renal masses, from a single center, during a 48 month follow up period. Thirty patients underwent thermal ablation of a small renal mass, 7 with RFA and 23 with CA. RESULTS: Median tumor size on preoperative CT was 2.6 cm ± 0.87 cm. Four patients experienced a loco-regional treatment failure and underwent subsequent radical nephrectomy. Two patients were diagnosed with metastatic renal cell cancer in the follow up period. Six patients died during the follow up period, five from unrelated cause and one from metastatic RCC (overall survival 80%, RCC-specific survival 96%). CONCLUSIONS: This study demonstrates low RCC recurrence rates and in combination with previously published reports supports the effectiveness of thermal ablation therapy as primary therapeutic option in a very specific patient population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".