Long-term Outcomes After Surgical Resection of Pancreatic Metastases from Renal Clear-Cell Carcinoma
Bibliographic record
Abstract
BACKGROUND: Pancreatic metastases (PM) from renal cell carcinoma (RCC) are uncommon. We herein describe the long-term outcomes associated with pancreatectomy at two academic institutions, with a specific focus on 10-year survival. METHODS: This investigation was limited to patients undergoing pancreatectomy for PM between 2000 and 2008 at the University of Verona and Memorial Sloan Kettering Cancer Center, allowing a potential for 10 years of surveillance. The probabilities of further RCC recurrence and RCC-related death were estimated using a competing risk analysis (method of Fine and Gray) to account for patients who died of other causes during follow-up. RESULTS: The study population consisted of 69 patients, mostly with isolated metachronous PM (77%). The median interval from nephrectomy to pancreatic metastasectomy was 109 months, whereas the median post-pancreatectomy follow-up was 141 months. The 10-year cumulative incidence of new RCC recurrence was 62.7%. In the adjusted analysis, the relative risk of repeated recurrence was significantly higher in PM synchronous to the primary RCC (sHR = 1.27) and in patients receiving extended pancreatectomy (sHR = 3.05). The 10-year cumulative incidence of disease-specific death was 25.5%. The only variable with an influence on disease-specific death was the recurrence-free interval following metastasectomy (sHR = 0.98). In patients with repeated recurrence, the 10-year cumulative incidence of RCC-related death was 35.4%. CONCLUSION: In a selected group of patients followed for a median of 141 months and mostly with isolated metachronous PM, resection was associated with a high possibility of long-term disease control in surgically fit patients with metastases confined to the pancreas.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".