Outcome of Patients with Renal Cell Carcinoma and Multiple Glandular Metastases Treated with Targeted Agents
Bibliographic record
Abstract
PURPOSE: Pancreatic metastases (PM) from renal cell carcinoma (RCC) have been associated with long-term survival. The aim of this study was to evaluate the outcome of RCC patients with multiple glandular metastases (MGM) treated with targeted therapies (TTs). METHODS: Sixty-four MGM patients treated between 1993 and 2014 were retrospectively identified from a database of 274 RCC patients with PM from 11 European centers. The survival of MGM patients was compared with that of both patients with PM only and a cohort of 325 RCC patients with non-GM (control group) treated with TTs. Survival was estimated using the Kaplan-Meier method and was statistically compared using the log-rank test. RESULTS: Fifty-six patients (88%) had at least 2 MGM, 7 patients (11%) had 3 MGM and 1 patient had 4 MGM, while non-GM were present in the remaining patients. The median overall survival (OS) was 54.2 months for MGM and 73.4 months for patients with PM only. The median OS in the control group was 22.7 months and statistically inferior to both MGM (p < 0.001) and PM patients (p < 0.001). CONCLUSION: MGM from RCC are associated with a remarkable survival. Despite some limitations, these findings suggest that GM might be considered a predictor of a favorable prognosis.
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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 | 0.000 |
| 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".