Unusual Metastases in Renal Cell Carcinoma: A Single Institution Experience and Review of Literature
Bibliographic record
Abstract
BACKGROUND: To report location and management of atypical metastases from renal cell carcinoma (RCC) in the Instituto Nacional de Ciencias Medicas e Investigacion Salvador Zubiran (INCMNSZ) in Mexico City. METHODS: Between 1987 to 2009, 545 patients with RCC were retrospectively identified at the INCMNSZ. Patients with unusual metastases confirmed by histopathology were analyzed. Epidemiological, clinical, diagnosis, treatment and outcome data were reviewed. RESULTS: Sixty patients developed 98 unusual metastases secondary to RCC. The group was comprised of 35 men (58.3%), with a median age of 60 years at diagnosis. Metachronous unusual metastases with primary renal cancer were observed in 37 individuals (61.7%). Median time from primary RCC diagnosis to the first unusual metastasis was 16.5 months. Median survival from diagnosis of the first unusual metastasis to death was 5.0 months (CI 95%: 2.8-7.2 months). Patients with an initial solitary metastatic lesion in an unusual site (28.3%) had a better survival compared to patients who primarily presented with multiple metastases, 17.0 (CI 95%: 6.1-27.9) Vs 3.0 months (CI 95%: 0.9-5.1), p = 0.001. Unusual metastasis resection (21 patients) improved survival, 25.0 (CI 95%: 5.1-44.9) Vs 3.0 months (CI 95%: 0.8-5.2), p < 0.0001. No survival difference was observed between localization of unsual metastases (p = 0.72). CONCLUSIONS: In patients with advanced RCC we suggest an individual diagnostic and surgical approach to achieve complete resection with disease-free margins, even in the presence of unusual metastatic sites, multifocality, or history of metastasectomy. These strategy might provide not only palliation for symptoms, but an opportunity for meaningful disease free and overall survival.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".