Cytoreductive nephrectomy in metastatic papillary renal cell carcinoma: Results from the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC).
Bibliographic record
Abstract
581 Background: There is evidence that cytoreductive nephrectomy (CN) may be beneficial in metastatic renal cell carcinoma (mRCC), but the role of CN in patients with papillary histology is unclear. Methods: Using the IMDC database, a retrospective analysis was performed on patients with papillary mRCC treated with or without CN. Baseline characteristics and IMDC risk factors were collected. Median overall survival (OS) was determined for both patient groups. Multivariable Cox regression analysis was performed to control for imbalances in individual IMDC risk factors. Results: In total, 353 patients with papillary mRCC with (n = 75) or without (n = 278) a component of clear cell histology were identified. Median follow-up time was 57.1 months (95% CI 32.9-77.8) and the OS from the start of first-line targeted therapy for the entire cohort was 13.2 months (95% CI 12.0-16.1). Baseline characteristics are in Table 1 and patients who had CN were more likely to be younger, with better KPS, and have sarcomatoid histology. Median OS in patients with CN was 16.3 months (95% CI 13.1-19.2), compared to 8.6 months (95% CI 6.1-12.2; p < 0.0001) in the no CN group. When adjusted for individual IMDC risk factors, the hazard ratio (HR) of death for CN was 0.62 (95% CI 0.45-0.85; p = 0.0031). Conclusions: The use of CN in patients with mRCC and papillary histology appears to be associated with improved survival when compared to no CN after adjustment for risk criteria. A clinical trial in this rare population may not be possible but this data does corroborate with clear cell literature. [Table: see text]
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".