Can Cytoreductive Nephrectomy Improve Outcomes of Nivolumab Treatment in Patients with Metastatic Clear-Cell Renal Carcinoma?
Bibliographic record
Abstract
Background: This study aimed to investigate the effect of cytoreductive nephrectomy (CN) on the survival outcomes of nivolumab used as a subsequent therapy after the failure of at least one anti-vascular endothelial growth factor (VEGF) agent in patients with metastatic clear-cell renal-cell carcinoma (ccRCC). Methods: We included 106 de novo metastatic ccRCC patients who received nivolumab after progression on at least one anti-VEGF agent. Multivariate Cox regression analysis was performed to investigate the factors affecting survival in patients receiving nivolumab. Results: Of the 106 de novo metastatic ccRCC patients, 83 (78.3%) underwent CN. There were no statistical differences between the two groups in terms of age, gender, Eastern Cooperative Oncology Group (ECOG) score, tumor size, International Metastatic RCC Database Consortium (IMDC) risk group, number of previous treatment lines, first-line anti-VEGF therapy, or metastasis sites (p = 0.137, p = 0.608, p = 0.100, p = 0.376, p = 0.185, p = 0.776, p = 0.350, and p = 0.608, respectively). The patients who received nivolumab with CN had a longer time to treatment discontinuation (TTD) [14.5 months, 95% confidence interval (CI): 8.6–20.3] than did those without CN 6.7 months (95% CI: 3.9–9.5) (p = 0.001). The median overall survival (OS) was 22.7 months (95% CI: 16.1–29.4). The patients with CN had a median OS of 22.9 months (95% CI: 16.3–29.4), while those without CN had a median OS of 8.1 months (95% CI: 5.6–10.5) (p = 0.104). In the multivariate analysis, CN [hazard ratio (HR): 0.521; 95% CI: 0.297–0.916; p = 0.024] and the IMDC risk score (p = 0.011) were statistically significant factors affecting TTD; however, the IMDC risk score (p = 0.006) was the only significant factor for overall survival. Conclusions: Our study showed that the TTD of nivolumab was longer in metastatic ccRCC patients who underwent cytoreductive nephrectomy.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".