The evolving role of cytoreductive nephrectomy in metastatic renal cell carcinoma
Bibliographic record
Abstract
PURPOSE OF REVIEW: To review the evidence related to cytoreductive nephrectomy in metastatic renal cell carcinoma (mRCC) treated in the targeted therapy era, with a focus on observational studies and randomized trials. RECENT FINDINGS: A number of retrospective observational studies exploring the role of cytoreductive nephrectomy have been reported. These have suggested an association between cytoreductive nephrectomy and survival, with hazard ratio estimates ranging from 0.39 to 0.68 in favour of cytoreductive nephrectomy. In contrast, the CARMENA randomized trial demonstrated that sunitinib alone was noninferior to cytoreductive nephrectomy followed by sunitinib in intermediate-risk and poor-risk patients. The results of the SURTIME trial suggest that initial sunitinib followed by a deferred cytoreductive nephrectomy may also be a reasonable approach in select patients. SUMMARY: On the basis of the evidence to date, there is still a role for cytoreductive nephrectomy in the multimodality treatment of mRCC. Careful patient selection is of paramount importance and discussion in multidisciplinary tumour boards is encouraged. As the treatment landscape of mRCC continues to change, the role of cytoreductive nephrectomy in the modern immuno-oncology era will need to be explored.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".