Therapies in Refractory Metastatic Renal Cell Carcinoma
Bibliographic record
Abstract
As the therapeutic landscape for metastatic clear cell renal cell carcinoma (mccRCC) expands to include vascular endothelial growth factor receptor tyrosine kinase inhibitors (VEGFR TKIs) and immunotherapies, new challenges are in place for evaluating and treating refractory disease. Assessing and managing refractory disease has several elements: (1) the mechanism(s) of front-line treatment, (2) timing of progressive disease, (3) rapidity and sites of progressing disease, (4) use of adjuvant therapy, and (5) incorporation of surgical and radiation techniques. These variables all have distinct impact on the biology of refractory or resistant mccRCC. A better understanding of the essential mechanisms of both primary and secondary immunotherapy resistance will inform biomarker development and therapeutic strategies in the refractory setting. This paper addresses the current understanding of treatment sequencing in refractory mccRCC, focusing on treatment options with prospective clinical trial data, considers refractory mccRCC after adjuvant immunotherapy, and incorporates radiation or surgical resection for oligoprogressive disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".