Addition of Salvage Immunotherapy to Targeted Therapy in Patients with Metastatic Renal Cell Carcinoma
Bibliographic record
Abstract
There have been significant advances in the treatment of metastatic renal cell carcinoma (mRCC), with immunotherapy (IO)-based combinations as the standard-of-care treatment in the front-line setting. IO in this setting is paired with another IO agent or with a vascular endothelial growth factor receptor (VEGF-R) tyrosine kinase inhibitor (TKI). One IO/IO combination and four IO/TKI combinations are currently approved. However, the role of the salvage IO in patients with disease progression on TKI monotherapy is uncertain. Here, we present a case series of five patients who were on single-agent TKI therapy for treatment-refractory mRCC and upon disease progression had an IO agent added to their TKI. The median duration of TKI monotherapy was 11.2 months (range, 1.7-31.1 months), and the median duration of response after the addition of IO was 4 months (range, 2.8-10.5 months). Although IO salvage therapy has a plausible rationale, this case series did not show a clear benefit to this approach. Further clinical trials are needed to determine the clinical utility of IO salvage therapy in mRCC.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".