Combining Radiotherapy with Immunocheckpoint Inhibitors or CAR-T in Renal Cell Carcinoma
Bibliographic record
Abstract
Radiotherapy is considered a second life in Renal Cell Carcinoma (RCC) patients, mainly due to the introduction of immune checkpoint inhibitors, such as anti-Programmed-death (PD)-1, alone or in combination with anti-Cytotoxic T-Lymphocyte Antigen (CTLA)-4. Several trials are investigating the efficacy/safety of immune checkpoint inhibitors in sequential or combined strategies with radiotherapy. Chimeric Antigen Receptor (CAR)-T cells therapy as a promising approach in cancer patients has opened the way to novel possibilities of integrating therapies. The identification of biomarkers of tumor response to these combinations represents a challenge in RCC, together with the research for the best partner for immunotherapy in metastatic patients. In this review we illustrated preclinical/clinical data on the integration of radiotherapy with immunocheckpoint inhibitors or CART cells in RCC.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".