The Clinical Activity of PD-1/PD-L1 Inhibitors in Metastatic Non–Clear Cell Renal Cell Carcinoma
Bibliographic record
Abstract
Abstract Programmed death 1 (PD-1) and PD ligand 1 (PD-L1) inhibitors have shown activity in metastatic clear cell renal cell carcinoma (ccRCC). Data on the activity of these agents in patients with non–clear cell RCC (nccRCC) or patients with sarcomatoid/rhabdoid differentiation are limited. In this multicenter analysis, we explored the efficacy of PD-1/PD-L1 inhibitors in patients with nccRCC or sarcomatoid/rhabdoid differentiation. Baseline and follow-up demographic, clinical, treatment, and radiographic data were collected. The primary endpoint was objective response rate. Secondary endpoints include time-to-treatment failure (TTF), overall survival (OS), and biomarker correlates. Forty-three patients were included: papillary (n = 14; 33%), chromophobe (n = 10; 23%), unclassified (n = 9; 21%), translocation (n = 3; 7%), and ccRCC with sarcomatoid differentiation (n = 7, 16%). Of those 43 patients, 11 patients (26%) had sarcomatoid and/or rhabdoid differentiation (n = 7 with ccRCC; n = 4 nccRCC). Overall, 8 patients (19%) objectively responded, including 4 patients (13%) who received PD-1/PD-L1 monotherapy. Responses were observed in patients with ccRCC with sarcomatoid and/or rhabdoid differentiation (n = 3/7, 43%), translocation RCC (n = 1/3, 33%), and papillary RCC (n = 4/14, 29%). The median TTF was 4.0 months [95% confidence interval (CI), 2.8–5.5] and median OS was 12.9 months (95% CI, 7.4–not reached). No specific genomic alteration was associated with clinical benefit. Modest antitumor activity for PD-1/PD-L1–blocking agents was observed in some patients with nccRCC. Further prospective studies are warranted to investigate the efficacy of PD-1/PD-L1 blockade in this heterogeneous patient population. Cancer Immunol Res; 6(7); 758–65. ©2018 AACR.
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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 | 0.000 | 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".