The Survival Outcomes of the Metastatic Nonclear Cell Renal Cell Carcinoma in the Immunotherapy Era: Princess Margaret Cancer Centre Experience
Bibliographic record
Abstract
Immunotherapy (IO) with or without targeted therapy (TT) is the standard treatment for patients with metastatic clear cell renal cell carcinoma (RCC). The evidence supporting their use in metastatic nonclear cell renal cell carcinoma (nccRCC) subtypes is based on small prospective trials and retrospective analyses. Here, we report survival outcomes for patients with metastatic nccRCC treated with IO and/or TT at the Princess Margaret Cancer Centre, Toronto, ON, Canada. Demographics, disease characteristics, and survival outcomes were collected retrospectively. Overall (OS), progression-free survival (PFS), and objective response rates (ORR) were calculated. We identified 69 patients with metastatic nccRCC treated with IO and/or TT as the first-line treatment, and 36 (52.1%) patients as the second-line treatment. Median OS of the first line IO recipients (n = 12) and non-IO recipients (n = 57) was not reached (NR) and 17.2 months (95% confidence interval (95% CI): 7.3-27.0; P = 0.23), respectively. Median PFS of first-line IO recipients and non-IO recipients was NR and 4.7 months (95% CI: 3.7-5.6; P = 0.019), respectively. The ORR of IO recipients versus non-IO recipients was 50% versus 12.3% (P = 0.007). Median OS of the second-line IO recipients (n = 8) and non-IO recipients (n = 28) was NR and 6.3 months (95% CI: 3.2-9.3; P = 0.003), respectively. Median PFS of second-line IO recipients and non-IO recipients was 4.8 months (95% CI: 2.7-6.8) and 2.8 months (95% CI: 1.8-3.7; P = 0.014), respectively. ORR of IO recipients and non-IO recipients was 37.5% and 3.5%, respectively; P = 0.028. While the number of patients included in our retrospective review was small, our analysis suggested that patients with nccRCC have improved survival outcomes with IO treatment. Validation of prospective dataset is required before widespread clinical utilization.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".