Outcome of metastatic sarcomatoid renal cell carcinoma (sRCC): Results from the International mRCC Database Consortium.
Bibliographic record
Abstract
4565 Background: Sarcomatoid differentiation in metastatic RCC (sRCC) is associated with poor prognosis. Robust data regarding outcome in the targeted therapy era is lacking. Methods: Clinical features, prognostic factors, and treatment outcomes in mRCC patients with and without sarcomatoid histology treated with targeted therapy were retrospectively analyzed and compared. Results: 2,286 patients were identified (non-sRCC(n=2,056); sRCC(n=230)). sRCC patients had significantly worse Heng prognostic group distribution compared to non-sRCC (11% vs 19% favorable risk, 49% vs 57% intermediate risk, and 40% vs 24% poor risk; p<0.0001). Time from original diagnosis to relapse (excluding synchronous metastatic disease) in the sRCC patients was 18.8 months compared to 42.9 months in non-sRCC group; p<0.0001. There was no significant difference in the incidence of CNS metastases (6-8%) or underlying clear cell histology (87-88%). Greater than 93% of patients received VEGF inhibitors as first line therapy; 21% achieved an objective response in the sRCC group as compared to 26% in the non-sRCC group with significantly more sRCC patients (43% vs. 21%) having primary refractory disease (p<0.0001, for both). sRCC patients had significantly less use of second-line (p=0.018) and third-line (p=0.0004) systemic therapy. The median PFS / OS was 4.5 months / 10.4 months in sRCC patients and 7.8 months / 22.5 months in non-sRCC patients (p<0.0001 for both). Sarcomatoid histology was associated with a significantly worse PFS and OS after adjusting for the individual Heng risk factors in multivariable analysis (HR 1.5, p<0.0001 for both). Conclusions: Patients with sRCC have worse baseline prognostic criteria, a shorter time to relapse and worse clinical outcome to targeted therapy compared to patients with non-sRCC. Additional insight into the biology of sRCC is needed to develop alternative therapeutics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| 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 teacher head, 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".