Adjuvant therapy in patients with sarcomatoid renal cell carcinoma: <i>post hoc</i> analysis from Eastern Cooperative Oncology Group‐American College of Radiology Imaging Network (ECOG‐ACRIN) E2805
Bibliographic record
Abstract
OBJECTIVES: To study the effects of adjuvant therapy in patients with sarcomatoid renal cell carcinoma (sRCC) enrolled in the randomised phase III clinical trial E2805. PATIENTS AND METHODS: The original trial (E2805) was a randomised, double-blinded phase III clinical trial comparing outcomes in 1943 patients with RCC accrued between 2006 and 2010 and treated with up to 1 year of adjuvant placebo, sunitinib, or sorafenib. The present study analyses the cohort of patients with sRCC that participated in E2805. RESULTS: A total of 171 patients (8.8%) had sarcomatoid features. Of these, 52 patients received sunitinib, 58 received sorafenib, and 61 received placebo. Most patients were pT3-4 (71.1%, 63.7%, and 70.5%, respectively); 17.3%, 19.0%, and 27.9% had pathologically positive lymph nodes; and 59.6%, 62.1%, and 62.3% of the patients were University of California Los Angeles (UCLA) Integrated Staging System (UISS) very-high risk. In 49% of patients with subsequent development of metastatic disease, recurrence occurred in the lung, followed by 30% in the lymph nodes, and 13% in the liver. There was a high local recurrence rate in the renal bed (16%, 29%, and 18%, respectively). The 5-year disease-free survival (DFS) rates were 33.6%, 36.0%, and 27.8%, for sunitinib, sorafenib and placebo, respectively (hazard ratio [HR] 0.74, 95% confidence interval [CI] 0.45-1.20 for sunitinib vs placebo, and HR 0.82, 95% CI 0.53-1.28 for sorafenib vs placebo). CONCLUSIONS: Adjuvant therapy with sunitinib or sorafenib did not show an improvement in DFS or OS in patients with sRCC.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".