Cancer-specific mortality free survival rates in non-metastatic non-clear cell renal carcinoma patients at intermediate/high risk of recurrence
Bibliographic record
Abstract
BACKGROUND: To date, five trials testing the effect of adjuvant systemic therapy in surgically treated non-metastatic renal cell carcinoma included patients with non-clear cell histology. We tested the effect of papillary vs. chromophobe histological subtype, stage, and grade on 10-year cancer-specific survival, in patients eligible for ≥1 such trial. METHODS: We identified patients meeting ASSURE, SORCE, EVEREST, PROSPER, or RAMPART trial inclusion criteria in the SEER (2000-2018) database. Kaplan-Meier analyses estimated 10-year survival rates and multivariable Cox regression models tested for the independent predictor status of histological subtype, stage, and grade. RESULTS: We identified 5465 (68%) papillary and 2562 (32%) chromophobe renal cell carcinoma patients. Cancer-specific survival rates at 10 years were 77% in papillary vs. 90% in chromophobe. In multivariable Cox regression models applied to papillary patients, cancer-specific mortality independent predictor status was reached for T3G3-4 (HR 2.9), T4Gany (HR 3.4), TanyN1G1-2 (HR 3.1), and TanyN1G3-4 (HR 8.0, P<0.001), relative to T1/2Gany. In multivariable Cox regression models applied to chromophobe patients, mortality independent predictor status was reached for T3G3-4 (HR 3.6), T4Gany (HR 14.0), TanyN1G1-2 (HR 5.7), and TanyN1G3-4 (HR 15.0, P<0.001), relative to T1/2Gany. CONCLUSIONS: In surgically treated non-metastatic intermediate/high-risk renal cell carcinoma patients, papillary histologic subtype exhibited worse cancer-specific survival than chromophobe histologic subtype. Although stage and grade represented independent predictors in both histological subtype groups, the magnitude of their effect was invariably worse in chromophobe than in papillary patients. In consequence, papillary and chromophobe patients should be considered separate entities instead of being combined under the non-clear cell designation.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".