Nodal involvement at nephrectomy is associated with worse survival: A stage‐for‐stage and grade‐for‐grade analysis
Bibliographic record
Abstract
OBJECTIVES: To examine cancer-specific mortality in patients with nodal metastases relative to patients without nodal involvement at nephrectomy for non-metastatic renal cell carcinoma in a population-based cohort. METHODS: A total of 11 374 non-metastatic renal cell carcinoma patients who underwent a lymph node dissection at nephrectomy were identified using the Surveillance, Epidemiology and End Results database (1988-2008). The 5-year cancer-specific mortality-free survival rates were examined according to the presence or absence of nodal involvement within the entire cohort, and stratified according to pathological tumor stage (pT1 vs pT2 vs pT3 vs pT4) and Fuhrman grade (I vs II vs III vs IV). Cox regression analyses for prediction of cancer-specific mortality were modeled to assess the effect of nodal metastases versus no nodal involvement in the entire population. Finally, separate Cox regression models were fitted within each pathological stage and grade. RESULTS: Overall, 1260 (11%) patients had nodal metastases at nephrectomy. The overall 5-year cancer-specific mortality-free survival rates were 38.4 versus 83.8% in patients with nodal metastases and without nodal metastases, respectively. In multivariable analyses, amongst pT1, pT2, pT3 and pT4, patients with nodal metastases were 6.0-, 3.6-, 3.2- and 2.0-fold, respectively, more likely to die after nephrectomy (all P < 0.001). Similarly, amongst Fuhrman grade I, Fuhrman grade II, Fuhrman grade III and Fuhrman grade IV, patients with nodal metastases were 3.9-, 3.5-, 3.1- and 2.7-fold, respectively, more likely to die of cancer-specific mortality (all P < 0.001). CONCLUSIONS: Nodal involvement is an important determinant of higher cancer-specific mortality after nephrectomy. The detrimental effect of nodal metastases is particularly strong amongst patients with low-stage or low-grade non-metastatic renal cell carcinoma.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".