Differences in other-cause mortality in metastatic renal cell carcinoma according to partial vs. radical nephrectomy and age: A propensity score matched study
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: It is unknown whether the benefit from partial nephrectomy regarding lower other-cause mortality is applicable to older patients with metastatic renal cell carcinoma. MATERIALS AND METHODS: Using Surveillance Epidemiology and End Results database, patients with metastatic renal cell carcinoma, undergoing partial or radical nephrectomy, were stratified according to age (<60, 60-69, and ≥70 years). After propensity score matching, Kaplan-Meier survival analyses and multivariable Cox regression models were used. RESULTS: Of 2,390 patients with metastatic renal cell carcinoma, 885 (37%) were aged <60 years, and 90 (10%) underwent partial nephrectomy; 824 (34%) were aged 60-69 years, and 61 (7%) underwent partial nephrectomy; and 681 (29%) were aged ≥70 years, and 64 (9%) underwent partial nephrectomy. After propensity score matching, in patients aged <60 years, partial nephrectomy was associated with lower other-cause mortality (hazard ratio 0.22; p = 0.02); in patients aged 60-69 years, partial nephrectomy was associated with lower other-cause mortality (hazard ratio 0.38; p = 0.03); but not in patients aged ≥70 years. DISCUSSION: In metastatic renal cell carcinoma, partial nephrectomy is associated with lower other-cause mortality in patients aged <60 years and in patients aged 60-69 years, but not in patients aged ≥70 years. In consequence, consideration of partial nephrectomy might be of great value in younger metastatic renal cell carcinoma patients.
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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 | 0.000 | 0.001 |
| 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) | 0.000 | 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 it