Primary tumor ablation in metastatic renal cell carcinoma
Bibliographic record
Abstract
BACKGROUND: The role of primary tumor ablation (pTA) in metastatic renal cell carcinoma (mRCC) is unknown. We compared pTA-treated mRCC patients to patients who underwent no local treatment (NLT), as well as patients who underwent cytoreductive nephrectomy (CN). METHODS: Within the Surveillance, Epidemiology, and End Results database (SEER, 2004-2020), we identified mRCC patients who underwent either pTA, NLT or CN. Endpoints consisted of overall survival (OM) and other-cause mortality (OCM). Propensity score 1:1 matching (PSM), multivariable cox regression models (OM), as well as, multivariable competing risk regressions (CRR) models (OCM) were used. RESULTS: We identified 27,087 mRCC patients, of whom 82 (0.3%) underwent pTA, 17,266 (64%) NLT and 9,739 (36%) CN. In comparisons of pTA vs. NLT mRCC patients addressing OM, after 1:1 PSM, median survival was 19 months for pTA vs. 4 months for NLT patients (multivariable HR 0.3, 95% CI 0.22-0.47, P < 0.001). No statistically significant OCM differences were recorded in multivariable CRR (HR 1.13 95%, CI 0.52-2.44, P = 0.8). In comparisons of pTA vs. CN, after 1:1 PSM, no statistically significant differences in OM (HR 1.22, 95% CI 0.81-1.83, P = 0.32), as well as OCM (HR 1.4, 95% CI 0.56-3.48, P = 0.5) were recorded. CONCLUSION: In mRCC patients, pTA is associated with significantly lower mortality compared to NLT. Interestingly, OM rates between pTA and CN mRCC patients do not exhibit statistically significant differences. This preliminary report may suggest that pTA may provide a comparable survival benefit to CN in highly selected mRCC patients.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 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".