Association of preoperative serum De Ritis ratio with oncological outcomes in patients treated with cytoreductive nephrectomy for metastatic renal cell carcinoma
Bibliographic record
Abstract
PURPOSE: Identifying which patients are likely to benefit from cytoreductive nephrectomy (CN) for metastatic renal cell carcinoma (mRCC) is important. We tested the association between preoperative serum De Ritis ratio (DRR, Aspartate Aminotransferase/Alanine Aminotransferase) and overall survival (OS) as well as cancer-specific survival (CSS) in mRCC patients treated with CN. MATERIAL AND METHODS: mRCC patients treated with CN at different institutions were included. After assessing for the optimal pretreatment DRR cut-off value, we found 1.2 to have the maximum Youden index value. The overall population was therefore divided into 2 DRR groups using this cut-off (low, <1.2 vs. high, ≥1.2). Univariable and multivariable Cox regression analyses tested the association between DRR and OS as well as CSS. The discrimination of the model was evaluated with the Harrel's concordance index (C-index). The clinical value of the DRR was evaluated with decision curve analysis. RESULTS: Among 613 mRCC patients, 239 (39%) patients had a DRR ≥1.2. Median follow-up was 31 (IQR 16-58) months. On univariable analysis, high DRR was significantly associated with OS (hazard ratios [HR]: 1.22, 95% confidence interval [CI]: 1.01-1.46, P = 0.04) and CSS (HR: 1.23, 95% CI: 1.02-1.47, P = 0.03). On multivariable analysis, which adjusted for the effect of established clinicopathologic features, high DRR remained significantly associated with both OS (HR: 1.26, 95% CI: 1.04-1.52, P = 0.02) and CSS (HR: 1.26, 95% CI: 1.05-1.53, P = 0.01). The addition of DRR only minimally improved the discrimination of a base model that included established clinicopathologic features (C-index = 0.633 vs. C-index = 0.629). On decision curve analysis, the inclusion of DRR did not improve the net-benefit beyond that obtained by established subgroup analyses stratified by IMDC risk groups, type of systemic therapy, body mass index and sarcomatoid features, did not reveal any prognostic value to DRR. CONCLUSION: Despite the statistically significant association between DRR and OS as well as CSS in mRCC patients treated with CN, DRR does not seem to add any further prognostic value beyond that obtained by currently available features.
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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 | 0.000 |
| 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) | 0.001 | 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".