Prognostic effect of preoperative serum albumin to globulin ratio in patients treated with cytoreductive nephrectomy for metastatic renal cell carcinoma
Bibliographic record
Abstract
Background: Accurate identification of ideal candidates for cytoreductive nephrectomy (CN) for metastatic renal cell carcinoma (mRCC) is an unmet need. We tested the association between preoperative value of systemic albumin to globulin ratio (AGR) and overall survival (OS) as well as cancer-specific survival (CSS) in mRCC patients treated with CN. Methods: mRCC patients treated with CN were included. The overall population was therefore divided into two AGR groups using cut-off of 1.43 (low, <1.43 vs. high, ≥1.43). Univariable and multivariable Cox regression analyses tested the association between AGR 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 AGR was evaluated with decision curve analysis (DCA). Results: Among 613 mRCC patients, 159 (26%) patients had an AGR <1.43. Median follow-up was 31 (IQR: 16–58) months. On univariable analysis, low preoperative serum AGR was significantly associated with both OS (HR: 1.55, 95% CI: 1.26–1.89, P<0.001) and CSS (HR: 1.55, 95% CI: 1.27–1.90, P<0.001). On multivariable analysis, AGR <1.43 was associated with worse OS (HR: 1.51, 95% CI: 1.23–1.85, P<0.001) and CSS (HR: 1.52, 95% CI: 1.24–1.86, P<0.001). The addition of AGR only minimally improved the discrimination of a base model that included established clinicopathologic features (C-index=0.640 vs. C-index=0.629). On DCA, the inclusion of AGR marginally improved the net benefit of the prognostic model. Low AGR remained independently associated with OS and CSS in the IMDC intermediate risk group (HR: 1.52, 95% CI: 1.16–1.99, P=0.002). Conclusions: In our study, low AGR before CN was associated with worse OS and CSS, particularly in intermediate risk patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.000 | 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".