Impact of preoperative serum albumin-globulin ratio on disease outcome after radical cystectomy for urothelial carcinoma of the bladder
Bibliographic record
Abstract
INTRODUCTION: The Albumin-Globulin Ratio (AGR; albumin/total protein - albumin) has been associated with oncological outcome in various malignancies. However, its role in urothelial carcinoma of the bladder (UCB) has not been clearly established. In this study, we assessed the association of preoperative AGR (pAGR) with survival in patients who underwent radical cystectomy (RC) for UCB. MATERIAL AND METHODS: We conducted a retrospective analysis of an established multicenter database of 4.335 patients who were treated with RC for UCB. The cohort was divided into 2 groups according to the pAGR status. Binominal logistic regression as well as uni- and multivariable Cox regression analyses were used. The predictive value of the models was assessed by calculating receiver operating characteristics curves and concordance-indices (C-Index). The additional clinical value was assessed using the decision curve analysis (DCA). RESULTS: Overall, 1.670 patients (38.5%) had a low pAGR. On multivariable logistic regression analyses, low pAGR was associated with an increased risk of ≥pT3 disease at RC (odds ratio [OR] 1.15, 95% confidence interval [CI] 1.01-1.31, P= 0.04). On multivariable Cox regression analyses, low pAGR remained associated with worse recurrence-free survival (RFS, HR 1.24, 95% CI 1.1-1.37, P< 0.001), cancer-specific survival (CSS, HR 1.23, 95% CI 1.1-1.38, P< 0.001) and overall survival (OS, HR 1.17, 95% CI 1.07-1.28, P< 0.001). The addition of pAGR to multiple prognostic models that were respectively fitted for clinical and postoperative variables did not improve the predictive accuracy. CONCLUSION: pAGR status is an independent predictor of ≥pT3 disease, therefore it could help identify patients who have a higher likelihood to benefit from neoadjuvant systemic therapy. While pAGR was independently associated with RFS, CSS, and OS, it did not improve the predictive accuracy and clinical value beyond obtained by information already available. The predictive value of this biomarker in the age of immunotherapy needs further evaluation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".