C‐reactive protein is an informative predictor of renal cell carcinoma‐specific mortality
Bibliographic record
Abstract
BACKGROUND: C-reactive protein (CRP) represents a promising prognostic variable in patients with sporadic renal cell carcinoma (RCC). It was hypothesized that CRP can improve the prognostic ability of standard RCC-specific mortality (RCC-SM) predictors in patients treated with nephrectomy for all stages of RCC. METHODS: Radical nephrectomy was performed in 314 patients from 2 European centers. Life table, Kaplan-Meier, and Cox regression analyses addressed RCC-SM. Covariates included age, gender, TNM stage, tumor size, Fuhrman grade, and histologic subtype. RESULTS: The median survival of the cohort was 19.9 years. Age ranged from 10 to 77 years. Most patients were male (69%). T-stages were distributed as follows: T1-121 (38.7%), T2-45 (14.4%), T3-140 (44.7%), T4-7 (2.2%). CRP values ranged from 1.0 to 358.0 mg/L (mean 40.9, median 11.0 mg/L). In multivariable analyses, CRP was an independent predictor of RCC-SM (P = .003). The consideration of CRP in the multivariable model increased the predictive accuracy by 3.7% (P < .001). Moreover, the model with CRP performed 2.4% and 4.6% better than the UCLA Integrated Staging System (UISS) at, respectively, 2 and 5 years. CONCLUSIONS: CRP represents an informative predictor of RCC-SM. Its routine use could allow better risk stratification and risk-adjusted follow-up of RCC patients.
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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) | 0.001 | 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 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".