Interleukin-8 as a potential prognostic biomarker in renal cell carcinoma: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Interleukin-8 (IL-8) is a chemokine involved in inflammation and primary immune response, playing a key role in recruiting neutrophils. IL-8 is produced by several cell types, including immune cells and certain cancer cells. Elevated levels of IL-8 have been associated with a poorer outcome in several tumors and have been related to advanced diseases, treatment resistance, and possibly promoting neo angiogenesis and immune cell recruitment. In the renal cell carcinoma (RCC), the prognostic role of IL-8 has not been settled. METHODS: From January 1, 2008 to June 18, 2024, PubMed, Embase, and Scopus databases were searched for all studies investigating the potential prognostic role of IL-8 in RCC. All studies were rated according to the Newcastle-Ottawa Scale. Progression-free survival (PFS) and overall survival (OS) were analyzed as clinical outcomes, and a meta-analysis was performed for both. KEY FINDINGS AND LIMITATIONS: Overall, six papers met the predefined inclusion criteria, with final analyses demonstrating that high IL-8 levels significantly correlate with worse prognosis in RCC, with a statistically shorter PFS (hazard ratio [HR]: 1.27, 95% confidence interval [CI]: 1.01-1.59; P = 0.037) and statistically shorter OS (HR: 1.85, 95% CI: 1.21-2.84; P = .001). Prospective randomized clinical trials are also necessary to investigate the predictive role of IL-8 in the contemporary treatment scenario of RCC to improve clinical decision-making. CONCLUSIONS: This meta-analysis demonstrates the significant prognostic role of IL-8 in RCC, suggesting that IL-8 could be used to refine the prognostic RCC assessment.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".