The prognostic value of vascular endothelial growth factor in patients with renal cell carcinoma: a systematic review of the literature and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Vascular endothelial growth factor (VEGF) serum level or tumor expression may be prognostic in renal cell carcinoma (RCC). The purpose of this meta-analysis was to examine the prognostic value of serum VEGF level and tumor expression in patients with RCC. METHODS: PubMed and EMBASE databases were searched until September 26, 2016. Prospective and retrospective studies of RCC patients that had VEGF levels measured were included. Outcome measures were overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS). RESULTS: A total of 14 studies were included in the meta-analysis. In patients with RCC, elevated serum VEGF level was not associated with OS (pooled hazard ratio [HR] = 1.16; 95% confidence interval [CI]: 0.52 to 2.60; p = 0.716), but was associated with poor DSS (pooled HR = 4.22; 95% CI: 2.02 to 8.79; p < 0.001) and PFS (pooled HR = 1.50; 95% CI: 1.22 to 1.85; p < 0.001). Removal of one study, however, resulted in elevated serum level being associated with poorer OS. Tumor VEGF expression was not associated with OS (pooled HR = 1.48; 95% CI: 0.74 to 2.95; p = 0.263), but was associated with worse DSS (pooled HR = 1.83; 95% CI: 1.24 to 2.71; p = 0.003). CONCLUSION: In patients with RCC, elevated serum VEGF level is associated with worse OS, DSS, and PFS, while tumor expression is only associated with worse DSS. The number of studies, however, was limited and the results should be interpreted with caution.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.027 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".