STATIN USE AND THE OVERALL SURVIVAL OF RENAL CELL CARCINOMA: A META-ANALYSIS
Bibliographic record
Abstract
PURPOSE: Statins are commonly prescribed drugs that reduce cholesterol levels and the risk of cardiovascular and cerebrovascular events. Clinical studies have shown that statins also possess cancer-preventive properties. Two studies have reported that statins also possess cancer-preventive properties; however, whether statins improve the prognosis of patients with renal cell carcinoma is still unclear. In this study, we used meta-analysis to evaluate the association between statin use and overall survival risk in patients with renal cell carcinoma. METHODS: Published studies on statin-treated renal cell carcinoma were retrieved from PubMed, Embase, The Cochrane Library, China National Knowledge Infrastructure and Wanfang databases from inception to July 2019. The relevant data were extracted and a meta-analysis was performed using Cochrane Review Manager (RevMan 5.3) software. RESULTS: Data from five studies, which reported on 5,299 patients, were analysed. The application of statins showed no effects on the overall survival of patients with renal cell carcinoma compared with the control group (OR = 1.07, 95% CI:0.77 to 1.49, P = 0.68). CONCLUSIONS: The findings of this meta-analysis suggest that statin application does not affect the overall survival of patients with renal cell carcinoma.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.032 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| 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".