Impact of statins and survival outcomes in patients with metastatic renal cell carcinoma.
Bibliographic record
Abstract
435 Background: A growing body of evidence has demonstrated the antineoplastic activity of statins. The objective of this study was to investigate the impact of statin use on survival in patients with metastatic renal cell carcinoma (mRCC) treated in the modern therapy era. Methods: We conducted a pooled analysis of mRCC patients treated on phase II and III clinical trials. Statistical analyses were performed using Cox regression adjusted for age, sex, race, histology, prior therapy, body-mass index, and other known prognostic factors and the Kaplan-Meier method. Results: We identified 4,736 patients treated with sunitinib (n=1,059), sorafenib (n=772), axitinib (n=896), temsirolimus (n=457), temsirolimus + interferon-alpha (n=208), bevacizumab + temsirolimus (n=393), bevacizumab + interferon-alpha (n=391), or interferon-alpha (n=560), of whom 511 were statin users. Overall, statin users demonstrated a statistically significant improvement in overall survival (OS) but not progression-free survival (PFS) compared to non-users (OS: 25.6 versus 18.9 months; p=0.015; adjusted hazard ratio [aHR] 0.787; 95% CI, 0.648-0.955; PFS: 7.9 versus 6.9 months; p=0.823, aHR 1.018; 95% CI, 0.867-1.196). When stratified by therapy type, a benefit in OS was demonstrated in statin users compared to non-users in individuals receiving therapy targeting vascular endothelial growth factor (28.4 versus 22.2 months, p=0.023; aHR 0.749; 95% CI, 0.584-0.961) or mammalian target of rapamycin (18.6 versus 14.0; p=0.035; aHR 0.657; 95% CI, 0.445-0.972), but not in those receiving interferon-alpha (15.6 versus 14.8 months; p=0.410; aHR 1.292; 95% CI 0.703-2.275). Adverse events were similar between statin users and non-users. Conclusions: In the largest RCC analysis to date, we demonstrate that statin use improved survival outcomes in patients with mRCC treated in the targeted therapy era. Statins could represents a potential adjunct therapeutic option for patients with metastatic RCC; however, this hypothesis needs to be corroborated with preclinical work exploring the mechanisms underlying their anti-cancer effects and well-designed clinical trials investigating the clinical benefits of adding statins to modern therapies.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".