Statin Use and Survival Among Men Receiving Androgen-Ablative Therapies for Advanced Prostate Cancer
Bibliographic record
Abstract
Importance: Epidemiological evidence supports a role for statins in improving survival in advanced prostate cancer, particularly among men receiving androgen-ablative therapies. Objective: To study the association between statin use and survival among men with prostate cancer receiving androgen deprivation therapy (ADT) or androgen receptor axis-targeted therapies (ARATs). Data Sources: This systemic review and meta-analysis used sources from MEDLINE, EMBASE, Epub Ahead of Print, Cochrane Clinical Trials, Cochrane Systematic Reviews, and Web of Science from inception to September 6, 2022. Study Selection: Observational studies reporting associations of concurrent statin use and survival outcomes (in hazard ratios [HRs]). Data Extraction and Synthesis: Two authors independently abstracted all data. Summary estimates pooled multivariable HRs with 95% CIs using the generic inverse variance method with random-effects modeling. A priori specified subgroup and sensitivity analyses were undertaken, and heterogeneity, study quality, and publication bias were evaluated. Confidence in the evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach. Main Outcomes and Measures: Overall mortality and prostate cancer-specific mortality (PCSM). Results: Twenty-five cohorts of 119 878 men (65 488 statin users [55%]) with more than 74 416 deaths were included. Concurrent statin use was associated with a 27% reduction in the risk of overall mortality (HR, 0.73 [95% CI, 0.66-0.82]; I2 = 83%) and a 35% reduction in the risk of PCSM (HR, 0.65 [95% CI, 0.58-0.73]; I2 = 74%), with substantial heterogeneity in both estimates. Subgroup analyses identified a PCSM advantage associated with statins for men receiving ARATs compared with ADT alone (HR, 0.40 [95% CI, 0.30-0.55] vs 0.68 [95% CI, 0.60-0.76]; P = .002 for difference). Confidence in the evidence was rated low for both outcomes. Conclusions and Relevance: The findings of this meta-analysis show that concurrent statin use was associated with reduced overall mortality and PCSM among men receiving androgen-ablative therapies for advanced prostate cancer. These findings are limited by the observational nature of the data and residual unexplained interstudy heterogeneity. Randomized clinical trials are warranted to validate these results.
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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 | 0.012 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.012 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".