Use of Statins and the Risk of Death in Patients With Prostate Cancer
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: To determine whether the use of statins after prostate cancer diagnosis is associated with a decreased risk of cancer-related mortality and all-cause mortality and to assess whether this association is modified by prediagnostic use of statins. PATIENTS AND METHODS: A cohort of 11,772 men newly diagnosed with nonmetastatic prostate cancer between April 1, 1998, and December 31, 2009, followed until October 1, 2012, was identified using a large population-based electronic database from the United Kingdom. Time-dependent Cox proportional hazards models were used to estimate adjusted hazard ratios (HRs) with 95% CIs of mortality outcomes associated with postdiagnostic use of statins, lagged by 1 year to account for latency considerations and to minimize reverse causality, and considering effect modification by prediagnostic use of statins. RESULTS: During a mean follow-up time of 4.4 years (standard deviation, 2.9 years), 3,499 deaths occurred, including 1,791 from prostate cancer. Postdiagnostic use of statins was associated with a decreased risk of prostate cancer mortality (HR, 0.76; 95% CI, 0.66 to 0.88) and all-cause mortality (HR, 0.86; 95% CI, 0.78 to 0.95). These decreased risks of prostate cancer mortality and all-cause mortality were more pronounced in patients who also used statins before diagnosis (HR, 0.55; 95% CI, 0.41 to 0.74; and HR, 0.66; 95% CI, 0.53 to 0.81, respectively), with weaker effects in patients who initiated the treatment only after diagnosis (HR, 0.82; 95% CI, 0.71 to 0.96; and HR, 0.91; 95% CI, 0.82 to 1.01, respectively). CONCLUSION: Overall, the use of statins after diagnosis was associated with a decreased risk in prostate cancer mortality. However, this effect was stronger in patients who also used statins before diagnosis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it