3-Hydroxy-3-Methylglutaryl Coenzyme A Reductase Inhibitors and the Risk of Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: During the past 15 years there has been an exponential increase in the number of prescriptions for lipid-lowering drugs. Uncertainties remain about the long-term impact of these medications on cancer, which is particularly bothersome given that the duration of these treatments may extend for several decades. OBJECTIVE: To explore the association between 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors and cancer incidence. METHODS: Using the administrative health databases of the Régie de l'Assurance-Maladie du Québec we performed a nested case-control study. We selected a cohort of 6721 beneficiaries of the health care plan of Quebec who were free of cancer for at least 1 year at cohort entry, 65 years and older, and treated with lipid-modifying agents. Cohort members were selected between 1988 and 1994 and were followed up for a median period of 2.7 years. From the cohort, 542 cases of first malignant neoplasm were identified, and 5420 controls were randomly selected. Users of HMG-CoA reductase inhibitors were compared with users of bile acid-binding resins as to their risk of cancer. Specific cancer sites were also considered. RESULTS: Users of HMG-CoA reductase inhibitors were found to be 28% less likely than users of bile acid-binding resins to be diagnosed as having any cancer (rate ratio, 0.72; 95% confidence interval, 0.57-0.92). All specific cancer sites under study were found to be not or inversely associated with the use of HMG-CoA reductase inhibitors. CONCLUSION: The results of our study provide some degree of reassurance about the safety of HMG-CoA reductase inhibitors.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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