Statins in the Cause and Prevention of Cancer: Confounding by Indication and Mediation by Rhabdomyolysis and Phosphate Toxicity
Bibliographic record
Abstract
Statins are drugs used in cardiovascular pharmacotherapy to decrease hypercholesterolemia and lower the risk of atherosclerosis. Statins also increase the risk of rhabdomyolysis, which is often minimized in comparison with large relative risk reductions of cardiovascular disease reported in clinical trials. By contrast, absolute risk reductions of cardiovascular disease are often clinically insignificant and unreported in statin clinical trials. Additionally, cytotoxic effects of statins inhibit cancer cell proliferation and reduce cancer risk, but other studies found that statins are carcinogenic. Due to an inverse association between incidence of cancer and atherosclerosis, the indication to prescribe statins likely biases the association of statins with cancer prevention. Dietary patterns associated with atherosclerosis and cancer contain inverse amounts of cholesterol and phosphate, an essential mineral that stimulates tumorigenesis. Accordingly, lower cancer risk is associated with high dietary cholesterol intake and increased risk of atherosclerosis. Furthermore, serum is exposed to excessive inorganic phosphate that could increase cancer risk as rhabdomyolysis induced by statins releases phosphate from skeletal muscle breakdown. Increased risk of comorbid conditions associated with statins may share the mediating factor of phosphate toxicity. More research is warranted on statins in the cause and prevention of cancer.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".