Risk of rhabdomyolysis from 5‐α reductase inhibitors
Bibliographic record
Abstract
PURPOSE: A recent regulatory warning and case reports have described the development of muscle complications with the use of 5-α reductase inhibitors (5ARIs). We wished to determine if there was a link between rhabdomyolysis and 5ARI usage. METHODS: We used a matched cohort design and linked administrative data from the province of Ontario, Canada, to investigate the risk of rhabdomyolysis in men using either finasteride or dutasteride. A total of 99 covariates were measured. We identified 93 197 men ≥66 years of age who initiated a new prescription for a 5ARI, and they were matched using a propensity score to an equal number of men not prescribed a 5ARI. RESULTS: New initiation of 5ARIs was not associated with a significantly increased risk of rhabdomyolysis (hazard ratio [HR] 1.21, 95% confidence interval [CI], 1.00-1.48, P = .06). When we examined the risk of rhabdomyolysis in the year prior to the initiation of a 5ARI, we found that men who would go on to use a 5ARI in the future had an elevated risk of rhabdomyolysis even prior to starting the medication (HR 1.31, 95% CI, 1.05-1.64, P = .01). Our secondary outcome of myositis and myopathy was significantly higher among 5ARI users (HR 1.63, 95% CI, 1.48-1.80, P < .01), and this risk was not present prior to 5ARI usage. CONCLUSION: 5-α reductase inhibitors do not appear to be associated with the development of rhabdomyolysis; however, they may be associated with an increased risk of myopathy and myositis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".