017 Pharmacovigilance Analysis of Reports of Sexual Dysfunction Associated with Finasteride Use: Implications for the Post-Finasteride Syndrome
Bibliographic record
Abstract
ABSTRACT Introduction Finasteride, a 5α-reductase inhibitor, is used in the management of androgenetic alopecia and benign prostatic hyperplasia (BPH). There is growing attention to the post-finasteride syndrome, a constellation of adverse events associated with finasteride use which include sexual dysfunction. Objective To investigate reports of sexual dysfunction associated with finasteride. Methods We conducted a pharmacovigilance study using VigiBase, the World Health Organization's international database of individual case safety reports. We used the reporting odds ratio (ROR). Sensitivity analyses stratified by indication (BPH and alopecia) and age (<45 and ≥45); compared finasteride signals to those of drugs with different mechanisms but similar indications (minoxidil for alopecia and tamsulosin for BPH); compared finasteride to a drug with a similar mechanism of action (dutasteride); and compared reports of sexual dysfunction before and after 2012. Results We identified 7700 sexual dysfunction reports associated with finasteride. There was a disproportionality signal for sexual dysfunction associated with finasteride (ROR 50.3, 95% confidence interval (CI) 49.0-51.6). Patients under 45 (ROR 56.4, 95% CI 53.1-59.9) and alopecia patients (ROR 64.9, 95% CI 62.7-67.2) drove the signal. All sensitivity analyses met the threshold of signal significance. Results of primary analyses are presented in Tables 1. Conclusions We detected disproportional signals of sexual dysfunction linked with finasteride use. Despite sexual dysfunction being more prevalent in older BPH patients, we detected larger signals of sexual dysfunction in young alopecia patients. Sensitivity analyses suggest that reports of sexual dysfunction linked with finasteride use may be confounded by indication and by stimulated reporting. However, confounding alone is unlikely to account for the totality of the signal observed in young patients with alopecia. Disclosure Work supported by industry: no. A consultant, employee (part time or full time) or shareholder is among the authors (QDT reports personal fees from Astellas, Bayer, Janssen, Insightec, and Intuitive Surgical, outside the submitted work. NB, DSE, and KCZ reports consulting fees from Procept Robotics, Olympus, and BSC. BC reports consulting fees from BSC, Olympus, Meditate, Ferring, and Urovant.).
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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 | 0.009 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".