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Record W4224491617 · doi:10.1016/j.jsxm.2022.01.236

222 Pharmacovigilance Analysis of Reports of Sexual Dysfunction Associated with Finasteride Use: Implications for the Post-Finasteride Syndrome

2022· article· en· W4224491617 on OpenAlexaff
David‐Dan Nguyen, P Herzog, EB Cone, Muhieddine Labban, KC Zorn, Bilal Chughtai, Shezhad Basaria, DS Elterman, Q-D. Trinh, Naeem Bhojani

Bibliographic record

VenueThe Journal of Sexual Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsUniversity Health NetworkCentre Hospitalier de l’Université de MontréalMcGill University
Fundersnot available
KeywordsFinasterideSexual dysfunctionMedicineDutasteridePharmacovigilanceUrologyErectile dysfunctionInternal medicineGynecologyAdverse effectProstate cancerProstateCancer

Abstract

fetched live from OpenAlex

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 and sensitivity analyses are presented in Tables 1 and 2. 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 Any of the authors act as a consultant, employee or shareholder of an industry for: 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.040
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.055
GPT teacher head0.320
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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