Differential signal strength of male sexual dysfunction associated with antidepressants: a disproportionality analysis of FAERS database.

INTRODUCTION

Male sexual dysfunction (MSD) can induce or exacerbate depressive symptoms, and MSD caused by antidepressants may further aggravate the depressive symptoms of patients. However, real-world evidence regarding the association between different antidepressants and MSD remains insufficient. This study aims to systematically analyze the differences in the association between antidepressants and MSD, by utilizing the U.S. Food and Drug Administration Adverse Event Reporting System.

METHODS

Adverse drug events (ADEs) for male patients using antidepressants were retrieved. Adverse drug events were classified using the Standardized MedDRA Query. Disproportionality analysis was performed using reporting odds ratio (ROR), proportional reporting ratio (PRR), multi-item gamma-Poisson shrinker, and Bayesian confidence propagation neural network. The time-to-onset of MSD for each drug and the inclusion of MSD information in the drug labels were also analyzed.

RESULTS

Among the 28 included drugs, 24 drugs reported MSD, 18 drugs simultaneously satisfied the positive signal criteria of all 4 algorithms. Sertraline had the highest number of MSD (988 cases), accounting for 6.22% of its total 15 875 cases. Escitalopram showed the strongest signal on all 4 algorithms [ROR: 13.67, PRR: 13.19, lower limit of 95% CI of empirical Bayes geometric mean (EBGM05): 12.19, lower limit of 95% CI of the information component (IC025): 3.59]. The time-to-onset of MSD for most antidepressant drugs followed an "Early failure" model.

CONCLUSION

This study employed 4 algorithms to detect and evaluate potential association signals between antidepressants and MSD. Among the 28 antidepressants analyzed, 18 demonstrated significant associations with MSD. Beyond traditional selective serotonin reuptake inhibitors, the signal strength of MSD associated with other classes of antidepressants should not be overlooked.