Cardiac arrhythmias associated with S1PRMs: a pharmacovigilance study based on real-world data.

Background: Sphingosine-1-phosphate receptor modulators (S1PRMs) are an effective class of disease-modifying therapies (DMTs) for the treatment of multiple sclerosis (MS). While cardiac arrhythmias such as bradycardia and atrioventricular (AV) block are recognized class effects of S1PRMs, comparative real-world safety profiles across all four approved agents-particularly newer agents with limited post-marketing data-remain insufficiently characterized. Methods: We conducted a retrospective pharmacovigilance analysis using data from the FDA Adverse Event Reporting System (FAERS) from the fourth quarter of 2010 to the first quarter of 2024. Disproportionality analysis was performed using the Reported Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN) and Multi-item Gamma Poisson Shrinker (MGPS). Adverse events were classified using Standardised MedDRA Queries narrow-scope terms and Preferred Terms (PTs). Univariate logistic regression was used to explore the association between demographic factors and arrhythmia reporting. Results: We identified 2,059 arrhythmia-related adverse events associated with S1PRMs, including 1,860 cases for fingolimod, 153 for siponimod, 38 for ozanimod, and 8 for ponesimod. Patients aged 18-65 and female patients constituted the majority of reports. Disproportionality analysis based signal detection identified heart rate decreased, cardiac flutter, and extrasystoles as prominent signals across S1PRMs. Conclusion: This pharmacovigilance study provides a comparative real-world overview of arrhythmia-related adverse event signals across four approved S1PRMs. The findings are concordant with the cardiac effects anticipated from the known pharmacology of S1PRMs and reinforce the importance of cardiac monitoring during treatment initiation. As a disproportionality analysis of spontaneous reports, these results reflect statistical associations rather than causal relationships and should be regarded as hypothesis-generating; cross-drug comparisons are further influenced by differential reporting, market duration and cumulative exposure. These results may complement clinical trial data for informed risk-benefit assessment, particularly for newer S1PRMs with limited post-marketing surveillance data.