Adverse Event Profiles of Antiseizure Medications and the Impact of Coadministration on Drug Tolerability in Adults with Epilepsy

BACKGROUND

Antiseizure medication (ASM) as monotherapy or in combination is the treatment of choice for most patients with epilepsy. Therefore, knowledge about the typical adverse events (AEs) for ASMs and other coadministered drugs (CDs) is essential for practitioners and patients. Due to frequent polypharmacy, it is often difficult to clinically assess the AE profiles of ASMs and differentiate the influence of CDs.

OBJECTIVE

This retrospective analysis aimed to determine typical AE profiles for ASMs and assess the impact of CDs on AEs in clinical practice.

METHODS

The Liverpool AE Profile (LAEP) and its domains were used to identify the AE profiles of ASMs based on data from a large German multicenter study (Epi2020). Following established classifications, drugs were grouped according to their mode of action (ASMs) or clinical indication (CDs). Bivariate correlation, multivariate ordinal regression (MORA), and artificial neural network (ANNA) analyses were performed. Bivariate correlation with Fisher's z-transformation was used to compare the correlation strength of LAEP with the Hospital Anxiety and Depression Scale (HADS) and Neurological Disorders Depression Inventory for Epilepsy (NDDI-E) to avoid LAEP bias in the context of antidepressant therapy.

RESULTS

Data from 486 patients were analyzed. The AE profiles of ASM categories and single ASMs matched those reported in the literature. Synaptic vesicle glycoprotein 2A (SV2A) and voltage-gated sodium channel (VGSC) modulators had favorable AE profiles, while brivaracetam was superior to levetiracetam regarding psychobehavioral AEs. MORA revealed that, in addition to seizure frequency, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) modulators and antidepressants were the only independent predictors of high LAEP values. After Fisher's z-transformation, correlations were significantly lower between LAEP and antidepressants than between LAEP and HADS or NDDI-E. Therefore, a bias in the results toward over interpreting the impact of antidepressants on LAEP was presumed. In the ANNA, perampanel, zonisamide, topiramate, and valproic acid were important nodes in the network, while VGSC and SV2A modulators had low relevance for predicting relevant AEs. Similarly, cardiovascular agents, analgesics, and antipsychotics were important CDs in the ANNA model.

CONCLUSION

ASMs have characteristic AE profiles that are highly reproducible and must be considered in therapeutic decision-making. Therapy using perampanel as an AMPA modulator should be considered cautiously due to its relatively high AE profile. Drugs acting via VGSCs and SV2A receptors are significantly better tolerated than other ASM categories or substances (e.g., topiramate, zonisamide, and valproate). Switching to brivaracetam is advisable in patients with psychobehavioral AEs who take levetiracetam. Because CDs frequently pharmacokinetically interact with ASMs, the cumulative AE profile must be considered.

TRIAL REGISTRATION

DRKS00022024, U1111-1252-5331.

A Comprehensive Analysis of Topiramate and Drug Reaction With Eosinophilia and Systemic Symptoms

Introduction Recent publications have described drug reaction with eosinophilia and systemic symptoms (DRESS) with topiramate. Topiramate has been associated with other severe cutaneous adverse reactions, including Stevens-Johnson syndrome, but a relationship to DRESS has not been established. To determine if there is a causal association between topiramate and DRESS, we conducted a comprehensive review of the data in the Janssen Research & Development Global Safety Database (GSD), signaling databases, and the literature. Methods The primary data were post-marketing reports of DRESS in the Janssen topiramate GSD (cumulative through 1 July 2022), representing >14,000,000 patient-years (PY) exposure. Cases were reviewed, assigned a Registry of Severe Cutaneous Adverse Reaction (RegiSCAR) score, and assessed for overall contribution of topiramate to DRESS based on temporality, concomitant medications, dechallenge/rechallenge, and baseline patient factors. Statistical disproportionality was evaluated in European Medicines Agency's EudraVigilance (EV) safety database and the United States Food and Drug Administration Adverse Event Reporting System (FAERS). For EV, the overall disproportionality threshold was the lower limit of the 95% confidence interval (CI) for the reporting odds ratio (ROR025) >1 and N ≥5. The overall threshold for FAERS was the Empirical Bayesian Geometric Mean (EBGM) ≥2, lower bound of the 90% CI (EB05) of >1, and N ≥3. To account for the role of concomitant drugs, Empirical Bayes regression-adjusted arithmetic mean (ERAM) scores were calculated, with a threshold ≥2, a lower bound of the 90% CI (ER05) of >1, and N ≥3. An integrated search of major biomedical literature was performed for reports of topiramate and DRESS. Results There were 17 reports of DRESS in the GSD (reporting rate 0.12/100,000 PY). RegiSCAR scores ranged from -3 to 7 (average -0.4). No cases met full diagnostic criteria and were highly confounded by the presence of other suspect drugs. Disproportionality scores exceeded thresholds for statistical significance in FAERS (N=72, EBGM=2.06, EB05=1.69), but not in EV (N=33, ROR025=0.79). When accounting for co-administered drugs, ERAM was statistically significant for carbamazepine (4.53), lamotrigine (ERAM=6.54), phenytoin (ERAM=2.91), and zonisamide (ERAM=2.25) exceeding disproportionality thresholds, but the score of topiramate was no longer significant (0.25). Conclusion A comprehensive review of all available evidence does not support a causal association between topiramate and DRESS.