Safety evaluation of metabolic adverse events associated with anti-seizure medications use in minors based on FAERS_Journal of Epilepsy

Authors：

SHAN Qing ^1,2 , CHEN Yan ^1,2 , ZHAO Yu ^1,2 , MA Ping ^1,2 ,  GUO Jinmin ^1,2

1. Department of Pharmacy, The 960th Hospital of the PLA Joint Logistics Support Force, Jinan 250031, China;
2. Jinan Key Laboratory of Individualized Clinical Medication Safety Monitoring and Pharmacovigilance Research, Jinan 250031, China;

Corresponding?author：

GUO Jinmin, Email: gjm90h@126.com

Keywords：

Anti-seizure medications; Minors; Metabolic disorders; Pharmacovigilance; FAERS; Data mining; Safety evaluation

DOI：

10.7507/2096-0247.202601003

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Objective To systematically evaluate the safety profiles of anti-seizure medications (ASMs) regarding metabolic adverse events in the pediatric population, identify risk signals across different age stages, and provide evidence-based support for clinical individualized medication and pharmacovigilance. Methods Data from the Food and Drug Administration (FDA) adverse event reporting system (FAERS) spanning Q1 2013 to Q3 2024 were analyzed. Reports involving metabolic adverse events in patients aged 0~18 years after ASMs use were screened. Data mining methods, including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), and Bayesian Confidence Propagation Neural Network (BCPNN), were applied. Standardized classification was performed using the Medical Dictionary for Regulatory Activities (MedDRA) v26.1 to analyze adverse reaction signals across metabolic pathways, including glucose, lipids, proteins/amino acids, and bone/calcium/phosphorus/magnesium, as well as trace metals. Stratified safety evaluations were conducted across four age groups: infants (0~2 years), toddlers (2~6 years), children (6~2 years), and adolescents (12~18 years). Results A total of 2,356 metabolic adverse event reports were included. Significant signals were observed for protein and amino acid metabolism disorders (ROR=5.44), bone/calcium/magnesium/phosphorus metabolism disorders (ROR=1.59), and iron/trace metal metabolism disorders (ROR=1.83), with some signals being specific to the pediatric population. Several drugs, including valproate, topiramate, levetiracetam, and gabapentin, showed strong risk signals across multiple metabolic pathways, primarily manifesting as hyperammonemia, hypocalcemia, and hypomagnesemia. Risk profiles varied significantly by age group: lacosamide showed prominent signals for bone metabolism disorders in the 0~2 years group; perampanel showed significant signals for amino acid metabolism disorders in the 2~6 years group; and in the 12~18 years group, clonazepam and gabapentin showed extremely high ROR values (>48) for iron/trace metal metabolism disorders. The median onset time for metabolic adverse events associated with novel ASMs was significantly later than that of traditional ASMs (38 days vs. 8 days), suggesting a relatively delayed but prolonged metabolic toxicity for newer agents. Conclusion The use of ASMs in minors can trigger multi-system metabolic disturbances, with significant differences in risk profiles across different drugs and age groups. We recommend strengthening the dynamic monitoring of metabolic parameters during treatment, with particular attention to the potential toxicity of high-risk drugs within specific age windows, thereby promoting the establishment of precision dosing and early intervention strategies.

Citation： SHAN Qing, CHEN Yan, ZHAO Yu, MA Ping, GUO Jinmin. Safety evaluation of metabolic adverse events associated with anti-seizure medications use in minors based on FAERS. Journal of Epilepsy, 2026, 12(2): 101-109. doi: 10.7507/2096-0247.202601003 Copy

1.	Menon RN, Helen Cross J. Childhood epilepsy. Lancet (London, England), 2025, 406(10503): 636-649.
2.	Sankaraneni R, Lachhwani D. Antiepileptic drugs--a review. Pediatric Annals, 2015, 44(2): e36-e42.
3.	Strozzi I, Nolan SJ, Sperling MR, et al. Early versus late antiepileptic drug withdrawal for people with epilepsy in remission. The Cochrane database of systematic reviews, 2015, 15(2): CD001902.
4.	Belete TM. Recent progress in the development of new antiepileptic drugs with novel targets. Annals of Neurosciences, 2023, 30(4): 262-276.
5.	Belcastro V, D'Egidio C, Striano P, et al. Metabolic and endocrine effects of valproic acid chronic treatment. Epilepsy Research, 2013, 107(1-2): 1-8.
6.	Zhang H, Lu P, Tang H, et al. Valproate-induced epigenetic upregulation of hypothalamic fto expression potentially linked with weight gain. Cellular and Molecular Neurobiology, 2021, 41(6): 1257-1269.
7.	Brandt C, Lahr D, May TW. Cognitive adverse events of topiramate in patients with epilepsy and intellectual disability. Epilepsy & Behavior, 2015, 45: 261-264.
8.	Mirza NS, Alfirevic A, Jorgensen A, et al. Metabolic acidosis with topiramate and zonisamide: an assessment of its severity and predictors. Pharmacogenetics and Genomics, 2011, 21(5): 297-302.
9.	Rothman KJ, Lanes S, Sacks ST. The reporting odds ratio and its advantages over the proportional reporting ratio. Pharmacoepidemiology and Drug Safety, 2004, 13(8): 519-523.
10.	Evans S J, Waller PC, Davis S. Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports. Pharmacoepidemiology and Drug Safety, 2001, 10(6): 483-486.
11.	Waller P, van Puijenbroek E, Egberts A, et al. The reporting odds ratio versus the proportional reporting ratio: 'deuce'. Pharmacoepidemiology and Drug Safety, 2004, 13(8): 525-528.
12.	Moore N, Thiessard F, Begaud B. The history of disproportionality measures (reporting odds ratio, proportional reporting rates) in spontaneous reporting of adverse drug reactions. Pharmacoepidemiology and Drug Safety, 2005, 14(4): 285-286.
13.	Johannessen SI, Tomson T. Pharmacokinetic variability of newer antiepileptic drugs: when is monitoring needed? Clinical Pharmacokinetics, 2006, 45(11): 1061-1075.
14.	Strolin Benedetti M, Ruty B, Baltes E. Induction of endogenous pathways by antiepileptics and clinical implications. Fundamental & Clinical Pharmacology, 2005, 19(5): 511-529.
15.	Nair SS, Harikrishnan S, Sarma PS, et al. Metabolic syndrome in young adults with epilepsy. Seizure, 2016, 37: 61-64.
16.	Rahimdel A, Dehghan A, Moghadam MA, et al. Relationship between bone density and biochemical markers of bone among two groups taking carbamazepine and sodium valproate for epilepsy in comparison with healthy individuals in Yazd. Electronic Physician, 2016, 8(11): 3257-3265.
17.	Dilber B, Gürgen SG, Yazar U, et al. Effect of antiseizure drugs on growing bone in prepubertal non-epileptic rats. Food and Chemical Toxicology, 2025, 204: 115671.
18.	Matuszewska A, Nowak B, Nikodem A, et al. Antiepileptic stiripentol may influence bones. International Journal of Molecular Sciences, 2021, 22(13): 7162.
19.	Inaloo S, Saki F, Paktinat M, et al. Evaluation of the metabolic syndrome criteria and body composition in ambulatory children with epilepsy using sodium valproate and carbamazepine in southern Iran: a case-control study. Iranian Journal of Child Neurology, 2020, 14(3): 47-56.
20.	Im DU, Kim SC, Chau GC, et al. Carbamazepine enhances adipogenesis by inhibiting wnt/β-catenin expression. Cells, 2019, 8(11): 1460.
21.	Hayes JF, Marston L, Walters K, et al. Adverse renal, endocrine, hepatic, and metabolic events during maintenance mood stabilizer treatment for bipolar disorder: a population-based cohort study. PLoS Medicine, 2016, 13(8): e1002058.
22.	Mintzer S, Skidmore CT, Abidin CJ, et al. Effects of antiepileptic drugs on lipids, homocysteine, and C-reactive protein. Annals of Neurology, 2009, 65(4): 448-456.
23.	French JA, Gazzola DM. New generation antiepileptic drugs: what do they offer in terms of improved tolerability and safety? Therapeutic Advances in Drug Safety, 2011, 2(4): 141-158.
24.	Grootens KP, Meijer A, Hartong EG, et al. Weight changes associated with antiepileptic mood stabilizers in the treatment of bipolar disorder. European Journal of Clinical Pharmacology, 2018, 74(11): 1485-1489.
25.	Chocho? P, Arturo N, ?ajczak P M, et al. Effects of antiseizure medications on lipid profile and weight in patients with epilepsy: a systematic review with meta-analysis. CNS Drugs, 2025, 39(12): 1221-1239.

1. Menon RN, Helen Cross J. Childhood epilepsy. Lancet (London, England), 2025, 406(10503): 636-649.
2. Sankaraneni R, Lachhwani D. Antiepileptic drugs--a review. Pediatric Annals, 2015, 44(2): e36-e42.
3. Strozzi I, Nolan SJ, Sperling MR, et al. Early versus late antiepileptic drug withdrawal for people with epilepsy in remission. The Cochrane database of systematic reviews, 2015, 15(2): CD001902.
4. Belete TM. Recent progress in the development of new antiepileptic drugs with novel targets. Annals of Neurosciences, 2023, 30(4): 262-276.
5. Belcastro V, D'Egidio C, Striano P, et al. Metabolic and endocrine effects of valproic acid chronic treatment. Epilepsy Research, 2013, 107(1-2): 1-8.
6. Zhang H, Lu P, Tang H, et al. Valproate-induced epigenetic upregulation of hypothalamic fto expression potentially linked with weight gain. Cellular and Molecular Neurobiology, 2021, 41(6): 1257-1269.
7. Brandt C, Lahr D, May TW. Cognitive adverse events of topiramate in patients with epilepsy and intellectual disability. Epilepsy & Behavior, 2015, 45: 261-264.
8. Mirza NS, Alfirevic A, Jorgensen A, et al. Metabolic acidosis with topiramate and zonisamide: an assessment of its severity and predictors. Pharmacogenetics and Genomics, 2011, 21(5): 297-302.
9. Rothman KJ, Lanes S, Sacks ST. The reporting odds ratio and its advantages over the proportional reporting ratio. Pharmacoepidemiology and Drug Safety, 2004, 13(8): 519-523.
10. Evans S J, Waller PC, Davis S. Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports. Pharmacoepidemiology and Drug Safety, 2001, 10(6): 483-486.
11. Waller P, van Puijenbroek E, Egberts A, et al. The reporting odds ratio versus the proportional reporting ratio: 'deuce'. Pharmacoepidemiology and Drug Safety, 2004, 13(8): 525-528.
12. Moore N, Thiessard F, Begaud B. The history of disproportionality measures (reporting odds ratio, proportional reporting rates) in spontaneous reporting of adverse drug reactions. Pharmacoepidemiology and Drug Safety, 2005, 14(4): 285-286.
13. Johannessen SI, Tomson T. Pharmacokinetic variability of newer antiepileptic drugs: when is monitoring needed? Clinical Pharmacokinetics, 2006, 45(11): 1061-1075.
14. Strolin Benedetti M, Ruty B, Baltes E. Induction of endogenous pathways by antiepileptics and clinical implications. Fundamental & Clinical Pharmacology, 2005, 19(5): 511-529.
15. Nair SS, Harikrishnan S, Sarma PS, et al. Metabolic syndrome in young adults with epilepsy. Seizure, 2016, 37: 61-64.
16. Rahimdel A, Dehghan A, Moghadam MA, et al. Relationship between bone density and biochemical markers of bone among two groups taking carbamazepine and sodium valproate for epilepsy in comparison with healthy individuals in Yazd. Electronic Physician, 2016, 8(11): 3257-3265.
17. Dilber B, Gürgen SG, Yazar U, et al. Effect of antiseizure drugs on growing bone in prepubertal non-epileptic rats. Food and Chemical Toxicology, 2025, 204: 115671.
18. Matuszewska A, Nowak B, Nikodem A, et al. Antiepileptic stiripentol may influence bones. International Journal of Molecular Sciences, 2021, 22(13): 7162.
19. Inaloo S, Saki F, Paktinat M, et al. Evaluation of the metabolic syndrome criteria and body composition in ambulatory children with epilepsy using sodium valproate and carbamazepine in southern Iran: a case-control study. Iranian Journal of Child Neurology, 2020, 14(3): 47-56.
20. Im DU, Kim SC, Chau GC, et al. Carbamazepine enhances adipogenesis by inhibiting wnt/β-catenin expression. Cells, 2019, 8(11): 1460.
21. Hayes JF, Marston L, Walters K, et al. Adverse renal, endocrine, hepatic, and metabolic events during maintenance mood stabilizer treatment for bipolar disorder: a population-based cohort study. PLoS Medicine, 2016, 13(8): e1002058.
22. Mintzer S, Skidmore CT, Abidin CJ, et al. Effects of antiepileptic drugs on lipids, homocysteine, and C-reactive protein. Annals of Neurology, 2009, 65(4): 448-456.
23. French JA, Gazzola DM. New generation antiepileptic drugs: what do they offer in terms of improved tolerability and safety? Therapeutic Advances in Drug Safety, 2011, 2(4): 141-158.
24. Grootens KP, Meijer A, Hartong EG, et al. Weight changes associated with antiepileptic mood stabilizers in the treatment of bipolar disorder. European Journal of Clinical Pharmacology, 2018, 74(11): 1485-1489.
25. Chocho? P, Arturo N, ?ajczak P M, et al. Effects of antiseizure medications on lipid profile and weight in patients with epilepsy: a systematic review with meta-analysis. CNS Drugs, 2025, 39(12): 1221-1239.

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