Association of Long-term Antiseizure Medication Use and Incident Type 2 Diabetes Mellitus.


Journal

Neurology
ISSN: 1526-632X
Titre abrégé: Neurology
Pays: United States
ID NLM: 0401060

Informations de publication

Date de publication:
16 05 2023
Historique:
received: 07 03 2022
accepted: 09 02 2023
pmc-release: 16 05 2024
medline: 17 5 2023
pubmed: 25 3 2023
entrez: 24 3 2023
Statut: ppublish

Résumé

Diabetes mellitus (DM) contributes significantly to metabolic syndrome and cardiovascular events, and it may be a comorbidity of epilepsy. The objective of this study was to investigate whether long-term antiseizure medication (ASM) use is associated with the risk of developing type 2 diabetes. We analyzed data from the Chang Gung Research Database. Patients aged ≥45 years who received ASM treatment from January 2001 to May 2019 were identified. Patients with DM-associated diseases and short-term ASM use were excluded. The patients were classified into nonenzyme interaction, enzyme-inducing, enzyme-inhibiting, and mixed ASM groups. The rate of incident diabetes associated with individual ASM was further analyzed. Propensity score weighting was performed to balance between-group differences. Analyses were conducted with Cox proportional regression models and stabilized inverse probability of treatment weighting (IPTW). Hazard ratios (HRs) were calculated at 3, 4, 6, and 9 years after the index date and the end of follow-up. A total of 5,103 patients were analyzed, of whom 474 took nonenzyme interaction ASMs, 1,156 took enzyme-inducing ASMs, 336 took enzyme-inhibiting ASMs, and 3,137 took mixed ASMs. During follow-up (39,248 person-years), 663 patients developed new-onset DM, and the prevalence was 13.0%. The incidence of DM plateaued at 6-9 years after ASM initiation. Enzyme-inhibiting ASMs were significantly associated with a higher HR starting at the third year and then throughout the study period. The HRs were 1.93 (95% CI 1.33-2.80), 1.85 (95% CI 1.24-2.75), and 2.08 (95% CI 1.43-3.03) in unadjusted, adjusted, and stabilized IPTW models, respectively, at the end of follow-up. The dosing of ASM did not increase the risk of DM, and none of the individual ASM analyses reached statistical significance. The long-term use of enzyme-inhibiting ASMs was associated with an increased risk of incident DM, and the risk increased with the duration of treatment. These findings may guide the choice of drugs in those requiring long-term ASM therapy, particularly in high-risk individuals. This study provides Class IV evidence that enzyme-inhibiting ASMs were associated with an increased risk of developing DM compared with nonenzyme interaction ASMs.

Sections du résumé

BACKGROUND AND OBJECTIVES
Diabetes mellitus (DM) contributes significantly to metabolic syndrome and cardiovascular events, and it may be a comorbidity of epilepsy. The objective of this study was to investigate whether long-term antiseizure medication (ASM) use is associated with the risk of developing type 2 diabetes.
METHODS
We analyzed data from the Chang Gung Research Database. Patients aged ≥45 years who received ASM treatment from January 2001 to May 2019 were identified. Patients with DM-associated diseases and short-term ASM use were excluded. The patients were classified into nonenzyme interaction, enzyme-inducing, enzyme-inhibiting, and mixed ASM groups. The rate of incident diabetes associated with individual ASM was further analyzed. Propensity score weighting was performed to balance between-group differences. Analyses were conducted with Cox proportional regression models and stabilized inverse probability of treatment weighting (IPTW). Hazard ratios (HRs) were calculated at 3, 4, 6, and 9 years after the index date and the end of follow-up.
RESULTS
A total of 5,103 patients were analyzed, of whom 474 took nonenzyme interaction ASMs, 1,156 took enzyme-inducing ASMs, 336 took enzyme-inhibiting ASMs, and 3,137 took mixed ASMs. During follow-up (39,248 person-years), 663 patients developed new-onset DM, and the prevalence was 13.0%. The incidence of DM plateaued at 6-9 years after ASM initiation. Enzyme-inhibiting ASMs were significantly associated with a higher HR starting at the third year and then throughout the study period. The HRs were 1.93 (95% CI 1.33-2.80), 1.85 (95% CI 1.24-2.75), and 2.08 (95% CI 1.43-3.03) in unadjusted, adjusted, and stabilized IPTW models, respectively, at the end of follow-up. The dosing of ASM did not increase the risk of DM, and none of the individual ASM analyses reached statistical significance.
DISCUSSION
The long-term use of enzyme-inhibiting ASMs was associated with an increased risk of incident DM, and the risk increased with the duration of treatment. These findings may guide the choice of drugs in those requiring long-term ASM therapy, particularly in high-risk individuals.
CLASSIFICATION OF EVIDENCE
This study provides Class IV evidence that enzyme-inhibiting ASMs were associated with an increased risk of developing DM compared with nonenzyme interaction ASMs.

Identifiants

pubmed: 36963840
pii: WNL.0000000000207222
doi: 10.1212/WNL.0000000000207222
pmc: PMC10186244
doi:

Substances chimiques

Anticonvulsants 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e2071-e2082

Informations de copyright

© 2023 American Academy of Neurology.

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Auteurs

Wei-En Johnny Tseng (WJ)

From the Section of Epilepsy (W.-E.J.T., C.-W.C., C.-J.L., S.-N.L.), Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center, and Chang Gung University College of Medicine; PhD Program in Biomedical Engineering (W.-E.J.T.), Chang Gung University; Division of Endocrinology and Metabolism (J.-S.H.), Department of Internal Medicine, Linkou Chang Gung Memorial Hospital; and Center for Big Data Analytics and Statistics (P.-C.K.), Chang Gung Memorial Hospital, Taoyuan, Taiwan.

Chun-Wei Chang (CW)

From the Section of Epilepsy (W.-E.J.T., C.-W.C., C.-J.L., S.-N.L.), Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center, and Chang Gung University College of Medicine; PhD Program in Biomedical Engineering (W.-E.J.T.), Chang Gung University; Division of Endocrinology and Metabolism (J.-S.H.), Department of Internal Medicine, Linkou Chang Gung Memorial Hospital; and Center for Big Data Analytics and Statistics (P.-C.K.), Chang Gung Memorial Hospital, Taoyuan, Taiwan.

Jawl-Shan Hwang (JS)

From the Section of Epilepsy (W.-E.J.T., C.-W.C., C.-J.L., S.-N.L.), Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center, and Chang Gung University College of Medicine; PhD Program in Biomedical Engineering (W.-E.J.T.), Chang Gung University; Division of Endocrinology and Metabolism (J.-S.H.), Department of Internal Medicine, Linkou Chang Gung Memorial Hospital; and Center for Big Data Analytics and Statistics (P.-C.K.), Chang Gung Memorial Hospital, Taoyuan, Taiwan.

Po-Chuan Ko (PC)

From the Section of Epilepsy (W.-E.J.T., C.-W.C., C.-J.L., S.-N.L.), Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center, and Chang Gung University College of Medicine; PhD Program in Biomedical Engineering (W.-E.J.T.), Chang Gung University; Division of Endocrinology and Metabolism (J.-S.H.), Department of Internal Medicine, Linkou Chang Gung Memorial Hospital; and Center for Big Data Analytics and Statistics (P.-C.K.), Chang Gung Memorial Hospital, Taoyuan, Taiwan.

Chun-Jing Liu (CJ)

From the Section of Epilepsy (W.-E.J.T., C.-W.C., C.-J.L., S.-N.L.), Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center, and Chang Gung University College of Medicine; PhD Program in Biomedical Engineering (W.-E.J.T.), Chang Gung University; Division of Endocrinology and Metabolism (J.-S.H.), Department of Internal Medicine, Linkou Chang Gung Memorial Hospital; and Center for Big Data Analytics and Statistics (P.-C.K.), Chang Gung Memorial Hospital, Taoyuan, Taiwan.

Siew-Na Lim (SN)

From the Section of Epilepsy (W.-E.J.T., C.-W.C., C.-J.L., S.-N.L.), Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center, and Chang Gung University College of Medicine; PhD Program in Biomedical Engineering (W.-E.J.T.), Chang Gung University; Division of Endocrinology and Metabolism (J.-S.H.), Department of Internal Medicine, Linkou Chang Gung Memorial Hospital; and Center for Big Data Analytics and Statistics (P.-C.K.), Chang Gung Memorial Hospital, Taoyuan, Taiwan. siewna@cgmh.org.tw.

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