| アブストラクト | Valproate is the most effective treatment for idiopathic generalised epilepsy. Currently, its use is restricted in women of childbearing potential owing to high teratogenicity. Recent evidence extended this risk to men's offspring, prompting recommendations to restrict use in everybody aged <55 years. This study will evaluate mortality and morbidity risks associated with valproate withdrawal by emulating a hypothetical randomised-controlled trial (called a "target trial") using retrospective observational data. The data will be drawn from ~250m mainly US patients in the TriNetX repository and ~60m UK patients in Clinical Practice Research Datalink (CPRD). These will be scanned for individuals aged 16-54 years with epilepsy and on valproate who either continued, switched to lamotrigine or levetiracetam, or discontinued valproate between 2014-2024, creating four groups. Randomisation to these groups will be emulated by baseline confounder adjustment using g-methods. Mortality and morbidity outcomes will be assessed and compared between groups over 1-10 years, employing time-to-first-event and recurrent events analyses. A causal prediction model will be developed from these data to aid in predicting the safest alternative antiseizure medications. Together, these findings will optimise informed decision-making about valproate withdrawal and alternative treatment selection, providing immediate and vital information for patients, clinicians and regulators. |
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| 投稿者 | Mbizvo, Gashirai K; Martin, Glen P; Sperrin, Matthew; Bonnett, Laura J; Schofield, Pieta; Buchan, Iain; Lip, Gregory Y H; Marson, Anthony G |
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| 組織名 | Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool;John Moores University and Liverpool Heart & Chest Hospital, Liverpool, United;Kingdom.;Institute of Systems, Molecular and Integrative Biology, Pharmacology and;Therapeutics, University of Liverpool, Liverpool, United Kingdom.;The Walton Centre NHS Foundation Trust, Liverpool, United Kingdom.;Faculty of Biology, Division of Informatics, Imaging and Data Science, Medicine;and Health, University of Manchester, Manchester Academic Health Science Centre,;Manchester, United Kingdom.;University of Liverpool Department of Biostatistics, Liverpool, United Kingdom.;Department of Public Health, Policy and Systems, Institute of Population Health,;University of Liverpool, Liverpool, United Kingdom.;Department of Clinical Medicine, Danish Centre for Health Services Research,;Aalborg University, Aalborg, Denmark. |
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