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Identification of patients who will not achieve seizure remission within 5 years on AEDs

OBJECTIVE: To identify people with epilepsy who will not achieve a 12-month seizure remission within 5 years of starting treatment. METHODS: The Standard and New Antiepileptic Drug (SANAD) study is the largest prospective study in patients with epilepsy to date. We applied a recently developed multi...

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Detalles Bibliográficos
Autores principales: Hughes, David M., Bonnett, Laura J., Czanner, Gabriela, Komárek, Arnošt, Marson, Anthony G., García-Fiñana, Marta
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6282237/
https://www.ncbi.nlm.nih.gov/pubmed/30389894
http://dx.doi.org/10.1212/WNL.0000000000006564
Descripción
Sumario:OBJECTIVE: To identify people with epilepsy who will not achieve a 12-month seizure remission within 5 years of starting treatment. METHODS: The Standard and New Antiepileptic Drug (SANAD) study is the largest prospective study in patients with epilepsy to date. We applied a recently developed multivariable approach to the SANAD dataset that takes into account not only baseline covariates describing a patient's history before diagnosis but also follow-up data as predictor variables. RESULTS: Changes in number of seizures and treatment history were the most informative time-dependent predictors and were associated with history of neurologic insult, epilepsy type, age at start of treatment, sex, and having a first-degree relative with epilepsy. Our model classified 95% of patients. Of those classified, 95% of patients observed not to achieve remission at 5 years were correctly classified (95% confidence interval [CI] 89.5%–100%), with 51% identified by 3 years and 90% within 4 years of follow-up. Ninety-seven percent (95% CI 93.3%–98.8%) of patients observed to achieve a remission within 5 years were correctly classified. Of those predicted not to achieve remission, 76% (95% CI 58.5%–88.2%) truly did not achieve remission (positive predictive value). The predictive model achieved similar accuracy levels via external validation in 2 independent United Kingdom–based datasets. CONCLUSION: Our approach generates up-to-date predictions of the patient's risk of not achieving seizure remission whenever new clinical information becomes available that could influence patient counseling and management decisions.