Identification of patients who will not achieve seizure remission within 5 years on AEDs. (27th November 2018)

• Record Type: Journal Article
• Authors: Hughes, David M.; Bonnett, Laura J.; Czanner, Gabriela; Komárek, Arnošt; Marson, Anthony G.; García-Fiñana, Marta
• Is Part Of: Neurology. Volume 91:Number 22(2018)
• Publication Date: 2018-11-27
• Subjects: Neurology -- Periodicals; Neurology -- Periodicals; Neurologie -- Périodiques; 616.8
• DOI: 10.1212/WNL.0000000000006564
• Languages: English
• ISSNs: 0028-3878

Abstract

Abstract : 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.