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

. 2018 Nov 27 ; 91 (22) : e2035-e2044. [epub] 20181102

Jazyk angličtina Země Spojené státy americké Médium print-electronic

Typ dokumentu časopisecké články, multicentrická studie, randomizované kontrolované studie, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid30389894

Grantová podpora
MR/L010909/1 Medical Research Council - United Kingdom
MR/R024847/1 Medical Research Council - United Kingdom
PDF-2015-08-044 Department of Health - United Kingdom

Odkazy

PubMed 30389894
PubMed Central PMC6282237
DOI 10.1212/wnl.0000000000006564
PII: WNL.0000000000006564
Knihovny.cz E-zdroje

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.

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