Back to Search Start Over

Predictive models for starting antiseizure medication withdrawal following epilepsy surgery in adults

Authors :
Carolina Ferreira-Atuesta
Jane de Tisi
Andrew W McEvoy
Anna Miserocchi
Jean Khoury
Ruta Yardi
Deborah T Vegh
James Butler
Hamin J Lee
Victoria Deli-Peri
Yi Yao
Feng-Peng Wang
Xiao-Bin Zhang
Lubna Shakhatreh
Pakeeran Siriratnam
Andrew Neal
Arjune Sen
Maggie Tristram
Elizabeth Varghese
Wendy Biney
William P Gray
Ana Rita Peralta
Alexandre Rainha-Campos
António J C Gonçalves-Ferreira
José Pimentel
Juan Fernando Arias
Samuel Terman
Robert Terziev
Herm J Lamberink
Kees P J Braun
Willem M Otte
Fergus J Rugg-Gunn
Walter Gonzalez
Carla Bentes
Khalid Hamandi
Terence J O’Brien
Piero Perucca
Chen Yao
Richard J Burman
Lara Jehi
John S Duncan
Josemir W Sander
Matthias Koepp
Marian Galovic
Publication Year :
2022
Publisher :
Cold Spring Harbor Laboratory, 2022.

Abstract

More than half of adults with epilepsy undergoing resective epilepsy surgery achieve long-term seizure freedom and might consider withdrawing antiseizure medications. We aimed to identify predictors of seizure recurrence after starting postoperative antiseizure medication withdrawal and develop and validate predictive models. We performed an international multicentre observational cohort study in nine tertiary epilepsy referral centres. We included 850 adults who started antiseizure medication withdrawal following resective epilepsy surgery and were free of seizures other than focal non-motor aware seizures before starting antiseizure medication withdrawal. We developed a model predicting recurrent seizures, other than focal non-motor aware seizures, using Cox proportional hazards regression in a derivation cohort (n = 231). Independent predictors of seizure recurrence, other than focal non-motor aware seizures, following the start of antiseizure medication withdrawal were focal non-motor aware seizures after surgery and before withdrawal [adjusted hazard ratio (aHR) 5.5, 95% confidence interval (CI) 2.7–11.1], history of focal to bilateral tonic-clonic seizures before surgery (aHR 1.6, 95% CI 0.9–2.8), time from surgery to the start of antiseizure medication withdrawal (aHR 0.9, 95% CI 0.8–0.9) and number of antiseizure medications at time of surgery (aHR 1.2, 95% CI 0.9–1.6). Model discrimination showed a concordance statistic of 0.67 (95% CI 0.63–0.71) in the external validation cohorts (n = 500). A secondary model predicting recurrence of any seizures (including focal non-motor aware seizures) was developed and validated in a subgroup that did not have focal non-motor aware seizures before withdrawal (n = 639), showing a concordance statistic of 0.68 (95% CI 0.64–0.72). Calibration plots indicated high agreement of predicted and observed outcomes for both models. We show that simple algorithms, available as graphical nomograms and online tools (predictepilepsy.github.io), can provide probabilities of seizure outcomes after starting postoperative antiseizure medication withdrawal. These multicentre-validated models may assist clinicians when discussing antiseizure medication withdrawal after surgery with their patients.

Subjects

Subjects :
Neurology (clinical)

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....e034b99b0aeeb36ef837c3273895c6d8
Full Text :
https://doi.org/10.1101/2022.07.22.22277802