Individualised prediction of drug resistance and seizure recurrence after medication withdrawal in people with juvenile myoclonic epilepsy: A systematic review and individual participant data meta-analysis

Stevelink, R. et al. (2022) Individualised prediction of drug resistance and seizure recurrence after medication withdrawal in people with juvenile myoclonic epilepsy: A systematic review and individual participant data meta-analysis. EClinicalMedicine, 53, 101732. (doi: 10.1016/j.eclinm.2022.101732) (PMID:36467455) (PMCID:PMC9716332)

Abstract

Background: A third of people with juvenile myoclonic epilepsy (JME) are drug-resistant. Three-quarters have a seizure relapse when attempting to withdraw anti-seizure medication (ASM) after achieving seizure-freedom. It is currently impossible to predict who is likely to become drug-resistant and safely withdraw treatment. We aimed to identify predictors of drug resistance and seizure recurrence to allow for individualised prediction of treatment outcomes in people with JME. Methods: We performed an individual participant data (IPD) meta-analysis based on a systematic search in EMBASE and PubMed – last updated on March 11, 2021 – including prospective and retrospective observational studies reporting on treatment outcomes of people diagnosed with JME and available seizure outcome data after a minimum one-year follow-up. We invited authors to share standardised IPD to identify predictors of drug resistance using multivariable logistic regression. We excluded pseudo-resistant individuals. A subset who attempted to withdraw ASM was included in a multivariable proportional hazards analysis on seizure recurrence after ASM withdrawal. The study was registered at the Open Science Framework (OSF; https://osf.io/b9zjc/). Findings: Our search yielded 1641 articles; 53 were eligible, of which the authors of 24 studies agreed to collaborate by sharing IPD. Using data from 2518 people with JME, we found nine independent predictors of drug resistance: three seizure types, psychiatric comorbidities, catamenial epilepsy, epileptiform focality, ethnicity, history of CAE, family history of epilepsy, status epilepticus, and febrile seizures. Internal-external cross-validation of our multivariable model showed an area under the receiver operating characteristic curve of 0·70 (95%CI 0·68–0·72). Recurrence of seizures after ASM withdrawal (n = 368) was predicted by an earlier age at the start of withdrawal, shorter seizure-free interval and more currently used ASMs, resulting in an average internal-external cross-validation concordance-statistic of 0·70 (95%CI 0·68–0·73). Interpretation: We were able to predict and validate clinically relevant personalised treatment outcomes for people with JME. Individualised predictions are accessible as nomograms and web-based tools.

• Item Type: Articles
• Keywords: Remission, seizure recurrence, juvenile myoclonic epilepsy, drug resistance, meta-analysis, medication withdrawal, individual participant data, multivariable prediction, JME, prediction model, refractory epilepsy.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Stephen, Dr Linda and Brodie, Professor Martin
• Authors: Stevelink, R., Al-Toma, D., Jansen, F. E., Lamberink, H. J., Asadi-Pooya, A. A., Farazdaghi, M., Cação, G., Jayalakshmi, S., Patil, A., Özkara, Ç., Aydın, Ş., Gesche, J., Beier, C. P., Stephen, L. J., Brodie, M. J., Unnithan, G., Radhakrishnan, A., Höfler, J., Trinka, E., Krause, R., Irelli, E. C., Di Bonaventura, C., Szaflarski, J. P., Hernández-Vanegas, L. E., Moya-Alfaro, M. L., Zhang, Y., Zhou, D., Pietrafusa, N., Specchio, N., Japaridze, G., Beniczky, S., Janmohamed, M., Kwan, P., Syvertsen, M., Selmer, K. K., Vorderwülbecke, B. J., Holtkamp, M., Viswanathan, L. G., Sinha, S., Baykan, B., Altindag, E., von Podewils, F., Schulz, J., Seneviratne, U., Viloria-Alebesque, A., Karakis, I., D'Souza, W. J., Sander, J. W., Koeleman, B. P. C., Otte, W. M., and Braun, K. P. J.
• College/School: College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing
• Journal Name: EClinicalMedicine
• Publisher: Elsevier
• ISSN: 2589-5370
• ISSN (Online): 2589-5370
• Published Online: 11 November 2022
• Copyright Holders: Copyright © 2022 The Authors
• First Published: First published in EClinicalMedicine 53:101732
• Publisher Policy: Reproduced under a Creative Commons licence