Stevelink, Remi;
Al-Toma, Dania;
Jansen, Floor E;
Lamberink, Herm J;
Asadi-Pooya, Ali A;
Farazdaghi, Mohsen;
Cação, Gonçalo;
... Braun, Kees PJ; + view all
(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
, Article 101732. 10.1016/j.eclinm.2022.101732.
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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. FUNDING: MING fonds.
| Type: | Article |
|---|---|
| Title: | 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 |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.eclinm.2022.101732 |
| Publisher version: | https://doi.org/10.1016/j.eclinm.2022.101732 |
| Language: | English |
| Additional information: | © 2022 The Author(s). Published by Elsevier Ltd. under a Creative Commons license (https://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Drug resistance, Individual participant data, JME, Juvenile myoclonic epilepsy, Medication withdrawal, Meta-analysis, Multivariable prediction, Prediction model, Refractory epilepsy, Remission, Seizure recurrence |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Experimental Epilepsy |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10161453 |
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