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成人癫痫手术后抗癫痫药物停药的预测模型。

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

机构信息

Department of Clinical and Experimental Epilepsy (DCEE), NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK.

Chalfont Centre for Epilepsy, Chalfont St Peter, Bucks SL9 0RJ, UK.

出版信息

Brain. 2023 Jun 1;146(6):2389-2398. doi: 10.1093/brain/awac437.

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.

摘要

超过一半的接受癫痫切除术的癫痫成人在长期无癫痫发作后,可能会考虑停止抗癫痫药物治疗。我们旨在确定术后开始抗癫痫药物停药后癫痫复发的预测因素,并开发和验证预测模型。我们在 9 个三级癫痫转诊中心进行了一项国际多中心观察性队列研究。我们纳入了 850 名在接受癫痫手术后开始抗癫痫药物停药且在开始抗癫痫药物停药前无除局灶性非运动性意识外的癫痫发作的成年人。我们在一个推导队列(n = 231)中使用 Cox 比例风险回归来开发预测除局灶性非运动性意识外的癫痫复发的模型。抗癫痫药物停药后开始出现癫痫复发的局灶性非运动性意识外的独立预测因素包括术后和停药前的局灶性非运动性意识外癫痫发作(调整后的危险比[aHR] 5.5,95%置信区间[CI] 2.7-11.1)、术前局灶性到双侧强直阵挛性癫痫发作史(aHR 1.6,95%CI 0.9-2.8)、手术至开始抗癫痫药物停药的时间(aHR 0.9,95%CI 0.8-0.9)和手术时的抗癫痫药物数量(aHR 1.2,95%CI 0.9-1.6)。在外部验证队列(n = 500)中,模型鉴别显示一致性统计量为 0.67(95%CI 0.63-0.71)。在未在停药前出现局灶性非运动性意识外癫痫发作的亚组中开发并验证了预测任何癫痫发作(包括局灶性非运动性意识外癫痫发作)复发的二级模型,一致性统计量为 0.68(95%CI 0.64-0.72)。校准图表明,两个模型的预测结果与观察结果高度一致。我们表明,简单的算法,以图形列线图和在线工具(predictepilepsy.github.io)的形式提供,可在术后开始抗癫痫药物停药后提供癫痫发作结果的概率。这些经过多中心验证的模型可能有助于临床医生在与患者讨论手术后抗癫痫药物停药时使用。

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