PDF(Pubmed)
Abstract：
UNASSIGNED: 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.
UNASSIGNED: 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/).
UNASSIGNED: 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).
UNASSIGNED: 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.
UNASSIGNED: MING fonds.
UNASSIGNED: 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/).
UNASSIGNED: 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).
UNASSIGNED: 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.
UNASSIGNED: MING fonds.
摘要：
未经证实：三分之一的青少年肌阵挛性癫痫（JME）患者具有耐药性。四分之三的人在实现无癫痫发作后尝试撤回抗癫痫药物（ASM）时癫痫发作复发。目前无法预测谁可能会产生耐药性并安全退出治疗。我们旨在确定耐药性和癫痫发作复发的预测因子，以便对JME患者的治疗结果进行个性化预测。
UNASSIGNED：我们基于EMBASE和PubMed的系统搜索进行了个体参与者数据（IPD）荟萃分析-最新更新于2021年3月11日-包括前瞻性和回顾性观察性研究，报告了诊断为JME的患者的治疗结果和至少一年随访后的可用癫痫发作结果数据。我们邀请作者分享标准化的IPD，以使用多变量逻辑回归确定耐药性的预测因素。我们排除了伪抗性个体。试图撤回ASM的子集被纳入ASM撤回后癫痫发作复发的多变量比例风险分析。该研究已在开放科学框架（OSF;https://osf.io/b9zjc/）上注册。
未经ASSIGNED：我们的搜索产生了1641篇文章；53是合格的，其中24项研究的作者同意通过共享IPD进行合作。使用来自2518名JME患者的数据，我们发现了九种独立的耐药性预测因子：三种癫痫发作类型，精神病合并症,月经性癫痫,癫痫样病灶,种族,CAE的历史,癫痫家族史,癫痫持续状态,和高热惊厥.我们的多变量模型的内部-外部交叉验证显示受试者工作特征曲线下的面积为0·70（95CI0·68-0·72）。ASM戒断后癫痫发作的复发（n=368）由戒断开始时的较早年龄预测，更短的无癫痫发作间隔和更多当前使用的ASM，导致平均内部-外部交叉验证一致性统计量为0·70（95CI0·68-0·73）。
UNASSIGNED：我们能够预测和验证JME患者的临床相关个性化治疗结果。个性化预测可以作为列线图和基于Web的工具访问。
未经批准：明方。
UNASSIGNED：我们基于EMBASE和PubMed的系统搜索进行了个体参与者数据（IPD）荟萃分析-最新更新于2021年3月11日-包括前瞻性和回顾性观察性研究，报告了诊断为JME的患者的治疗结果和至少一年随访后的可用癫痫发作结果数据。我们邀请作者分享标准化的IPD，以使用多变量逻辑回归确定耐药性的预测因素。我们排除了伪抗性个体。试图撤回ASM的子集被纳入ASM撤回后癫痫发作复发的多变量比例风险分析。该研究已在开放科学框架（OSF;https://osf.io/b9zjc/）上注册。
未经ASSIGNED：我们的搜索产生了1641篇文章；53是合格的，其中24项研究的作者同意通过共享IPD进行合作。使用来自2518名JME患者的数据，我们发现了九种独立的耐药性预测因子：三种癫痫发作类型，精神病合并症,月经性癫痫,癫痫样病灶,种族,CAE的历史,癫痫家族史,癫痫持续状态,和高热惊厥.我们的多变量模型的内部-外部交叉验证显示受试者工作特征曲线下的面积为0·70（95CI0·68-0·72）。ASM戒断后癫痫发作的复发（n=368）由戒断开始时的较早年龄预测，更短的无癫痫发作间隔和更多当前使用的ASM，导致平均内部-外部交叉验证一致性统计量为0·70（95CI0·68-0·73）。
UNASSIGNED：我们能够预测和验证JME患者的临床相关个性化治疗结果。个性化预测可以作为列线图和基于Web的工具访问。
未经批准：明方。
