Modeling remission and relapse in pediatric epilepsy: application of a Markov process
Modeling remission and relapse in pediatric epilepsy: application of a Markov process
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DOI：
10.1016/j.eplepsyres.2004.05.002
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发表时间：
2004-06-01
影响因子：
2.2
通讯作者：
Shinnar, S
中科院分区：
文献类型：
--
作者：
Berg, AT;Lin, JX;Shinnar, S
癫痫发作的结果经常被描述为患者曾经达到缓解或处于晚期缓解。结果更为复杂，多年后可能出现反复缓解和复发。这些是难以量化的标准生存技术用于分析缓解和复发。马尔可夫过程允许人们跟踪病人的状态（缓解或不缓解），为研究反复缓解和复发提供了一种合适的方法。在一项前瞻性社区儿童研究中，从癫痫的初始诊断开始，我们检查了每名患者三次不同缓解期（每次至少1年）反复缓解和复发的可能性。癫痫综合征的作用是分析中考虑的缓解-复发模式的主要决定因素。使用了两种不同的马尔可夫模型，一种涉及三个状态，另一种涉及七个状态。在最初招募的613名儿童中，有602名被随访了至少1年，因此有资格进行分析。几乎90%的患者经历了缓解；然而，几乎一半的人后来又复发了。复发的患者中有81%出现第二次缓解，其中38%再次复发。在第二次复发后，82%的患者出现了第三次缓解，其中58%的患者再次复发。在最初的2年后，大约70%的队列缓解，20%不再缓解并复发，10%从未缓解过。潜在癫痫综合征差异有统计学意义。患有其中一种癫痫性脑病的儿童是所有综合征组中最不可能减轻的。有症状性部分癫痫的儿童比有其他症状的儿童（特发性部分或广泛性、隐源性部分和未分类）更不容易缓解。当考虑到他们随后的缓解和复发史时，最后两组之间的差异变得明显。这些差异在七州模式中表现得最为明显。例如，特发性部分癫痫最有可能进入缓解期，从不复发。相比之下，特发性广泛性和隐源性部分癫痫更容易缓解和反复复发。马尔可夫方法为理解癫痫的缓解和复发结果提供了一种替代标准生存技术。它的优点是，即使在病情波动的情况下，它也允许人们追踪个体的结果。这项技术也将适用于几乎任何反复发作的疾病。(C) 2004 Elsevier B.V.版权所有
Seizure outcome is frequently described in terms of patients ever attaining remission or being in terminal remission. Outcomes are more complicated and, over many years, repeated remission and relapses may occur. These are difficult to quantify with standard survival techniques used in analysis of remission and relapse. The Markov process, which allows one to track a patient's state (remission or not) over time, provides a suitable approach for studying repeated remission and relapse.In a prospective community-based study of children followed from the point of the initial diagnosis of epilepsy, we examined the probability of repeated remission and relapse over up to three different remission episodes (minimum 1 year each) per patient. The role of epilepsy syndrome was the main determinant of remission-relapse patterns considered in the analysis. Two different Markov models were used, one involving three states and the other seven states.Of 613 children initially recruited into the study, 602 were followed at least 1 year and thus eligible for the analysis. Almost 90% of the cohort experienced a remission; however, almost half then relapsed. Second remissions occurred in 81% of those who relapsed of whom 38% relapsed again. A third remission occurred in 82% of those after a second relapse of whom 58% relapsed yet again. After the first 2 years, similar to70% of the cohort was in remission, 20% was no longer in remission having relapsed, and 10% had never been in remission. Significant differences were seen by underlying epilepsy syndrome. Children with one of the epileptic encephalopathies were least likely of all syndrome groups ever to remit. Those with symptomatic partial epilepsies were less likely to remit than children with any of the other syndromes, idiopathic partial or generalized, cryptogenic partial, and unclassified. Differences between these last groups became apparent when considering their subsequent remission and relapse histories. These differences were best seen in the seven-state model. For example, idiopathic partial epilepsies were most likely to enter remission and never relapse. By contrast, idiopathic generalized and cryptogenic partial epilepsies were more likely to remit and relapse repeatedly.The Markov approach provides an alternative to standard survival techniques for understanding remission and relapse outcomes in epilepsy. Its advantage is that it allows one to track the individuals' outcome over time even as the condition fluctuates. The technique would also be applicable in virtually any remitting-relapsing disorder. (C) 2004 Elsevier B.V. All rights reserved.