Withdrawal of antiepileptic drugs in young patients with cryptogenic focal epilepsies

Abnormal electroencephalogram (EEG) after drug withdrawal is a risk factor for epilepsy recurrence in children: a systematic review and meta-analysis

BACKGROUND

The relationship between abnormal electroencephalogram (EEG) and epilepsy recurrence after antiepileptic drug (AED) withdrawal has been controversial. We aimed to explore the relationship between abnormal EEG after AED withdrawal and the risk of epilepsy recurrence in children.

METHODS

Literature retrieval was performed using the PubMed, EMBASE, Medline, CENTRAL, and China National Knowledge Infrastructure (CNKI) databases. Included literatures were subjects of pediatric epilepsy patients who discontinued medication. The recurrence rate of epilepsy in patients with normal and abnormal EEG after AED withdrawal was observed. The Newcastle-Ottawa scale (NOS) was used to evaluate the quality of literatures. The Chi-square test was used to test heterogeneity. If heterogeneity between the articles existed, a random-effects model was used; otherwise, fixed-effects models were used. Subgroup analysis was used to explore the causes of heterogeneity. The odds ratio (OR) and 95% confidence interval (CI) were calculated using the Mantel-Haenszel statistical method. OR was not adjusted for other factors.

RESULTS

A total of 843 articles were retrieved. Nine studies were included, with a total of 1,663 patients, including 1,299 patients with normal EEG and 364 patients with abnormal EEG. Compared with the normal EEG patients, the OR of recurrence rate after AEDs withdrawal was 3.02 (P=0.0003), with heterogeneity (P<0.0001). The funnel plot indicated that there was no publication bias among the studies. The not partial seizure group analysis showed OR =1.70 (P=0.003) and no heterogeneity (P=0.70) in patients with abnormal EEG compared to those with normal EEG. In the partial seizures subgroup, the OR of the recurrence rate after AED withdrawal was 8.08 (P<0.00001) compared with the normal EEG patients, and there was no heterogeneity (P=0.29). The funnel chart shows that the partial seizures type subgroup analysis revealed positive results, while the not partial seizure group analysis reported negative results, indicating publication bias.

CONCLUSIONS

The risk of epilepsy recurrence is higher in children with abnormal EEG after AED withdrawal, regardless of seizure type. For pediatric epilepsy patients with abnormal EEG after AED withdrawal, a more cautious discontinuation regimen, closer follow-up and monitoring are required.

Risk of seizure recurrence from antiepileptic drug withdrawal among seizure-free patients for more than two years

OBJECTIVE

The aim of this study was to determine the outcome of antiepileptic drug (AED) withdrawal in patients who were seizure-free for more than two years.

METHODS

Patients with epilepsy who were seizure-free for at least two years and decided to stop AED therapy gradually were followed up every two months for seizure relapse. The inclusion criteria were as follows: (1) diagnosis of epilepsy, defined as the following conditions: ① at least two unprovoked (or reflex) seizures occurring >24 h apart; ② one unprovoked (or reflex) seizure and a probability of further seizures similar to the general recurrence risk (at least 60%) after two unprovoked seizures, occurring over the next 10 years; ③ diagnosis of an epilepsy syndrome; (2) patients remained seizure-free for at least 24 consecutive months during AED therapy; and (3) patients expressed a desire to discontinue AED therapy gradually and agreed to return for regular follow-ups. The time to a seizure relapse and predictive factors were analyzed by survival methods, including sex; age at seizure onset; number of episodes; seizure-free period before AED withdrawal; duration of follow-up after AED withdrawal; AED tapering off period (taper period); results from brain magnetic resonance (MRI); electroencephalogram (EEG) after drug withdrawal; EEG before drug withdrawal; seizure type (classified as generalized, partial, or multiple types based on history); and the number of AEDs administered for long-term seizure control. A log-rank test was used for univariate analysis, and a Cox proportional hazard model was used for multivariate analysis.

RESULTS

We selected 94 patients (58 men, 36 women). The relapse ratio was 29.8%. Univariate analysis and multivariate Cox regression analysis indicated that withdrawal times and multiple AEDs, as well as the seizure-free period before withdrawal and abnormal EEG after drug withdrawal were significantly correlated with seizure recurrence and were significant independent predictive factors, with a hazard ratio of 0.839 and 3.971, 0.957, and 3.684, respectively.

SIGNIFICANCE

The relapse rate in our study was similar to commonly reported overall rates for epilepsy. Distinguishing variables, such as withdrawal times, multiple AEDs, seizure-free period before withdrawal, and abnormal EEG after drug withdrawal, need to be considered when choosing to withdraw from AEDs. Therefore, our recommendation is that after two years of seizure-free survival, patients could consider withdrawal unless they have hippocampal sclerosis (HS).

Relative Seizure Relapse Risks Associated with Antiepileptic Drug Withdrawal After Different Seizure-Free Periods in Adults with Focal Epilepsy: A Prospective, Controlled Follow-Up Study

BACKGROUND

Approximately two-thirds of patients with newly diagnosed epilepsy become seizure-free after antiepileptic drug (AED) treatment. A crucial issue for these patients and their families, especially after a long period of seizure freedom, is when to stop their medications.

OBJECTIVE

The aim of this study was to identify the optimal timing of AED withdrawal in adults with focal epilepsy who had been seizure-free for ≥ 2 years.

METHODS

Adults with focal epilepsy who had been seizure-free for ≥ 2 years were recruited. Based on their decision to discontinue (withdrawal) or continue (non-withdrawal) AED treatment, patients were assigned to withdrawal or non-withdrawal subgroups according to the length of remission (2 to < 3 years, 3 to < 4 years, 4 to < 5 years and ≥ 5 years). The relapse risks of the withdrawal and corresponding non-withdrawal subgroups were compared, and the relative relapse risks were assessed in a Cox proportional hazard regression model.

RESULTS

A total of 213 eligible patients began to withdraw from AED treatment; 70 had been seizure-free for 2 to < 3 years, 62 had been seizure-free for 3 to < 4 years, 37 had been seizure-free for 4 to < 5 years and 44 had been seizure-free for ≥ 5 years. The figures for the corresponding non-withdrawal subgroups were 463, 334, 251 and 182, respectively. There was a significantly higher risk of seizure relapse in patients withdrawing from AEDs after 2 to < 5 years of seizure freedom than in the corresponding non-withdrawal controls, and the relative relapse risk was 3.052 (95% confidence interval [CI] 2.126-4.381; p < 0.001) for the seizure-free period of 2 to < 3 years, 3.617 (95% CI 2.384-5.488; p < 0.001) for 3 to < 4 years and 2.644 (95% CI 1.456-4.799; p = 0.001) for 4 to < 5 years. However, for patients who were seizure-free for ≥ 5 years, AED withdrawal did not significantly increase the risk of seizure relapse compared with that of patients continuing treatment (hazard ratio [HR] 1.362, 95% CI 0.634-2.926, p = 0.428). Compared with a seizure-free period of 2 to < 3 years, the relative relapse risk after AED withdrawal was significantly reduced only after being seizure-free for ≥ 5 years (HR 0.441, 95% CI 0.233-0.834; p = 0.012).

CONCLUSION

Overall, for adults with focal epilepsy, withdrawal from AEDs significantly increased the risk of seizure relapse after being seizure-free for 2 to < 5 years, but might not increase the risk if the seizure-free period was ≥ 5 years.

Correlation between EEG during AED withdrawal and epilepsy recurrence: a meta-analysis

To assess the risk of epilepsy recurrence after withdrawal from antiepileptic drugs (AEDs), researchers extensively studied recurrence-related risk factors, including electroencephalogram (EEG) during AED withdrawal. The relationship between EEG and epilepsy recurrence is controversial. We used meta-analysis to determine the correlation between EEG during AED withdrawal and epilepsy recurrence. A total of seven studies met the criteria for inclusion. The Newcastle-Ottawa Scale was used to conduct the research quality evaluation. Seven hundred three patients were included in meta-analysis. Patients with abnormal EEGs during withdrawal had a higher recurrence rate than patients with normal EEGs. Abnormal EEGs during withdrawal were a risk factor for recurrence.

Can electroencephalograms provide guidance for the withdrawal of antiepileptic drugs: A meta-analysis

OBJECTIVE

The discontinuation of antiepileptic drugs (AEDs) is an important treatment decision for epilepsy patients who have been seizure-free for 2years or longer. Some patients experience seizures relapse after AED withdrawal. The prognostic value of electroencephalograms (EEGs) for seizure relapse following AED withdrawal is controversial. To our knowledge, this is the first meta-analysis to address whether EEG data can be used to guide the discontinuation of AEDs.

METHOD

We performed a meta-analysis of cohort studies that reported original EEG data from before AED withdrawal and recurrence after AED-withdrawal. The quality of each study was assessed using the Newcastle-Ottawa Scale.

RESULTS

Fifteen studies including a total of 2349 participants were included in this meta-analysis. This meta-analysis of 15 studies demonstrates that an abnormal electroencephalogram was a predictor of the risk of relapse. Additionally, paroxysmal, slowing, spike and wave activities on electroencephalograms were associated with increased risk of relapse.

CONCLUSION

We reveal that abnormal EEG records, particularly paroxysmal abnormalities, before AED withdrawal predicted a high risk of relapse. Slowing and spike and wave activities also exhibited moderate predictive values.

SIGNIFICANCE

Our findings suggest that, EEGs might be an important prognostic tool for antiepileptic drug reduction.