Deciding When Less Is More: The Crossroads of Withdrawing Antiepileptic Drugs

Commentary

Can Electroencephalograms Provide Guidance for the Withdrawal of Antiepileptic Drugs: A Meta-Analysis.

Tang L, Xiao Z. 2017;128:297–302.

OBJECTIVE: The discontinuation of antiepileptic drugs (AEDs) is an important treatment decision for epilepsy patients who have been seizure-free for 2 years 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.

Individualised Prediction Model of Seizure Recurrence and Long-Term Outcomes After Withdrawal of Antiepileptic Drugs in Seizure-Free Patients: A Systematic Review and Individual Participant Data Meta-Analysis.

Lamberink HJ, Otte WM, Geerts AT, Pavlovic M, Ramos-Lizana J, Marson AG, Overweg J, Sauma L, Specchio LM, Tennison M, Cardoso TMO, Shinnar S, Schmidt D, Geleijns K, Braun KPJ. 2017;16:523–531.

BACKGROUND: People with epilepsy who became seizure-free while taking antiepileptic drugs might consider discontinuing their medication, with the possibility of increased quality of life because of the elimination of adverse events. The risk with this action, however, is seizure recurrence. The objectives of our study were to identify predictors of seizure recurrence and long-term seizure outcomes and to produce nomograms for estimation of individualised outcomes. METHODS: We did a systematic review and meta-analysis, and identified eligible articles and candidate predictors, using PubMed and Embase databases with a last update on Nov 6, 2014. Eligible articles had to report on cohorts of patients with epilepsy who were seizure-free and had started withdrawal of antiepileptic drugs; articles also had to contain information regarding seizure recurrences during and after withdrawal. We excluded surgical cohorts, reports with fewer than 30 patients, and reports on acute symptomatic seizures because these topics were beyond the scope of our objective. Risk of bias was assessed using the Quality in Prognosis Studies system. Data analysis was based on individual participant data. Survival curves and proportional hazards were computed. The strongest predictors were selected with backward selection. Models were converted to nomograms and a web-based tool to determine individual risks. FINDINGS: We identified 45 studies with 7082 patients; ten studies (22%) with 1769 patients (25%) were included in the meta-analysis. Median follow-up was 5.3 years (IQR 3.0–10.0, maximum 23 years). Prospective and retrospective studies and randomised controlled trials were included, covering non-selected and selected populations of both children and adults. Relapse occurred in 812 (46%) of 1769 patients; 136 (9%) of 1455 for whom data were available had seizures in their last year of follow-up, suggesting enduring seizure control was not regained by this timepoint. Independent predictors of seizure recurrence were epilepsy duration before remission, seizure-free interval before antiepileptic drug withdrawal, age at onset of epilepsy, history of febrile seizures, number of seizures before remission, absence of a self-limiting epilepsy syndrome, developmental delay, and epileptiform abnormality on electroencephalogram (EEG) before withdrawal. Independent predictors of seizures in the last year of follow-up were epilepsy duration before remission, seizure-free interval before antiepileptic drug withdrawal, number of antiepileptic drugs before withdrawal, female sex, family history of epilepsy, number of seizures before remission, focal seizures, and epileptiform abnormality on EEG before withdrawal. Adjusted concordance statistics were 0.65 (95% CI 0.65–0.66) for predicting seizure recurrence and 0.71 (0.70–0.71) for predicting long-term seizure freedom. Validation was stable across the individual study populations. INTERPRETATION: We present evidence-based nomograms with robust performance across populations of children and adults. The nomograms facilitate prediction of outcomes following drug withdrawal for the individual patient, including both the risk of relapse and the chance of long-term freedom from seizures. The main limitations were the absence of a control group continuing antiepileptic drug treatment and a consistent definition of long-term seizure freedom.

Epilepsy, a disease characterized by recurrent seizures, is often associated with fear of dying, as well as of losing employment, of driving rights and of independence. It is not surprising that most patients and their treating physicians are often hesitant to withdraw antiepileptic drugs (AEDs) once seizure freedom has been achieved. With a seizure recurrence rate estimated to be around 34% (1) after AED withdrawal the decision to taper off these medications is never taken lightly. However, medication side effects and cost add to the burden of a disease already difficult to live with due to its stigma and psychosocial consequences (2). Hence, all of these factors should be taken into consideration when faced with the question of whether to withdraw AEDs in seizure-free patients. Sometimes this holistic approach may make the decision harder, especially given that each patient has a unique presentation and distinct needs.

In a world where medicine is moving towards simplification and tailoring of treatment to the patients' specific needs, the development of a systematic individualized approach to address the issue of AED withdrawal is extremely useful, if not indispensable, for clinicians that encounter this issue routinely in their daily practice. Herein lies the value of Dr. Lamberink and colleagues predictive nomograms, designed as tools to estimate the risk of seizure recurrence after AED withdrawal. While some predictors of seizure recurrence had been previously identified, the use these predictors in clinical practice has remained a dilemma, particularly in patients with some predictors in favor and others against discontinuation of treatment.

This study's elegant design involved a systematic review of the literature with subsequent meta-analysis of individual participant data (IPD) from original studies. The strongest predictors of seizure recurrence were identified and utilized for the development of predictive nomograms that were subsequently submitted to internal-external cross-validation. The adjusted concordance statistics were 0.65 (95% CI 0.65–0.66) and 0.71 (95% CI 0.70–0.71), for predicting seizure recurrence and long term seizure freedom respectively, demonstrating that these nomograms can be widely used across populations.

The IPD meta-analysis revealed seizure recurrence in 812 (46%) of 1,769 seizure-free patients after AED withdrawal. However, 136 (9%) of 1,455 patients with available information experienced seizures in the last year of follow up, suggesting that seizure freedom was not regained after the re-introduction of AEDs in these patients. Although there is no proof of causality between AED withdrawal and the subsequent development of treatment-resistant epilepsy (3), the risk of not being able to regain seizure freedom after discontinuation of therapy should be considered and discussed with the patient.

An individualized risk-benefit assessment is the best approach to tackle this challenging clinical question. Dr. Lambe rink and colleagues provide us with a tool to assess the risk of seizure recurrence beyond the “2 year seizure freedom rule” (4). Moreover, this new approach makes generalization of the 2-year mark an obsolete concept. The nomogram for predicting the likelihood of long-term seizure freedom is also helpful when making the final decision to stop AEDs, as it provides a concrete point of comparison when considering the alternative of long-term AED use with its associated side effects. While many of the newer AEDs have a better side effect profile than older agents, one must not understate the economic and psychosocial impact of taking a daily medication (5).

Lastly, these nomograms decrease the weight placed on the already overemphasized EEG, where the predictive value has to be evaluated in the context of the distinctive characteristics of the patient in question. In this study, any EEG abnormalities in the absence of other predictive factors increased the risk of seizure recurrence only minimally. Hence, isolated EEG abnormalities should not prevent withdrawal of a medication. In addition, when relying solely on EEG data to predict the likelihood of seizure recurrence, the duration of the study always comes into question. How long of a recording is long enough in order to confer predictive value to the EEG findings?

The use of multiple additional strong predictors in these nomograms provide a more comprehensive approach. In addition to the presence of EEG abnormalities, the strongest predictors for seizure recurrence used in the first nomogram include epilepsy duration before remission, seizure-free interval before AED withdrawal, age at onset of seizures, history of febrile seizures, number of seizures before remission (ten or more), the absence of a self-limiting epilepsy syndrome, and intelligence quotient (IQ) below 70. To predict long-term seizure freedom, the second nomogram uses a slightly different set of independent factors, which include positive family history of epilepsy in a first or second-degree relative.

For our convenience the authors have created an easy to use web-based tool for AED withdrawal based on these nomograms ((http://epilepsypredictiontools.info), which facilitate the formulation of a final recommendation and the counseling of our patients.