Prognostic Value of Generalized Polyspike Trains and Prolonged Epileptiform EEG Runs

Gauging and controlling excitability in cortical disorders

PURPOSE OF REVIEW

Cortical excitability, defined as the cortex's responsiveness to incoming stimuli, is a fundamental concept in neuroscience and a targetable mechanism for controlling brain dysfunctions such as epilepsy, as well as other neurological and psychiatric disorders. In this review, we delineate the boundaries between physiological and pathological excitability, highlighting recent theoretical, experimental, and translational advances relevant to human brain disorders. Specifically, we describe the dynamic regulation of cortical excitability and propose practical means to monitor its known fluctuations as to guide therapeutic interventions.

RECENT FINDINGS

From a conceptual standpoint, the last decade of research on cortical excitability has benefited from dynamical systems theory, which studies the behavior of nonlinear systems (here, the cortex) and their resilience to perturbations in different conditions (here, variable excitability). We review how fundamental relationships between excitability and resilience were verified in the brain in a series of recent studies. We also review natural fluctuations in cortical excitability, and how these may open windows of vulnerability for the expression of cortical dysfunctions. We then turn to the practicalities of measuring and monitoring cortical excitability, a latent variable that must be actively probed.

SUMMARY

Practical means for gauging cortical excitability likely have broad applicability. To enable new developments in clinical practice, a principled design of pharmacological and neurostimulation therapies must leverage current understanding of cortical dynamics.

Seizure Cycles under Pharmacotherapy

OBJECTIVE

This study was undertaken to determine the effects of antiseizure medications (ASMs) on multidien (multiday) cycles of interictal epileptiform activity (IEA) and seizures and evaluate their potential clinical significance.

METHODS

We retrospectively analyzed up to 10 years of data from 88 of the 256 total adults with pharmacoresistant focal epilepsy who participated in the clinical trials of the RNS System, an intracranial device that keeps records of IEA counts. Following adjunctive ASM trials, we evaluated changes over months in (1) rates of self-reported disabling seizures and (2) multidien IEA cycle strength (spectral power for periodicity between 4 and 40 days). We used a survival analysis and the receiver operating characteristics to assess changes in IEA as a predictor of seizure control.

RESULTS

Among 56 (33.3%) of the 168 adjunctive ASM trials suitable for analysis, ASM introduction was followed by an average 50 to 70% decrease in multidien IEA cycle strength and a concomitant 50 to 70% decrease in relative seizure rate for up to 12 months. Individuals with a ≥50% decrease in IEA cycle strength in the first 3 months of an ASM trial had a higher probability of remaining seizure responders (≥50% seizure rate reduction, p < 10-7) or super-responders (≥90%, p < 10-8) over the next 12 months.

INTERPRETATION

In this large cohort, a decrease in multidien IEA cycle strength following initiation of an adjunctive ASM correlated with seizure control for up to 12 months, suggesting that fluctuations in IEA mirror "disease activity" in pharmacoresistant focal epilepsy and may have clinical utility as a biomarker to predict treatment response. ANN NEUROL 2024;95:743-753.

Drug-resistant juvenile myoclonic epilepsy: A literature review

The ILAE's Task Force on Nosology and Definitions revised in 2022 its definition of juvenile myoclonic epilepsy (JME), the most common idiopathic generalized epilepsy disorder, but this definition may well change again in the future. Although good drug response could almost be a diagnostic criterion for JME, drug resistance (DR) is observed in up to a third of patients. It is important to distinguish this from pseudoresistance, which is often linked to psychosocial problems or psychiatric comorbidities. After summarizing these aspects and the various definitions applied to JME, the present review lists the risk factors for DR-JME that have been identified in numerous studies and meta-analyses. The factors most often cited are absence seizures, young age at onset, and catamenial seizures. By contrast, photosensitivity seems to favor good treatment response, at least in female patients. Current hypotheses on DR mechanisms in JME are based on studies of either simple (e.g., cortical excitability) or more complex (e.g., anatomical and functional connectivity) neurophysiological markers, bearing in mind that JME is regarded as a neural network disease. This research has revealed correlations between the intensity of some markers and DR, and above all shed light on the role of these markers in associated neurocognitive and neuropsychiatric disorders in both patients and their siblings. Studies of neurotransmission have mainly pointed to impaired GABAergic inhibition. Genetic studies have generally been inconclusive. Increasing restrictions have been placed on the use of valproate, the standard antiseizure medication for this syndrome, owing to its teratogenic and developmental risks. Levetiracetam and lamotrigine are prescribed as alternatives, as is vagal nerve stimulation, and there are several other promising antiseizure drugs and neuromodulation methods. The development of better alternative treatments is continuing to take place alongside advances in our knowledge of JME, as we still have much to learn and understand.

The landscape of drug resistant absence seizures in adolescents and adults: Pathophysiology, electroclinical spectrum and treatment options

The persistence of typical absence seizures (AS) in adolescence and adulthood may reduce the quality of life of patients with genetic generalized epilepsies (GGEs). The prevalence of drug resistant AS is probably underestimated in this patient population, and treatment options are relatively scarce. Similarly, atypical absence seizures in developmental and epileptic encephalopathies (DEEs) may be unrecognized, and often persist into adulthood despite improvement of more severe seizures. These two seemingly distant conditions, represented by typical AS in GGE and atypical AS in DEE, share at least partially overlapping pathophysiological and genetic mechanisms, which may be the target of drug and neurostimulation therapies. In addition, some patients with drug-resistant typical AS may present electroclinical features that lie in between the two extremes represented by these generalized forms of epilepsy.

Epilepsy with generalized tonic-clonic seizures alone: Electroclinical features and prognostic patterns

OBJECTIVE

Epilepsy with generalized tonic-clonic seizures alone (GTCA) is a common but poorly characterized idiopathic generalized epilepsy (IGE) syndrome. Hence, we investigated electroclinical features, seizure outcome, and antiseizure medication (ASM) withdrawal in a large cohort of GTCA patients.

METHODS

In this multicenter retrospective study, GTCA patients defined according to the diagnostic criteria of the International League Against Epilepsy (2022) were included. We investigated prognostic patterns, drug resistance at the last visit, and ASM withdrawal, along with their prognostic factors.

RESULTS

We included 247 patients with a median (interquartile range [IQR]) age at onset of 17 years (13-22) and a median follow-up duration of 10 years (IQR = 5-20). Drug resistance at the last visit was observed in 40 (16.3%) patients, whereas the median latency to achieve 2-year remission was 24 months (IQR = 24-46.5) with a median number of 1 (IQR = 1-2) ASM. During the long-term follow-up (i.e., 202 patients followed ≥5-years after the first ASM trial), 69 (34.3%) patients displayed an early remission pattern and 36 (17.9%) patients displayed a late remission pattern, whereas 16 (8%) and 73 (36.3%) individuals had no-remission and relapsing-remitting patterns, respectively. Catamenial seizures and morning predominance of generalized tonic-clonic seizures (GTCS) independently predicted drug resistance at the last visit according to multivariable logistic regression. Treatment withdrawal was attempted in 63 (25.5%) patients, with 59 (93.7%) of them having at least a 12-month follow-up after ASM discontinuation. At the last visit, 49 (83%) of those patients had experienced GTCS recurrence. A longer duration of seizure freedom was the only factor predicting a higher chance of successful ASM withdrawal according to multivariable Cox regression.

SIGNIFICANCE

GTCA could be considered a relatively easily manageable IGE syndrome, with a low rate of drug resistance and a high prevalence of early response to treatment. Nevertheless, a considerable proportion of patients experience relapsing patterns of seizure control, highlighting the need for appropriate counseling and lifestyle recommendations.

Association of symptoms of psychiatric disease and electroencephalographic patterns in idiopathic generalized epilepsy

OBJECTIVE

Idiopathic generalized epilepsies (IGE) are genetic epilepsies with alterations of thalamo-frontocortical circuits that play a major role in seizure generation and propagation. Psychiatric diseases and drug resistance are strongly associated, but it remains unknown if they are symptoms of the same pathophysiological process. Hypothesizing that the same network alterations are associated with the frequency of epileptic discharges (ED) and psychiatric symptoms, we here tested the association of self-reported psychiatric symptoms and IGE severity estimated by electroencephalographic (EEG) biomarkers.

METHODS

Idiopathic generalized epilepsies patients were asked to fill out four validated psychiatric screening tools assessing symptoms of personality disorders (Standard Assessment of Personality- Abbreviated Scale), depression (Major Depression Inventory), impulsiveness (Barratt Impulsiveness Scale), and anxiety (brief Epilepsy Anxiety Survey Instrument). Blinded to results and clinical data on the patients, we analyzed the patients' EEGs, assessed, and quantified ED. The number and duration of ED divided by the duration of the EEG served as a proxy for the severity of IGE that was correlated with the results of the psychiatric screening.

RESULTS

Paired data from 64 patients were available for analysis. The duration of EDs per minute EEG was inversely associated with the time since the last seizure. The number of patients with generalized polyspike trains (n = 2), generalized paroxysmal fast activity (n = 3), and prolonged epileptiform discharges (n = 10) were too low for statistically meaningful analyses. Self-reported symptoms of depression, personality disorder, and impulsivity were not associated with EDs. In contrast, the duration of EDs per minute EEG was associated with self-reported symptoms of anxiety in univariate analyses, not significant, however, following adjustment for time since the last seizure in regression models.

SIGNIFICANCE

Self-reported symptoms of psychiatric diseases were not strongly associated with EDs as the best available quantifiable biomarker of IGE severity. As expected, the duration of EDs per minute and anxiety was inversely associated with time since the last seizure. Our data argue against a direct link between the frequency of EDs - as an objective proxy of IGE severity - and psychiatric symptoms.

Prognostic interictal electroencephalographic biomarkers and models to assess antiseizure medication efficacy for clinical practice: A scoping review

Antiseizure medication (ASM) is the primary treatment for epilepsy. In clinical practice, methods to assess ASM efficacy (predict seizure freedom or seizure reduction), during any phase of the drug treatment lifecycle, are limited. This scoping review identifies and appraises prognostic electroencephalographic (EEG) biomarkers and prognostic models that use EEG features, which are associated with seizure outcomes following ASM initiation, dose adjustment, or withdrawal. We also aim to summarize the population and context in which these biomarkers and models were identified and described, to understand how they could be used in clinical practice. Between January 2021 and October 2022, four databases, references, and citations were systematically searched for ASM studies investigating changes to interictal EEG or prognostic models using EEG features and seizure outcomes. Study bias was appraised using modified Quality in Prognosis Studies criteria. Results were synthesized into a qualitative review. Of 875 studies identified, 93 were included. Biomarkers identified were classed as qualitative (visually identified by wave morphology) or quantitative. Qualitative biomarkers include identifying hypsarrhythmia, centrotemporal spikes, interictal epileptiform discharges (IED), classifying the EEG as normal/abnormal/epileptiform, and photoparoxysmal response. Quantitative biomarkers were statistics applied to IED, high-frequency activity, frequency band power, current source density estimates, pairwise statistical interdependence between EEG channels, and measures of complexity. Prognostic models using EEG features were Cox proportional hazards models and machine learning models. There is promise that some quantitative EEG biomarkers could be used to assess ASM efficacy, but further research is required. There is insufficient evidence to conclude any specific biomarker can be used for a particular population or context to prognosticate ASM efficacy. We identified a potential battery of prognostic EEG biomarkers, which could be combined with prognostic models to assess ASM efficacy. However, many confounders need to be addressed for translation into clinical practice.

Neurophysiology of Juvenile and Progressive Myoclonic Epilepsy

SUMMARY

Myoclonus can be epileptic or nonepileptic. Epileptic myoclonus has been defined in clinical, neurophysiological, and neuroanatomical terms. Juvenile myoclonic epilepsy (JME) is typically considered to be an adolescent-onset idiopathic generalized epilepsy with a combination of myoclonic, generalized tonic-clonic, and absence seizures and normal cognitive status that responds well to anti-seizure medications but requires lifelong treatment. EEG shows generalized epileptiform discharges and photosensitivity. Recent observations indicate that the clinical picture of JME is heterogeneous and a number of neuropsychological and imaging studies have shown structural and functional abnormalities in the frontal lobes and thalamus. Advances in neurophysiology and imaging suggest that JME may not be a truly generalized epilepsy, in that restricted cortical and subcortical networks appear to be involved rather than the entire brain. Some patients with JME may be refractory to anti-seizure medications and attempts have been made to identify neurophysiological biomarkers predicting resistance. Progressive myoclonic epilepsy is a syndrome with multiple specific causes. It is distinct from JME because of the occurrence of progressive neurologic dysfunction in addition to myoclonus and generalized tonic-clonic seizures but may sometimes be difficult to distinguish from JME or misdiagnosed as drug-resistant JME. This article provides an overview of progressive myoclonic epilepsy and focuses on the clinical and neurophysiological findings in the two most commonly recognized forms of progressive myoclonic epilepsy-Unverricht-Lundborg disease (EPM1) and Lafora disease (EPM2). A variety of neurophysiological tests can be used to distinguish between JME and progressive myoclonic epilepsy and between EPM1 and EPM2.

Drug resistance in idiopathic generalized epilepsies: Evidence and concepts

Although approximately 10%-15% of patients with idiopathic generalized epilepsy (IGE)/genetic generalized epilepsy remain drug-resistant, there is no consensus or established concept regarding the underlying mechanisms and prevalence. This review summarizes the recent data and the current hypotheses on mechanisms that may contribute to drug-resistant IGE. A literature search was conducted in PubMed and Embase for studies on mechanisms of drug resistance published since 1980. The literature shows neither consensus on the definition nor a widely accepted model to explain drug resistance in IGE or one of its subsyndromes. Large-scale genetic studies have failed to identify distinct genetic causes or affected genes involved in pharmacokinetics. We found clinical and experimental evidence in support of four hypotheses: (1) "network hypothesis"-the degree of drug resistance in IGE reflects the severity of cortical network alterations, (2) "minor focal lesion in a predisposed brain hypothesis"-minor cortical lesions are important for drug resistance, (3) "interneuron hypothesis"-impaired functioning of γ-aminobutyric acidergic interneurons contributes to drug resistance, and (4) "changes in drug kinetics"-genetically impaired kinetics of antiseizure medication (ASM) reduce the effectiveness of available ASMs. In summary, the exact definition and cause of drug resistance in IGE is unknown. However, published evidence suggests four different mechanisms that may warrant further investigation.

EEG Markers of Treatment Resistance in Idiopathic Generalized Epilepsy: From Standard EEG Findings to Advanced Signal Analysis

Idiopathic generalized epilepsy (IGE) represents a common form of epilepsy in both adult and pediatric epilepsy units. Although IGE has been long considered a relatively benign epilepsy syndrome, a remarkable proportion of patients could be refractory to treatment. While some clinical prognostic factors have been largely validated among IGE patients, the impact of routine electroencephalography (EEG) findings in predicting drug resistance is still controversial and a growing number of authors highlighted the potential importance of capturing the sleep state in this setting. In addition, the development of advanced computational techniques to analyze EEG data has opened new opportunities in the identification of reliable and reproducible biomarkers of drug resistance in IGE patients. In this manuscript, we summarize the EEG findings associated with treatment resistance in IGE by reviewing the results of studies considering standard EEGs, 24-h EEG recordings, and resting-state protocols. We discuss the role of 24-h EEG recordings in assessing seizure recurrence in light of the potential prognostic relevance of generalized fast discharges occurring during sleep. In addition, we highlight new and promising biomarkers as identified by advanced EEG analysis, including hypothesis-driven functional connectivity measures of background activity and data-driven quantitative findings revealed by machine learning approaches. Finally, we thoroughly discuss the methodological limitations observed in existing studies and briefly outline future directions to identify reliable and replicable EEG biomarkers in IGE patients.

Using Generalized Polyspike Train to Predict Drug-Resistant Idiopathic Generalized Epilepsy

INTRODUCTION

The authors tested the hypothesis that the EEG feature generalized polyspike train (GPT) is associated with drug-resistant idiopathic generalized epilepsy (IGE).

METHODS

The authors conducted a single-center case-control study of patients with IGE who had outpatient EEGs performed between 2016 and 2020. The authors classified patients as drug-resistant or drug-responsive based on clinical review and in a masked manner reviewed EEG data for the presence and timing of GPT (a burst of generalized rhythmic spikes lasting less than 1 second) and other EEG features. A relationship between GPT and drug resistance was tested before and after controlling for EEG duration. The EEG duration needed to observe GPT was also calculated.

RESULTS

One hundred three patients were included (70% drug-responsive and 30% drug-resistant patients). Generalized polyspike train was more prevalent in drug-resistant IGE (odds ratio, 3.8; 95% confidence interval, 1.3-11.4; P = 0.02). This finding persisted when controlling for EEG duration both with stratification and with survival analysis. A median of 6.5 hours (interquartile range, 0.5-12.7 hours) of EEG recording was required to capture the first occurrence of GPT.

CONCLUSIONS

The findings support the hypothesis that GPT is associated with drug-resistant IGE. Prolonged EEG recording is required to identify this feature. Thus, >24-hour EEG recording early in the evaluation of patients with IGE may facilitate prognostication.

Drug-resistant epilepsy at the age extremes: Disentangling the underlying etiology

The incidence of epilepsy is highest at the extreme age ranges: childhood and elderly age. The most common syndromes in these demographics - self-limited epilepsies of childhood and idiopathic generalized epilepsies in pediatric age, focal epilepsy with structural etiology in older people - are expected to be drug responsive. In this work, we focus on such epilepsy types, overviewing the complex clinical background of unexpected drug-resistance. For self-limited epilepsies of childhood and idiopathic generalized epilepsies, we illustrate drug-resistance resulting from syndrome misinterpretation, reason on possible unexpected courses of epilepsy, and explicate the influence of inappropriate treatments. For elderly-onset epilepsy, we show the challenges in differential diagnosis possibly leading to pseudoresistance and analyze how drug-resistant epilepsy can arise in stroke, neurocognitive disorders, brain tumors, and autoimmune encephalitis. In children and senior people, drug-resistance can be regarded as a hint to review the diagnosis or explore alternative therapeutic strategies. Refractory seizures are not only a therapeutic challenge, but also a cardinal sign not to be overlooked in syndromes commonly deemed to be drug-responsive.

Significance of Polyspikes on Electroencephalography in Children with Focal Epilepsy

Purpose: Epilepsy is one of the most common neurological disorders in both adults and children. After detailed history-taking, electroencephalography (EEG) is the most important investigation in the evaluation of epilepsy patients. Polyspikes, defined as a sequence of two or more spikes, are among the findings that can be seen on EEGs of epilepsy patients, but the literature on their significance in focal epilepsy patients is scarce. Therefore, in the current study, we investigated the significance of polyspikes on EEG in childhood focal epilepsy. Methods: A retrospective analysis was conducted of data from children who were diagnosed with focal epilepsy and received anti-seizure medications at Pusan National University Children’s Hospital. Results: Among the 1,125 children included in this study, 468 (41.6%) showed interictal polyspikes on their EEGs. In the multivariate analysis, only the presence of brain magnetic resonance imaging (MRI) abnormalities was significantly associated with the presence of interictal polyspikes on EEGs. Among patients with brain MRI abnormalities, localized polyspikes were significantly associated with focal cortical dysplasia, while multifocal polyspikes were significantly associated with perinatal insults (hypoxic-ischemic encephalopathy and destructive encephalomalacia). Conclusion: Focal epilepsy patients with interictal polyspikes were more likely to have a structural etiology. Furthermore, patients with localized polyspikes were more likely to have focal cortical dysplasia as the structural etiology, while patients with multifocal polyspikes were more likely to have perinatal insults as the structural etiology. This study demonstrates that focal polyspikes can be used as markers of the possible presence of a structural etiology in routine practice.

Generalized Fast Discharges Along the Genetic Generalized Epilepsy Spectrum: Clinical and Prognostic Significance

Objective

To investigate the electroclinical characteristics and the prognostic impact of generalized fast discharges in a large cohort of genetic generalized epilepsy (GGE) patients studied with 24-h prolonged ambulatory electroencephalography (paEEG).

Methods

This retrospective multicenter cohort study included 202 GGE patients. The occurrence of generalized paroxysmal fast activity (GPFA) and generalized polyspike train (GPT) was reviewed. GGE patients were classified as having idiopathic generalized epilepsy (IGE) or another GGE syndrome (namely perioral myoclonia with absences, eyelid myoclonia with absences, epilepsy with myoclonic absences, generalized epilepsy with febrile seizures plus, or GGE without a specific epilepsy syndrome) according to recent classification proposals.

Results

GPFA/GPT was found in overall 25 (12.4%) patients, though it was significantly less frequent in IGE compared with other GGE syndromes (9.3 vs. 25%, p = 0.007). GPFA/GPT was found independently of seizure type experienced during history, the presence of mild intellectual disability/borderline intellectual functioning, or EEG features. At multivariable analysis, GPFA/GPT was significantly associated with drug resistance (p = 0.04) and with a higher number of antiseizure medications (ASMs) at the time of paEEG (p < 0.001) and at the last medical observation (p < 0.001). Similarly, GPFA/GPT, frequent/abundant generalized spike-wave discharges during sleep, and a higher number of seizure types during history were the only factors independently associated with a lower chance of achieving 2-year seizure remission at the last medical observation. Additionally, a greater number of GPFA/GPT discharges significantly discriminated between patients who achieved 2-year seizure remission at the last medical observation and those who did not (area under the curve = 0.77, 95% confidence interval 0.57-0.97, p = 0.02).

Conclusion

We found that generalized fast discharges were more common than expected in GGE patients when considering the entire GGE spectrum. In addition, our study highlighted that GPFA/GPT could be found along the entire GGE continuum, though their occurrence was more common in less benign GGE syndromes. Finally, we confirmed that GPFA/GPT was associated with difficult-to-treat GGE, as evidenced by the multivariable analysis and the higher ASM load during history.

Clinical and EEG factors associated with antiseizure medication resistance in idiopathic generalized epilepsy

OBJECTIVE

We sought to determine which combination of clinical and electroencephalography (EEG) characteristics differentiate between an antiseizure medication (ASM)-resistant vs ASM-responsive outcome for patients with idiopathic generalized epilepsy (IGE).

METHODS

This was a case-control study of ASM-resistant cases and ASM-responsive controls with IGE treated at five epilepsy centers in the United States and Australia between 2002 and 2018. We recorded clinical characteristics and findings from the first available EEG study for each patient. We then compared characteristics of cases vs controls using multivariable logistic regression to develop a predictive model of ASM-resistant IGE.

RESULTS

We identified 118 ASM-resistant cases and 114 ASM-responsive controls with IGE. First, we confirmed our recent finding that catamenial epilepsy is associated with ASM-resistant IGE (odds ratio [OR] 3.53, 95% confidence interval [CI] 1.32-10.41, for all study subjects) after covariate adjustment. Other independent factors seen with ASM resistance include certain seizure-type combinations (absence, myoclonic, and generalized tonic-clonic seizures [OR 7.06, 95% CI 2.55-20.96]; absence and generalized tonic-clonic seizures [OR 4.45, 95% CI 1.84-11.34]), as well as EEG markers of increased generalized spike-wave discharges (GSWs) in sleep (OR 3.43, 95% CI 1.12-11.36 for frequent and OR 7.21, 95% CI 1.50-54.07 for abundant discharges in sleep) and the presence of generalized polyspike trains (GPTs; OR 5.49, 95% CI 1.27-38.69). The discriminative ability of our final multivariable model, as measured by area under the receiver-operating characteristic curve, was 0.80.

SIGNIFICANCE

Multiple clinical and EEG characteristics independently predict ASM resistance in IGE. To improve understanding of a patient's prognosis, clinicians could consider asking about specific seizure-type combinations and track whether they experience catamenial epilepsy. Obtaining prolonged EEG studies to record the burden of GSWs in sleep and assessing for the presence of GPTs may provide additional predictive value.

Under-sampling in epilepsy: Limitations of conventional EEG

The cyclical structure of epilepsy was recently (re)-discovered through years-long intracranial electroencephalography (EEG) obtained with implanted devices. In this review, we discuss how new revelations from chronic EEG relate to the practice and interpretation of conventional EEG. We argue for an electrographic definition of seizures and highlight the caveats of counting epileptiform discharges in EEG recordings of short duration. Limitations of conventional EEG have practical implications with regard to titrating anti-seizure medications and allowing patients to drive, and we propose that chronic monitoring of brain activity could greatly improve epilepsy care. An impending paradigm shift in epilepsy will involve using next-generation devices for chronic EEG to leverage known biomarkers of disease state.

Patterns and prognostic markers for treatment response in generalized epilepsies

Objective

To determine the pattern of treatment response in patients with idiopathic generalized epilepsy (IGE) and whether routinely assessed clinical and neurophysiological parameters allow predicting response to lamotrigine, levetiracetam, or valproic acid.

Methods

In 328 adult patients with IGE, demographic data, imaging, EEG data, current and prior antiepileptic treatment, treatment outcome, and side effects were analyzed from the patients' medical files and patient interviews.

Results

Seizure freedom with acceptable side effects at the first attempt was achieved in 61 (18.6%) patients. One hundred four (31.7%) patients tried ≥3 antiepileptic drugs before achieving seizure control at the last follow-up. Lamotrigine, levetiracetam, and valproic acid showed differential response rates (39.8% vs 47.5% vs 71.1%) that were most pronounced in patients with juvenile myoclonic epilepsy. The risk of having side effects was higher with valproic acid (23.7%) than with lamotrigine (10.4%) or levetiracetam (20.4%) treatment, contributing to the low retention rate of valproic acid (53.7%). Treatment resistance was associated with established risk factors. Multivariate analyses aiming at identifying clinical indicators for response to specific drugs did not reveal putative biomarkers when corrected for drug resistance.

Conclusion

Despite a high rate of seizure control, the chance of achieving seizure control and acceptable side effects at first attempt was low due to an inverse association of effectiveness and side effects of the 3 most commonly used drugs. Routinely assessed clinical parameters were not indicative for response to specific drugs.

Classification of evidence

This study provides Class II evidence that for patients with IGE, various clinical factors do not predict a response to specific antiepileptic drugs.