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Recent studies have provided much needed data on the probability of seizure remission among adults with chronic intractable epilepsy treated medically. Here we provide an extended follow-up to our earlier study in order to provide a more comprehensive picture of long-term prognosis in this patient population during medical treatment. The prevalence cohort was followed for two outcomes-complete seizure remission for ≥ 12 months and subsequent seizure relapse among those attaining a seizure remission. The study outcomes were estimated using Kaplan-Meier analysis. We found that the probability of attaining a ≥ 12 months of complete seizure freedom to be approximately 3-4% per year through 8 years of follow-up. By year 5 since the start of seizure remission, the cumulative probability of seizure relapse was 81%, although only half of the patients with seizure relapse went on to experience their previous seizure frequency., (Copyright © 2010 Elsevier B.V. All rights reserved.)

Patients with epilepsy are frequently confronted with complex treatment decisions. Communicating treatment risks is often difficult because patients may have difficulty with basic statistical concepts (i.e., low numeracy) or might misconceive the statistical information based on the way information is presented, a phenomenon known as "framing bias." We assessed numeracy and framing bias in 95 adults with chronic epilepsy and explored cognitive correlates of framing bias. Compared with normal controls, patients with epilepsy had significantly poorer performance on the Numeracy scale (P=0.02), despite a higher level of education than normal controls (P<0.001). Compared with patients with higher numeracy, patients with lower numeracy were significantly more likely to exhibit framing bias. Abstract problem solving performance correlated with the degree of framing bias (r=0.631, P<0.0001), suggesting a relationship between aspects of executive functioning and framing bias. Poor numeracy and susceptibility framing bias place patients with epilepsy at risk for uninformed decisions., (Copyright © 2010 Elsevier Inc. All rights reserved.)

Purpose: Depression is the most common comorbid condition in epilepsy. The cause of this comorbidity is unknown, and could involve psychosocial consequences of epilepsy, treatment side effects, seizure manifestations, or common neurobiologic mechanisms. One hypothesis of particular interest is a shared genetic susceptibility to epilepsy and depression. We tested this hypothesis by studying depressive symptoms in families with an identified genetic form of epilepsy: autosomal dominant partial epilepsy with auditory features caused by mutations in the leucine-rich, glioma inactivated 1 gene (LGI1)., Methods: A standardized depression screen was administered to 94 individuals from 11 families with mutations in LGI1, including 38 mutation carriers with epilepsy (AC), 11 clinically unaffected mutation carriers (UC), and 45 noncarriers (NC)., Results: Current depressive symptom scores were significantly higher in AC than in NC, an association that remained after excluding depressive symptoms that appeared likely to be caused by antiepileptic medication use. However, scores did not differ between UC and NC., Discussion: Although LGI1 mutation carriers who were clinically affected with epilepsy had increased depressive symptoms, mutation carriers without epilepsy did not. These findings suggest that the increase in depressive symptoms in affected individuals from these families is related to epilepsy or its treatment rather than to LGI1 mutations per se.

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. [ABSTRACT FROM AUTHOR]

Summary: Objective: Mood disorders are the most common comorbid conditions in epilepsy, but the cause remains unclear. One possible explanation is a shared genetic susceptibility to epilepsy and mood disorders. We tested this hypothesis by evaluating lifetime prevalence of mood disorders in relatives with and without epilepsy in families containing multiple individuals with epilepsy, and comparing the findings with rates from a general population sample. Methods: The Composite International Diagnostic Interview was administered to 192 individuals from 60 families, including 110 participants with epilepsy of unknown cause (50 focal epilepsy [FE], 42 generalized epilepsy [GE], 6 FE and GE, 12 unclassifiable) and 82 relatives without epilepsy (RWOE). Odds ratios (ORs) for lifetime prevalence of mood disorders in participants with versus without epilepsy were computed through logistic regression, using generalized estimation equations to account for familial clustering. Standardized prevalence ratios (SPRs) were used to compare prevalence in family members with general population rates. Results: Compared with RWOE, ORs for mood disorders were significantly increased in participants with FE (OR = 2.4, 95% confidence interval [CI] = 1.1‐5.2) but not in those with GE (OR = 1.0, 95% CI = 0.4‐2.2). In addition, prevalence of mood disorders was increased in individuals with epilepsy who had ≥1 relative with FE. Compared with general population rates, mood disorders were significantly increased in individuals with FE but not in those with GE. Rates were also increased in RWOE, but not significantly so (SPR = 1.4, P = .14). Significance: These findings are consistent with the hypothesis of shared genetic susceptibility to epilepsy and mood disorders, but suggest (1) the effect may be restricted to FE, and (2) the shared genetic effect on risk of mood disorders and epilepsy may be restricted to individuals with epilepsy, that is, to those in whom the genetic risk for epilepsy is “penetrant.” [ABSTRACT FROM AUTHOR]