Faculty Bibliography

Rationale: WEPOD is a multicenter prospective observational study evaluating fertility among women with epilepsy (WWE) compared to healthy controls. WEPOD utilizes a customized mobile electronic patient diary on a commercially available mobile device (Apple's iPod Touch) . A customized diary application made by Irody tracks fertility information, and in WWE, seizures and daily medication use. The app delivers all patient captured information to a cloud database where it is analyzed. We determined the degree of data tracking adherence associated with dropping out of the study. Methods: WWE planning pregnancy enrolled within 6 months of stopping birth control. Subjects were trained to use a customized application (the WEPOD App) for daily data tracking. All subjects were asked to track data daily until delivery or up to 12 months if they did not become pregnant. Data were analyzed by percent of days in the study for which data was tracked. The cut point of percent tracking with the maximum sensitivity and specificity associating with dropping out of the study was determined. Further, the timing of dropping out of the study was evaluated. Results: Of 61 WWE who enrolled before 12/1/12 and tracked data, 9 subjects dropped out and 52 continued in the study. The overall adherence was 92.3%; 36/61 had 100% adherence. Mean percent adherence of the 52 completed subjects was 96.1% (median 100, range 33-100). Of the 9 subjects who dropped out, percent adherence was 6, 22, 55, 77, 86, 87, 90, 100 and 100 for a mean of 69.9 (median 86). Only 4 subjects were less than 90% tracking adherent and completed the study. The optimal percent adherence cut point for associating with dropping out of the study was 96.5% which had a sensitivity of 87% and a specificity of 83% (point A). Given that the cut point of 96.5 % adherence is higher than the overall mean adherence, and that specificity may be less important than sensitivity since other factors accounting for late drop outs are not accounted for, a more reasonabl!

Rationale: Seizure misclassification in randomized clinical studies of antiepileptic drugs (AEDs) can negatively impact trial outcomes. To ensure homogeneity and accuracy of seizure classification in clinical trials, The Epilepsy Study Consortium has created a seizure training program for study investigators and site coordinators to enhance the understanding of seizure types and provide independent verification of seizure classification. This prospective training has previously been used in AED clinical trials, including PREVAIL, a recently completed global, phase 3 study evaluating the efficacy and safety of USL255, once-daily extended-release topiramate, as adjunctive therapy in subjects with partial-onset seizures (NCT01142193). Methods: The PREVAIL training program included a seizure identification video providing in-depth descriptions of seizure types and advice for patient interviews. The video was moderated by a Consortium member at the investigator meetings and posted online for those unable to attend. After the video, a quiz was administered and the answers discussed in real time. PREVAIL was the first trial to implement this quiz with the requirement for retraining if a passing score (>70%) was not achieved. Additionally, each site was required to submit a Seizure Identification Form (SIF) for all subjects, which included descriptions of seizures by the subject and/or caregiver, and the investigator's classification(s) of seizure(s). The SIF was reviewed independently by the Consortium immediately after the Screening Visit and was to be approved prior to randomization. To ensure seizures were captured correctly in the case report forms (CRFs) on subsequent study visits, misclassifications were communicated to the study team to allow for subject retraining (as necessary). CRFs were checked by the sponsor/CRO to confirm that classifications matched those approved by the Consortium. Additionally, subject diaries were assessed by centralized CRO reviewers to ensure qualifying seizure type!

Despite the expanding treatment options in the past two decades, a third of patients with epilepsy remain treatment resistant, and there is a continued need for new therapies. After many years of repeated success, several late-stage clinical development programs for antiseizure drugs have seen unexpected failures to demonstrate superiority of the experimental drug over placebo, which has led to a re-examination of how clinical trials are conducted in this heterogeneous and often unpredictable condition. There are numerous sources of variability in epilepsy trials that can reduce effect size. Methods to improve diagnostic accuracy and outcome assessment are needed to ensure that promising compounds have the best chance to get to patients. 2013 Future Science Ltd

Advances in MRI have transformed the in vivo detection of brain abnormalities in neurological disease. However, many subtle structural abnormalities remain undetected, especially in individual patients, where clinical relevance is highest. We present a quantitative, multifeature morphometry approach combined with machine learning algorithms for detecting structural cortical abnormalities in epilepsy patients with focal cortical dysplasia (FCD). FCD is a malformation of cortical development and is the most common etiology in pediatric epilepsy and the second most common etiology in adults with treatment resistant epilepsy. Lesions may occur anywhere in cortex. Seizure freedom after surgery is reported at 66% with a detected lesion, but only 29% in MRI-negative patients. Yet, 70% to 80% of histologically confirmed FCD cases go undetected by visual inspection of the MRI. Sixty-one controls and 23 MRI-negative patients in whom no focal lesion was detected during routine visual radiological analysis and 7 MRI-positive patients were scanned before surgery at 3 T using a T1-weighted MRI sequence. All patients subsequently underwent intracranial EEG monitoring and resection of the epileptic focus and pathology confirmed FCD. Morphometric routines with surface-based spherical averaging techniques were used to align anatomical structures between individual brains and to calculate 6 features at each vertex, including cortical thickness, gray-white contrast, local gyrification, sulcal depth, Jacobian distance, and curvature. A logistic regression classifier was trained on normal control data and the data from the FCD region of MRI-positive patients to classify, in MRI-negative patients, vertices into lesional and nonlesional. The logistic regression approach correctly classified lesions within the resection zone in 14 out of the 24 (58%) MRInegative patients. The overall false positive rate (by vertex) was never greater than 1.05%. Quantitative MRI can aid in the presurgical detection of FCD lesions, even !

Epileptic encephalopathies are a devastating group of severe childhood epilepsy disorders for which the cause is often unknown. Here we report a screen for de novo mutations in patients with two classical epileptic encephalopathies: infantile spasms (n = 149) and Lennox-Gastaut syndrome (n = 115). We sequenced the exomes of 264 probands, and their parents, and confirmed 329 de novo mutations. A likelihood analysis showed a significant excess of de novo mutations in the ∼4,000 genes that are the most intolerant to functional genetic variation in the human population (P = 2.9 × 10(-3)). Among these are GABRB3, with de novo mutations in four patients, and ALG13, with the same de novo mutation in two patients; both genes show clear statistical evidence of association with epileptic encephalopathy. Given the relevant site-specific mutation rates, the probabilities of these outcomes occurring by chance are P = 4.1 × 10(-10) and P = 7.8 × 10(-12), respectively. Other genes with de novo mutations in this cohort include CACNA1A, CHD2, FLNA, GABRA1, GRIN1, GRIN2B, HNRNPU, IQSEC2, MTOR and NEDD4L. Finally, we show that the de novo mutations observed are enriched in specific gene sets including genes regulated by the fragile X protein (P < 10(-8)), as has been reported previously for autism spectrum disorders.

The ideal proof-of-principle study design provides a strong efficacy signal over the shortest duration, while exposing the fewest patients possible. Data from a large database (Pfizer Inc) which studied add-on pregabalin for the treatment of partial seizures was used to model how duration of baseline, post-randomization treatment period, and number of subjects impact the likelihood of an interpretable efficacy signal. Data from four double-blind, randomized, placebo-controlled, phase III studies that had at least one 600mg/day treatment arm were combined. The common 6-week baseline period was divided into weekly intervals, as was the 12-week post-randomization period. Two methods of analysis were used: logistic regression performed on 50% responder rate and the Hodges-Lehmann estimate on percentage reduction from baseline seizure rate. A simulation-based re-sampling approach was used to determine sufficient sample size. Four weeks of baseline with 3 weeks of treatment were determined to be clinically and statistically sufficient. A reasonable sample size was estimated to be 40-50 patients per group, if a highly efficacious drug was used. These modeling results indicate that the efficacy of an antiepileptic drug can be demonstrated in a relatively short period of time with a reasonable sample size.

BACKGROUND: Epilepsy is a common neurological disorder that affects approximately 50 million people worldwide. Both risk of epilepsy and response to treatment partly depend on genetic factors, and gene identification is a promising approach to target new prediction, treatment, and prevention strategies. However, despite significant progress in the identification of genes causing epilepsy in families with a Mendelian inheritance pattern, there is relatively little known about the genetic factors responsible for common forms of epilepsy and so-called epileptic encephalopathies. Study design The Epilepsy Phenome/Genome Project (EPGP) is a multi-institutional, retrospective phenotype-genotype study designed to gather and analyze detailed phenotypic information and DNA samples on 5250 participants, including probands with specific forms of epilepsy and, in a subset, parents of probands who do not have epilepsy. RESULTS: EPGP is being executed in four phases: study initiation, pilot, study expansion/establishment, and close-out. This article discusses a number of key challenges and solutions encountered during the first three phases of the project, including those related to (1) study initiation and management, (2) recruitment and phenotyping, and (3) data validation. The study has now enrolled 4223 participants. CONCLUSIONS: EPGP has demonstrated the value of organizing a large network into cores with specific roles, managed by a strong Administrative Core that utilizes frequent communication and a collaborative model with tools such as study timelines and performance-payment models. The study also highlights the critical importance of an effective informatics system, highly structured recruitment methods, and expert data review.

OBJECTIVE: Preapproval randomized controlled trials of antiepileptic drugs provide data in limited patient groups. We assessed the side effect and seizure reduction profile of tiagabine (TGB) in typical clinical practice. METHODS: Investigators recorded adverse effect (AE), seizure, and assessment-of-benefit data prospectively in sequential patients treated open label with TGB. RESULTS: Two hundred ninety-two patients (39 children) were enrolled to be treated long term with TGB. Seizure types were focal-onset (86%), generalized-onset (12%), both focal- and generalized-onset (0.3%), and multiple associated with Lennox-Gastaut Syndrome (2%). Two hundred thirty-one received at least one dose of TGB (median=28mg/day) and had follow-up seizure or AE data reported. Common AEs were fatigue, dizziness, psychomotor slowing, ataxia, gastrointestinal upset, weight change, insomnia, and "others" (mostly behavioral). Serious AEs occurred in 19 patients: behavioral effects (n=12), status epilepticus (n=3), others (n=3), and sudden unexplained death (n=1). No patients experienced suicidal ideation/behavior, rash, nephrolithiasis, or organ failure. Seizure outcomes were seizure freedom (5%), >/=75% reduction (12%), >/=50% reduction (23%), and increased number of seizures (17%), or new seizure type (1%). CONCLUSIONS: Behavioral AEs occurred in a larger proportion of patients compared to those reported in TGB preapproval randomized controlled trials. A moderate percentage of patients had a meaningful reduction in seizure frequency. In clinical practice, TGB remains a useful antiepileptic drug.