Reducing Placebo Exposure In Trials

The randomized controlled trial is the unequivocal gold standard for demonstrating clinical efficacy and safety of investigational therapies. Recently there have been concerns raised about prolonged exposure to placebo and ineffective therapy during the course of an add-on regulatory trial for new antiepileptic drug approval (typically ∼6 months in duration), due to the potential risks of continued uncontrolled epilepsy for that period. The first meeting of the Research Roundtable in Epilepsy on May 19-20, 2016, focused on Reducing placebo exposure in epilepsy clinical trials, with a goal of considering new designs for epilepsy regulatory trials that may be added to the overall development plan to make it, as a whole, safer for participants while still providing rigorous evidence of effect. This topic was motivated in part by data from a meta-analysis showing a 3-to 5-fold increased rate of sudden unexpected death in epilepsy in participants randomized to placebo or ineffective doses of new antiepileptic drugs. The meeting agenda included rationale and discussion of different trial designs, including active-control add-on trials, placebo add-on to background therapy with adjustment, time to event designs, adaptive designs, platform trials with pooled placebo control, a pharmacokinetic/pharmacodynamic approach to reducing placebo exposure, and shorter trials when drug tolerance has been ruled out. The merits and limitations of each design were discussed and are reviewed here

Seizure diaries for clinical research and practice: Limitations and future prospects

© 2012 Purpose: An NINDS-sponsored conference in April of 2011 reviewed issues in epilepsy clinical trials. One goal was to clarify new electronic methods for recording seizure information and other data in clinical trials. Methods: This selective literature review and compilation of expert opinion considers advantages and limitations of traditional paper-based seizure diaries in comparison to electronic diaries. Key findings: Seizure diaries are a type of patient-reported outcome. All seizure diaries depend first on accurate recognition and recording of seizures, which is a problem since about half of seizures recorded during video-EEG monitoring are not known to the patient. Reliability of recording is another key issue. Diaries may not be at hand after a seizure, lost or not brought to clinic visits. On-line electronic diaries have several potential advantages over paper diaries. Smartphones are increasingly accessible as data entry gateways. Data are not easily lost and are accessible from clinic. Entries can be time-stamped and provide immediate feedback, validation or reminders. Data can also be graphed and pasted into an EMR. Disadvantages include need for digital sophistication, higher cost, increased setup time, and requiring attention to potential privacy issues. The Epilepsy Diary by epilepsy.com and Irody, Inc. has over 13,000 registrants and SeizureTracker over 10,000, and both are used for clinical and research purposes. Some studies have documented patient preference and increased compliance for electronic versus paper diaries. Seizure diaries can be challenging in the pediatric population. Children often have multiple seizure types and limited reporting of subjective symptoms. Multiple caregivers during the day require more training to produce reliable and consistent data. Diary-based observational studies have the advantages of low cost, allowing locus-of-control by the patient and testing in a “real-world” environment. Diary-based studies can also be useful as descriptive “snapshots” of a population. However, the type of information available is very different from that obtained by prospective controlled studies. The act of self-recording observations may itself influence the observation, for example, by causing the subject to attend more vigilantly to seizures after changing medication. Pivotal anti-seizure drug or device trials still mostly rely on paper-based seizure diaries. Industry is aware of the potential advantages of electronic diaries, particularly, the promise of real-time transmission of data, time-stamping of entries, reminders to subjects, and potentially automatic interfaces to other devices. However, until diaries are validated as research tools and the regulatory environment becomes clearer, adoption of new types of diaries as markers for a primary study outcome will be cautious. Significance: Recommendations from the conference included: further studies of validity of epilepsy diaries and how they can be used to improve adherence; use and further development of core data sets, such as the one recently developed by NINDS; encouraging links of diaries to electronic sensors; development of diary privacy and legal policies; examination of special pediatric diary issues; development of principles for observational research from diaries; and work with the FDA to make electronic diaries more useful in industry-sponsored clinical trials

Establishing a learning healthcare system to improve health outcomes for people with epilepsy

© 2021 Elsevier Inc. Objective: To describe the organization of the Epilepsy Learning Healthcare System (ELHS), a network that aims to improve care outcomes for people with epilepsy (PWE). Materials and Methods: Patients and family partners, providers, researchers, epidemiologists, and other leaders collaborated to recruit epilepsy centers and community services organizations into a novel learning network. A multidisciplinary Coordinating Committee developed ELHS governance and organizational structure, including four key planning Cores (Community, Clinical, Quality Improvement, and Data). Through Quality Improvement (QI) methodology grounded in the Institute for Healthcare Improvement (IHI) model, including iterative Plan-Do-Study-Act (PDSA) rapid learning cycles and other learning and sharing sessions, ELHS equipped epilepsy centers and community organizations with tools to standardize, measure, share, and improve key aspects of epilepsy care. The initial learning cycles addressed provider documentation of seizure frequency and type, and also screening for medication adherence barriers. Rapid learning cycles have been carried out on these initial measures in both clinical centers and community-based settings. Additional key measures have been defined for quality of life, screening, and treatment for mental health and behavioral comorbidities, transition from pediatric to adult care, counseling for women and girls living with epilepsy, referral for specialty care, and prevention and treatment of seizure clusters and status epilepticus. Results: It is feasible to adopt a learning healthcare system framework in epilepsy centers and community services organizations. Through structured collaboration between epilepsy care providers, community support organizations, PWE, and their families/caregivers we have identified new opportunities to improve outcomes that are not available in traditional care models

Implementing standardized provider documentation in a tertiary epilepsy clinic

© American Academy of Neurology. Objective To incorporate standardized documentation into an epilepsy clinic and to use these standardized data to compare patients\u27 perception of epilepsy diagnosis to provider documentation.MethodsUsing quality improvement methodology, we implemented interventions to increase documentation of epilepsy diagnosis, seizure frequency, and type from 49.8% to 70% of adult nonemployee patients seen by 6 providers over 5 months of routine clinical care. The main intervention consisted of an interactive SmartPhrase that mirrored a documentation template developed by the Epilepsy Learning Healthcare System. We assessed the weekly proportion of complete SmartPhrases among eligible patient encounters with a statistical process control chart. We used a subset of patients with established epilepsy care linked to existing patient-reported survey data to examine the proportion of patient-to-provider agreement on epilepsy diagnosis (yes vs no/unsure). We also examined sociodemographic and clinical characteristics of patients who disagreed vs agreed with provider\u27s documentation of epilepsy diagnosis.ResultsThe median SmartPhrase weekly completion rate was 78%. Established patients disagreed with providers with respect to epilepsy diagnosis in 18.5% of encounters ( = 0.13), indicating that they did not have or were unsure if they had epilepsy despite having a provider-documented epilepsy diagnosis. Patients who disagreed with providers were similar to those who agreed with respect to age, sex, ethnicity, marital status, seizure frequency, type, and other quality-of-life measures.ConclusionThis project supports the feasibility of implementing standardized documentation of data relevant to epilepsy care in a tertiary epilepsy clinic and highlights an opportunity for improvement in patient-provider communication

Accuracy of ICD-10-CM claims-based definitions for epilepsy and seizure type

© 2020 Elsevier B.V. Objective: To evaluate the accuracy of ICD-10-CM claims-based definitions for epilepsy and classifying seizure types in the outpatient setting. Methods: We reviewed electronic health records (EHR) for a cohort of adults aged 18+ years seen by six neurologists who had an outpatient visit at a level 4 epilepsy center between 01/2019−09/2019. The neurologists used a standardized documentation template to capture the diagnosis of epilepsy (yes/no/unsure), seizure type (focal/generalized/unknown), and seizure frequency in the EHR. Using linked ICD-10-CM codes assigned by the provider, we assessed the accuracy of claims-based definitions for epilepsy, focal seizure type, and generalized seizure type against the reference-standard EHR documentation by estimating sensitivity (Sn), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV). Results: There were 673 eligible outpatient encounters. After review of EHRs for standardized documentation, an analytic sample consisted of 520 encounters representing 402 unique patients. In the EHR documentation, 93.5 % (n = 486/520) of encounters were with patients with a diagnosis of epilepsy. Of those, 66.0 % (n = 321/486) had ≥1 focal seizure, 41.6 % (n = 202/486) had ≥1 generalized seizure, and 7% (n = 34/486) had ≥1 unknown seizure. An ICD-10-CM definition for epilepsy (i.e., ICD-10 G40.X) achieved Sn = 84.4 % (95 % CI 80.8−87.5%), Sp = 79.4 % (95 % CI 62.1−91.3%), PPV = 98.3 % (95 % CI 96.6−99.3%), and NPV = 26.2 % (95 % CI 18.0−35.8%). The classification of focal vs generalized/unknown seizures achieved Sn = 69.8 % (95 % CI 64.4−74.8%), Sp = 79.4 % (95 % CI 72.4−85.3%), PPV = 86.8 % (95 % CI 82.1−90.7%), and NPV = 57.5 % (95 % CI 50.8−64.0%). Conclusions: Claims-based definitions using groups of ICD-10-CM codes assigned by neurologists in routine outpatient clinic visits at a level 4 epilepsy center performed well in discriminating between patients with and without a diagnosis of epilepsy and between seizure types

Epilepsy biomarkers.

A biomarker is defined as an objectively measured characteristic of a normal or pathologic biologic process. Identification and proper validation of biomarkers of epileptogenesis (the development of epilepsy) and ictogenesis (the propensity to generate spontaneous seizures) might predict the development of an epilepsy condition; identify the presence and severity of tissue capable of generating spontaneous seizures; measure progression after the condition is established; and determine pharmacoresistance. Such biomarkers could be used to create animal models for more cost-effective screening of potential antiepileptogenic and antiseizure drugs and devices, and to reduce the cost of clinical trials by enriching the trial population, and acting as surrogate markers to shorten trial duration. The objectives of the biomarker subgroup for the London Workshop were to define approaches for identifying possible biomarkers for these purposes. Research to identify reliable biomarkers may also reveal underlying mechanisms that could serve as therapeutic targets for the development of new antiepileptogenic and antiseizure compounds

Epilepsy biomarkers

A biomarker is defined as an objectively measured characteristic of a normal or pathological biological process. Identification and proper validation of biomarkers of epileptogenesis, the development of epilepsy, and ictogenesis, the propensity to generate spontaneous seizures, might predict the development of an epilepsy condition; identify the presence and severity of tissue capable of generating spontaneous seizures; measure progression after the condition is established; and determine pharmacoresistance. Such biomarkers could be used to create animal models for more cost-effective screening of potential antiepileptogenic and antiseizure drugs and devices, and to reduce the cost of clinical trials by enriching the trial population, and acting as surrogate markers to shorten trial duration. The objectives of the biomarker subgroup for the London Workshop were to define approaches for identifying possible biomarkers for these purposes. Research to identify reliable biomarkers may also reveal underlying mechanisms that could serve as therapeutic targets for the development of new antiepileptogenic and antiseizure compounds

Identification of clinically relevant biomarkers of epileptogenesis — a strategic roadmap

Onset of many forms of epilepsy occurs after an initial epileptogenic insult or as a result of an identified genetic defect. Given that the precipitating insult is known, these epilepsies are, in principle, amenable to secondary prevention. However, development of preventive treatments is difficult because only a subset of individuals will develop epilepsy and we cannot currently predict which individuals are at the highest risk. Biomarkers that enable identification of these individuals would facilitate clinical trials of potential anti- epileptogenic treatments, but no such prognostic biomarkers currently exist. Several putative molecular, imaging, electroencephalographic and behavioural biomarkers of epileptogenesis have been identified, but clinical translation has been hampered by fragmented and poorly coordinated efforts, issues with inter- model reproducibility, study design and statistical approaches, and difficulties with validation in patients. These challenges demand a strategic roadmap to facilitate the identification, characterization and clinical validation of biomarkers for epileptogenesis. In this Review, we summarize the state of the art with respect to biomarker research in epileptogenesis and propose a five- phase roadmap, adapted from those developed for cancer and Alzheimer disease, that provides a conceptual structure for biomarker research