Response to placebo in clinical epilepsy trials--Old ideas and new insights

A narrative review of the placebo effect: historical roots, current applications, and emerging insights

PURPOSE

Placebo is a term to define physiologically inactive compounds used in treatment that causes physical and emotional changes. The placebo effect, driven by expectation and conditioning, plays a significant role in various conditions like pain, depression, and Parkinson's disease, while the nocebo effect can hinder treatment outcomes. Understanding mechanisms such as neuromodulation and genetics has gained importance in modern medicine. This review aims to explore the clinical relevance of placebo responses, particularly in neuropsychiatric disorders, and their potential in personalized medicine. By integrating placebo research into healthcare, it highlights opportunities to enhance treatment efficacy, improve patient well-being, and reduce reliance on pharmacological interventions.

METHODS

A comprehensive literature search was conducted in PubMed, Scopus, and Google Scholar databases. Recent studies were reviewed to evaluate placebo effects, and the variability of the placebo response in neuropsychiatric disorders was summarized.

RESULTS

Placebo effects significantly impact treatment outcomes across various conditions, including Parkinson's disease, depression, pain syndromes, and epilepsy. The mechanisms involve neurobiological and psychological factors, with evidence suggesting that placebo interventions can modulate neurotransmitter activity and improve patient well-being.

CONCLUSION

Integrating placebo research into clinical practice may enhance treatment outcomes, reduce drug dependency, and support personalized medicine by tailoring interventions to individual placebo responsiveness. Understanding placebo and nocebo mechanisms can optimize therapeutic strategies while minimizing unnecessary pharmacological treatments.

Inductive reasoning with large language models: A simulated randomized controlled trial for epilepsy

INTRODUCTION

To investigate the potential of using artificial intelligence (AI), specifically large language models (LLMs), for synthesizing information in a simulated randomized clinical trial (RCT) for an anti-seizure medication, cenobamate, demonstrating the feasibility of inductive reasoning via medical chart review.

METHODS

An LLM-generated simulated RCT was conducted, featuring a placebo arm and a full-strength drug arm with a cohort of 240 patients divided 1:1. Seizure counts were simulated using a realistic seizure diary simulator. The study utilized LLMs to generate clinical notes with four neurologist writing styles and random extraneous details. A secondary LLM pipeline synthesized data from these notes. The efficacy and safety of cenobamate in seizure control were evaluated by both an LLM-based pipeline and a human reader.

RESULTS

The AI analysis closely mirrored human analysis, demonstrating the drug's efficacy with marginal differences (<3 %) in identifying both drug efficacy and reported symptoms. The AI successfully identified the number of seizures, symptom reports, and treatment efficacy, with statistical analysis comparing the 50 %-responder rate and median percentage change between the placebo and drug arms, as well as side effect rates in each arm.

DISCUSSION

This study highlights the potential of AI to accurately analyze noisy clinical notes to inductively produce clinical knowledge. Here, treatment effect sizes and symptom frequencies derived from unstructured simulated notes were inferred despite many distractors. The findings emphasize the relevance of AI in future clinical research, offering a scalable and efficient alternative to traditional labor-intensive data mining.

Factors associated with placebo response rate in randomized controlled trials of antiseizure medications for focal epilepsy

OBJECTIVE

Randomized controlled trials (RCTs) are necessary to evaluate the efficacy of novel treatments for epilepsy. However, there have been concerning increases in the placebo responder rate over time. To understand these trends, we evaluated features associated with increased placebo responder rate.

METHODS

Using individual-level data from 20 focal-onset seizure trials provided by seven pharmaceutical companies, we evaluated associations with change in seizure frequency in participants randomized to placebo. We used multivariable logistic regression to evaluate participant and study factors associated with differing rates of 50% reduction in seizure frequency during blinded placebo treatment, as compared to pre-randomization baseline seizure frequency. In addition, we focused on the association of placebo responder rate with pre-randomization baseline seizure frequency and country of recruitment.

RESULTS

In the pooled analysis of 1674 participants randomized to placebo, a higher 50% responder rate (50RR) was associated with a shorter duration of epilepsy (p = .006), lower baseline seizure rate (p = .002), fewer concomitant antiseizure medications (p = .004), absence of adverse events (p < .001), more trial arms (p = .006), and geographic region (p < .001). Mixture modeling indicated a significantly higher 50RR in Bulgaria, Croatia, India, and Canada (42% in the higher group vs 22% in the lower group comprising all 40 other countries, p < 10-15). In addition, there was a significantly higher 50RR in participants with a baseline seizure frequency of six or fewer seizures per 28 days (29% vs 21%, p = .00018).

SIGNIFICANCE

These results can assist future RCTs in estimating the expected placebo responder rate, which may lead to more reliable power estimates. Higher placebo responder rate was associated with markers of less-refractory epilepsy. There were concerning significant differences in placebo responder rate by country and geographic region as well as an elevated placebo responder rate in participants with baseline seizure frequency close to the minimum eligibility criteria.

Time to prerandomization seizure count design sufficiently assessed the safety and tolerability of perampanel for the treatment of primary generalized tonic-clonic seizures

OBJECTIVE

Static assignment of participants in randomized clinical trials to placebo or ineffective treatment confers risk from continued seizures. An alternative trial design of time to exceed prerandomization monthly seizure count (T-PSC) has replicated the efficacy conclusions of traditionally designed trials, with shorter exposure to placebo and ineffective treatment. Trials aim to evaluate efficacy as well as safety and tolerability; therefore, we evaluated whether this T-PSC design also could replicate the trial's safety and tolerability conclusions.

METHODS

We retrospectively applied the T-PSC design to analyze treatment-emergent adverse events (TEAEs) from a blinded, placebo-controlled trial of perampanel for primary generalized tonic-clonic seizures (NCT01393743). The safety analysis set consisted of 81 and 82 participants randomized to perampanel and placebo arms, respectively. We evaluated the incidences of TEAEs, treatment-related TEAEs, serious TEAEs, and TEAEs of special interest that occurred before T-PSC relative to those observed during the full-length trial.

RESULTS

Of the 67 and 59 participants who experienced TEAEs in the perampanel and placebo arms during full-length trial, 66 (99%) and 54 (92%) participants experienced TEAEs with onset occurring before T-PSC, respectively. When limited to treatment-related TEAEs, 55 of 56 (98%) and 32 of 37 (86%) participants reported treatment-related TEAEs that occurred before T-PSC in the perampanel and placebo arms, respectively. There were more TEAEs after T-PSC with placebo as compared to perampanel (Fisher exact odds ratio = 8.6, p = .035), which resulted in overestimation of the difference in TEAE rate. There was a numerical reduction in serious TEAEs (3/13 occurred after T-PSC, one in placebo and two in perampanel).

SIGNIFICANCE

Almost all TEAEs occurred before T-PSC. More treatment-related TEAEs occurred after T-PSC for participants randomized to placebo than perampanel, which may be due to either a shorter T-PSC or delayed time to TEAE for placebo.

The present and future of seizure detection, prediction, and forecasting with machine learning, including the future impact on clinical trials

Seizures have a profound impact on quality of life and mortality, in part because they can be challenging both to detect and forecast. Seizure detection relies upon accurately differentiating transient neurological symptoms caused by abnormal epileptiform activity from similar symptoms with different causes. Seizure forecasting aims to identify when a person has a high or low likelihood of seizure, which is related to seizure prediction. Machine learning and artificial intelligence are data-driven techniques integrated with neurodiagnostic monitoring technologies that attempt to accomplish both of those tasks. In this narrative review, we describe both the existing software and hardware approaches for seizure detection and forecasting, as well as the concepts for how to evaluate the performance of new technologies for future application in clinical practice. These technologies include long-term monitoring both with and without electroencephalography (EEG) that report very high sensitivity as well as reduced false positive detections. In addition, we describe the implications of seizure detection and forecasting upon the evaluation of novel treatments for seizures within clinical trials. Based on these existing data, long-term seizure detection and forecasting with machine learning and artificial intelligence could fundamentally change the clinical care of people with seizures, but there are multiple validation steps necessary to rigorously demonstrate their benefits and costs, relative to the current standard.

Placebo response in patients with Dravet syndrome: Post-hoc analysis of two clinical trials

OBJECTIVE

Dravet syndrome is a rare, early childhood-onset epileptic and developmental encephalopathy. Responses to placebo in clinical trials for epilepsy therapies range widely, but factors influencing placebo response remain poorly understood. This study explored placebo response and its effects on safety, efficacy, and quality of life outcomes in patients with Dravet syndrome.

METHODS

We performed exploratory post-hoc analyses of pooled data from placebo-treated patients from the GWPCARE 1B and GWPCARE 2 randomized controlled phase III trials, comparing cannabidiol and matched placebo in 2-18 year old Dravet syndrome patients. All patients had ≥4 convulsive seizures during a baseline period of 4 weeks.

RESULTS

124 Dravet syndrome-treated patients were included in the analysis (2-5 years: n = 35; 6-12 years: n = 52; 13-18 years: n = 37). Convulsive seizures were experienced by all placebo group patients at all timepoints, with decreased median convulsive seizure frequency during the treatment period versus baseline; the number of convulsive seizure-free days was similar to baseline. Convulsive seizure frequency had a nominally significant positive correlation with age and a nominally significant negative correlation with body mass index. Most placebo-treated patients experienced a treatment-emergent adverse event; however, most resolved quickly, and serious adverse events were infrequent. Placebo treatment had very little effect on reported Caregiver Global Impression of Change outcomes versus baseline.

INTERPRETATION

Placebo had little impact on convulsive seizure-free days and Caregiver Global Impression of Change versus baseline, suggesting that these metrics may help differentiate placebo and active treatment effects in future studies. However, future research should further assess placebo responses to confirm these results.

Re-evaluating the placebo response in recent canine dietary epilepsy trials

The placebo response is a common phenomenon. Limited evidence is available about its magnitude in canine epilepsy trials, even though it can significantly influence the efficacy evaluation of new treatments. It was hypothesised that the placebo response is diminished when epilepsy trials are conducted in a prospective crossover design. Seizure data spanning six months from three previous multicenter epilepsy studies were analysed. The monthly seizure frequency of 60 dogs diagnosed with idiopathic epilepsy was calculated, comparing baseline data with placebo treatment. Furthermore, differentiation was made between dogs randomised to the placebo group early (Phase 1: first 3 months) or later during the study (Phase 2: second 3 months).The analysis did not reveal any placebo response in terms of monthly seizure frequency. Instead, an increase was noted during the placebo treatment period, with a mean of 2.95 seizures per month compared to 2.30 seizures per month before study entry (p = 0.0378). Additionally, a notable phase effect was observed. Dogs receiving the placebo in the second study phase exhibited a significant increase in monthly seizure frequency compared to baseline (p = 0.0036). Conversely, no significant difference from baseline was observed for dogs receiving the placebo in the first study phase. These findings underscore the considerable variability in placebo responses observed in trials for canine epilepsy, contrasting with previous limited data. The identified phase effect should be carefully considered in the design and evaluation of canine epilepsy trials to ensure a more accurate assessment of efficacy for new treatments.

An observational time-series study on the behavioral effects of adjunctive artisanal cannabidiol use by adults with treatment resistant epilepsies

BACKGROUND

For approximately 30% of people with epilepsy, seizures are not well-controlled by anti-seizure medication (ASM). This condition, called treatment resistant epilepsy (TRE), is associated with increased morbidity and mortality, and substantially impacts the quality of life of both the individual and their family. Non-responsiveness to ASMs leads many people with TRE to seek alternative therapies, such as cannabinoid-based medication, particularly cannabidiol (CBD), with or without medical or professional advice. This is due in part to widespread reporting in the media about the benefits of CBD for seizures in some forms of epilepsy.

METHODS

Adults with TRE, opting to add CBD to their existing treatment regime, completed this prospective, observational, longitudinal, quasi-experimental, time-series study. We hypothesized that adjunctive CBD use would positively impact participants' quality of life and psychological well-being in comparison to a baseline period without CBD use. Participants were followed for a period of approximately six months - for approximately one month of baseline prior to the initiation of CBD use and approximately five months after the initiation of CBD use. Participants provided urine samples and completed behavioral questionnaires that assessed quality of life, anxiety/depression, and adverse events during baseline and at two times during CBD use.

RESULTS

Complete case analyses (n = 10) showed a statistically significant improvement in quality of life, a statistically significant decrease in anxiety symptoms, and a statistically significant decrease in the experience of adverse events over time (p < 0.05). Improvements noted in the experience of depression symptoms did not reach statistical significance. Urinalysis revealed the majority of participants had no CBD/metabolites in their system at the beginning of the study, and confirmed the presence of CBD/metabolites in participants' urine after CBD was added to their treatment regime. Analysis of missing data using multiple imputation supported the findings of the complete case analysis.

INTERPRETATION

For a small group of individuals with TRE of varying etiologies, adjunctive use of artisanal CBD was associated with improvements in the behavioral and psychological symptoms of TRE, as well as improved medication tolerability.

Challenges and directions in epilepsy diagnostics and therapeutics: Proceedings of the 17th Epilepsy Therapies and Diagnostics Development conference

Substantial efforts are underway toward optimizing the diagnosis, monitoring, and treatment of seizures and epilepsy. We describe preclinical programs in place for screening investigational therapeutic candidates in animal models, with particular attention to identifying and eliminating drugs that might paradoxically aggravate seizure burden. After preclinical development, we discuss challenges and solutions in the design and regulatory logistics of clinical trial execution, and efforts to develop disease biomarkers and interventions that may be not only seizure-suppressing, but also disease-modifying. As disease-modifying treatments are designed, there is clear recognition that, although seizures represent one critical therapeutic target, targeting nonseizure outcomes like cognitive development or functional outcomes requires changes to traditional designs. This reflects our increasing understanding that epilepsy is a disease with profound impact on quality of life for the patient and caregivers due to both seizures themselves and other nonseizure factors. This review examines selected key challenges and future directions in epilepsy diagnostics and therapeutics, from drug discovery to translational application.

Inductive reasoning with large language models: a simulated randomized controlled trial for epilepsy

Importance

The analysis of electronic medical records at scale to learn from clinical experience is currently very challenging. The integration of artificial intelligence (AI), specifically foundational large language models (LLMs), into an analysis pipeline may overcome some of the current limitations of modest input sizes, inaccuracies, biases, and incomplete knowledge bases.

Objective

To explore the effectiveness of using an LLM for generating realistic clinical data and other LLMs for summarizing and synthesizing information in a model system, simulating a randomized clinical trial (RCT) in epilepsy to demonstrate the potential of inductive reasoning via medical chart review.

Design

An LLM-generated simulated RCT based on a RCT for treatment with an antiseizure medication, cenobamate, including a placebo arm and a full-strength drug arm, evaluated by an LLM-based pipeline versus a human reader.

Setting

Simulation based on realistic seizure diaries, treatment effects, reported symptoms and clinical notes generated by LLMs with multiple different neurologist writing styles.

Participants

Simulated cohort of 240 patients, divided 1:1 into placebo and drug arms.

Intervention

Utilization of LLMs for the generation of clinical notes and for the synthesis of data from these notes, aiming to evaluate the efficacy and safety of cenobamate in seizure control either with a human evaluator or AI-pipeline.

Measures

The AI and human analysis focused on identifying the number of seizures, symptom reports, and treatment efficacy, with statistical analysis comparing the 50%-responder rate and median percentage change between the placebo and drug arms, as well as side effect rates in each arm.

Results

AI closely mirrored human analysis, demonstrating the drug's efficacy with marginal differences (<3%) in identifying both drug efficacy and reported symptoms.

Conclusions and Relevance

This study showcases the potential of LLMs accurately simulate and analyze clinical trials. Significantly, it highlights the ability of LLMs to reconstruct essential trial elements, identify treatment effects, and recognize reported symptoms, within a realistic clinical framework. The findings underscore the relevance of LLMs in future clinical research, offering a scalable, efficient alternative to traditional data mining methods without the need for specialized medical language training.

Quantifying and controlling the impact of regression to the mean on randomized controlled trials in epilepsy

OBJECTIVE

Randomized controlled trials (RCTs) in epilepsy for drug treatments are plagued by high costs. One potential remedy is to reduce placebo response via better control over regression to the mean (RTM). Here, RTM represents an initial observed seizure rate higher than the long-term average, which gradually settles closer to the average, resulting in apparent response to treatment. This study used simulation to clarify the relationship between eligibility criteria and RTM.

METHODS

Using a statistically realistic seizure diary simulator, the impact of RTM on placebo response and trial efficacy was explored by varying eligibility criteria for a traditional treatment phase II/III RCT for drug-resistant epilepsy.

RESULTS

When the baseline period was included in the eligibility criteria, increasingly larger fractions of RTM were observed (25%-47% vs. 23%-25%). Higher fractions of RTM corresponded with higher expected placebo responses (50% responder rate [RR50]: 2%-9% vs. 0%-8%) and lower statistical efficacy (RR50: 47%-67% vs. 47%-81%). The exclusion of baseline from eligibility criteria was shown to decrease the number of patients needed by roughly 30%.

SIGNIFICANCE

The manipulation of eligibility criteria for RCTs has a predictable and important impact on RTM, and therefore on placebo response; the difference between drug and placebo was more easily detected. This in turn impacts trial efficacy and therefore cost. This study found dramatic improvements in efficacy and cost when baseline was not included in eligibility.

Increasing challenges to trial recruitment and conduct over time

OBJECTIVE

This study was undertaken to evaluate how the challenges in the recruitment and retention of participants in clinical trials for focal onset epilepsy have changed over time.

METHODS

In this systematic analysis of randomized clinical trials of adjunct antiseizure medications for medication-resistant focal onset epilepsy, we evaluated how the numbers of participants, sites, and countries have changed since the first such trial in 1990. We also evaluated the proportion of participants who completed each trial phase and their reasons for early trial exit. We analyzed these trends using mixed effects generalized linear models accounting for the influence of the number of trial sites and trial-specific variability.

RESULTS

The number of participants per site has steadily decreased over decades, with recent trials recruiting fewer than five participants per site (reduction by .16 participants/site/year, p < .0001). Fewer participants also progressed from recruitment to randomization over time (odds ratio = .94/year, p = .014). Concurrently, there has been an increase in the placebo response over time (increase in median percent reduction of .4%/year, p = .02; odds ratio of increase in 50% responder rate of 1.03/year, p = .02), which was not directly associated with the number of sites per trial (p > .20).

SIGNIFICANCE

This historical analysis highlights the increasing challenges with participant recruitment and retention, as well as increasing placebo response. It serves as a call to action to change clinical trial design to address these challenges.

Reasons for ineligibility for clinical trials of patients with medication-resistant epilepsy

Selection criteria for clinical trials for medication-resistant epilepsy are used to limit variability and to ensure safety. However, it has become more challenging to recruit subjects for trials. This study investigated the impact of each inclusion and exclusion criterion on medication-resistant epilepsy clinical trial recruitment at a large academic epilepsy center. We retrospectively identified all patients with medication-resistant focal or generalized onset epilepsy who attended an outpatient clinic over a consecutive 3-month period. We assessed each patient's eligibility for trials with commonly required inclusion and exclusion criteria to evaluate the proportion of eligible patients and the most common reasons for exclusion. Among 212 patients with medication-resistant epilepsy, 144 and 28 patients met the criteria for focal or generalized onset epilepsy, respectively. Overall, 9.4% (n = 20) patients were eligible for trials (19 focal onset and one generalized onset). Most patients were excluded from the study due to insufficient seizure frequency (58% of focal onset, 55% of generalized onset). A small proportion of patients with medication-resistant epilepsy were eligible for trials based on common selection criteria. These eligible patients may not be representative of the general population of patients with medication-resistant epilepsy. Insufficient seizure frequency was the most common reason for exclusion.

Translational veterinary epilepsy: A win-win situation for human and veterinary neurology

Epilepsy is a challenging multifactorial disorder with a complex genetic background. Our current understanding of the pathophysiology and treatment of epilepsy has substantially increased due to animal model studies, including canine studies, but additional basic and clinical research is required. Drug-resistant epilepsy is an important problem in both dogs and humans, since seizure freedom is not achieved with the available antiseizure medications. The evaluation and exploration of pharmacological and particularly non-pharmacological therapeutic options need to remain a priority in epilepsy research. Combined efforts and sharing knowledge and expertise between human medical and veterinary neurologists are important for improving the treatment outcomes or even curing epilepsy in dogs. Such interactions could offer an exciting approach to translate the knowledge gained from people and rodents to dogs and vice versa. In this article, a panel of experts discusses the similarities and knowledge gaps in human and animal epileptology, with the aim of establishing a common framework and the basis for future translational epilepsy research.

Personalized, Multisession, Multichannel Transcranial Direct Current Stimulation in Medication-Refractory Focal Epilepsy: An Open-Label Study

PURPOSE

Animal and proof-of-principle human studies suggest that cathodal transcranial direct current stimulation may suppress seizures in drug-resistant focal epilepsy. The present study tests the safety, tolerability, and effect size of repeated daily cathodal transcranial direct current stimulation in epilepsy have not been established, limiting development of clinically meaningful interventions.

METHODS

We conducted a 2-center, open-label study on 20 participants with medically refractory, focal epilepsy, aged 9 to 56 years (11 women and 9 children younger than18 years). Each participant underwent 10 sessions of 20 minutes of cathodal transcranial direct current stimulation over 2 weeks. Multielectrode montages were designed using a realistic head model-driven approach to conduct an inhibitory electric field to the target cortical seizure foci and surrounding cortex to suppress excitability and reduce seizure rates. Patients recorded daily seizures using a seizure diary 8 weeks prior, 2 weeks during, and 8 to 12 weeks after the stimulation period.

RESULTS

The median seizure reduction was 44% relative to baseline and did not differ between adult and pediatric patients. Three patients experienced an increase in seizure frequency of >50% during the stimulation period; in one, a 36% increase in seizure frequency persisted through 12 weeks of follow-up. Otherwise, participants experienced only minor adverse events-the most common being scalp discomfort during transcranial direct current stimulation.

CONCLUSIONS

This pilot study supports the safety and efficacy of multifocal, personalized, multichannel, cathodal transcranial direct current stimulation for adult and pediatric patients with medication-refractory focal epilepsy, although identifies a possibility of seizure exacerbation in some. The data also provide insight into the effect size to inform the design of a randomized, sham-stimulation controlled trial.

Investigating the trends in patient-reported outcomes pre-treatment and implications to efficacy analyses: A post-hoc analysis of a cancer clinical trial

Background

Uncertainty around key elements of an appropriate patient-reported outcome (PRO) baseline assessment introduces trial-specific variation in oncology clinical trials with a poorly understood consequence on drug evaluation decisions. This research investigated the impact of multiple pre-treatment PRO assessments and timing of assessments in a clinical trial.

Methods

A post-hoc analysis of a completed phase 3, open-label, randomized, parallel arm clinical trial in non-small cell lung cancer with two pre-treatment PRO assessments (screening and Week 1 Day 1 [W1D1]). Descriptive analyses, mixed models for repeated measures and time until definitive deterioration analyses were performed to estimate differences between treatment arms. Through model adjustments, different baseline specifications and assessment timing (pre/post-randomization) on W1D1 PROs were evaluated.

Results

Patients with both pre-treatment PRO assessments were included in the analysis (N = 535). Numerically small average change scores were observed between screening and W1D1 (mean change, 0-100 scale ranges): Chest pain (-0.94), Cough (-0.94), Dyspnea (1.27), Physical functioning (-1.19). Both pre-treatment assessments were moderately-highly correlated (r: 0.55-0.78) and no trend was found for deterioration or improvement during this period. Varying baseline definitions in the models produced slight differences in model fit but no impact on the between treatment group effect estimate. W1D1 PRO scores were not statistically influenced by assessment timing pre/post-randomization (p-values: 0.142-0.628).

Conclusion

Findings from this study question the need for multiple pre-treatment PRO assessments in oncology drug development trials and the degree of bias thought to be introduced through patient knowledge of treatment assignment. Implications for researchers are presented.

Significant improvements in SEIzure interVAL (time between seizure clusters) across time in patients treated with diazepam nasal spray as intermittent rescue therapy for seizure clusters

OBJECTIVE

Intermittent rescue therapy may be used for seizure clusters, which are clinical emergencies that may persist ≥24 h and increase risk of status epilepticus, emergency room visits, and reduced quality of life for patients with epilepsy. Beyond effectiveness for aborting seizure clusters, no data exist on how intermittent rescue therapy may impact the long-term natural course of seizure clusters. This novel analysis explores SEIzure interVAL (SEIVAL; time between seizure clusters) in patients from a long-term safety study of diazepam nasal spray (Valtoco) to assess SEIVAL changes with intermittent rescue therapy across time.

METHODS

Patients were aged 6-65 years. Age- and weight-based doses of diazepam nasal spray were administered during a 12-month treatment period with an optional follow-up period. SEIVAL was evaluated in patients receiving two or more doses of diazepam nasal spray using 90-day periods.

RESULTS

Of 163 treated patients, 151 had one or more SEIVALs. One hundred twenty had SEIVALs in Period 1 and one or more other periods. An increase in SEIVAL was noted from Period 1 compared with all subsequent periods (p ≤ .001). A consistent cohort (n = 76) had one or more SEIVALs in each of Periods 1-4 (360 days); mean SEIVALs increased significantly (p < .01) from 12.2 days (Period 1) to 25.7 days (Period 4). Similar SEIVAL patterns occurred when repeat doses within a seizure cluster were eliminated and irrespective of age group, treatment duration, and change to concomitant medications. In adults, Quality of Life in Epilepsy scores were maintained with increased SEIVALs.

SIGNIFICANCE

Across 12 months, increases in SEIVAL were demonstrated in patients using diazepam nasal spray for seizure cluster treatment in a phase 3 safety study. Increased time between seizure clusters may reflect a previously unrecognized beneficial effect of intermittent rescue therapy. These results generate a range of biological and behavioral hypotheses and warrant exploration of the impact of intermittent rescue therapy.

Dogs as a Natural Animal Model of Epilepsy

Epilepsy is a common neurological disease in both humans and domestic dogs, making dogs an ideal translational model of epilepsy. In both species, epilepsy is a complex brain disease characterized by an enduring predisposition to generate spontaneous recurrent epileptic seizures. Furthermore, as in humans, status epilepticus is one of the more common neurological emergencies in dogs with epilepsy. In both species, epilepsy is not a single disease but a group of disorders characterized by a broad array of clinical signs, age of onset, and underlying causes. Brain imaging suggests that the limbic system, including the hippocampus and cingulate gyrus, is often affected in canine epilepsy, which could explain the high incidence of comorbid behavioral problems such as anxiety and cognitive alterations. Resistance to antiseizure medications is a significant problem in both canine and human epilepsy, so dogs can be used to study mechanisms of drug resistance and develop novel therapeutic strategies to benefit both species. Importantly, dogs are large enough to accommodate intracranial EEG and responsive neurostimulation devices designed for humans. Studies in epileptic dogs with such devices have reported ictal and interictal events that are remarkably similar to those occurring in human epilepsy. Continuous (24/7) EEG recordings in a select group of epileptic dogs for >1 year have provided a rich dataset of unprecedented length for studying seizure periodicities and developing new methods for seizure forecasting. The data presented in this review substantiate that canine epilepsy is an excellent translational model for several facets of epilepsy research. Furthermore, several techniques of inducing seizures in laboratory dogs are discussed as related to therapeutic advances. Importantly, the development of vagus nerve stimulation as a novel therapy for drug-resistant epilepsy in people was based on a series of studies in dogs with induced seizures. Dogs with naturally occurring or induced seizures provide excellent large-animal models to bridge the translational gap between rodents and humans in the development of novel therapies. Furthermore, because the dog is not only a preclinical species for human medicine but also a potential patient and pet, research on this species serves both veterinary and human medicine.

Assessing preoperative hope and expectations related to functional neurosurgery: a new questionnaire

BACKGROUND

Despite successful functional neurosurgery, patients suffering from epilepsy or Parkinson's disease may experience postoperative psychological distress and social maladjustments. Difficulties in coping with postoperative changes, even positive ones, have shown to be related to patients' presurgery cognitive representations (i.e., expectations, hope). The aim of this study was to develop an instrument assessing various key features of surgery outcomes' representations, namely the Preoperative Hope and Expectations Questionnaire (PHEQ).

METHODS

Participants were patients (n = 50) diagnosed with Parkinson's disease (n = 25) or epilepsy (n = 25), candidates for functional neurosurgery (i.e., Deep brain stimulation, anterior temporal lobectomy). Two to three weeks before the planned surgery, they were administrated items assessing their actual state, preoperative expectations, and hope regarding surgery outcomes. They also completed measures assessing optimism, quality of life and mood.

RESULTS

Exploratory analysis resulted in a 14-item version of the PHEQ composed of two factors (abstract representations, including psychological well-being and concrete representations, such as direct surgery outcomes). The PHEQ demonstrated high internal consistency and good convergent validity. Patients were more prone to express postoperative improvements in terms of hope rather than expectations. They generally focused on concrete rather than abstract features, although patients with Parkinson's disease had higher abstract future-oriented representations.

CONCLUSIONS

The PHEQ presents satisfactory psychometric properties and may be considered as a reliable instrument for research and clinical practice.

Lack of association between generic brittleness and neuropsychiatric measures in patients with epilepsy

PURPOSE

In a prior bioequivalence study, generic brittle (GB) patients with epilepsy who were considered at risk of worsened seizures or drug side effects from switching antiepileptic drug (AED) formulations demonstrated no significant difference in their drug levels when switched between a brand and generic AED. An alternative basis for being GB may relate to having a personality or mindset that predisposes to poor outcomes from a formulation switch. The objective of this study was to explore whether GB patients with epilepsy could be differentiated from not GB patients based on standardized measures of personality, mood, outlook, and beliefs.

METHODS

This was an exploratory, observational, case-control, non-therapeutic study in patients with epilepsy. Patient interviews were conducted, and histories were collected, yielding each patient (n = 148) to be determined as GB or not GB. Eight neuropsychiatry tests were administered to n = 127 of these patients. Tests included Neuroticism Extraversion Openness Personality Inventory 3 (NEO-PI 3), Life Orientation Test-Revised (LOT-R), Quality of Life in Epilepsy Inventory-89 (QOLIE-89), Adverse Childhood Experiences Score (ACE), Physical Symptoms Questionnaire or Patient Health Questionnaire-15 (PHQ-15), Beck Depression Inventory II (BDI-II), Beck Anxiety Inventory (BAI), and the Beliefs About Medicines Questionnaire Epilepsy (BMQ-Epilepsy). A total of 23 Chi squared analyses, along with logistical regression, were performed to assess which tests and sub-elements associated with GB status.

RESULTS

None of the neuropsychiatry tests or their sub-elements differentiated GB patients from not GB patients. Results implicate that standardized measures of personality, mood, outlook, and beliefs about their healthcare do not differ between GB and not GB patients with epilepsy, possibly because generic brittleness is caused by factors that neuropsychiatry tests do not measure.

CONCLUSIONS

We hypothesized that being GB may relate to having a personality or mindset that predisposes patients to attributing poor outcomes to a formulation switch. However, findings here in patients with epilepsy did not uncover neuropsychiatric factors that predict which patients were GB and which were not GB.

Seizure frequency, quality of life, behavior, cognition, and sleep in pediatric patients enrolled in a prospective, open-label clinical study with cannabidiol

OBJECTIVE

To evaluate the effects of oral pharmacological cannabidiol (CBD) on seizures, side effects, quality of life, behavior, mood, and sleep in children with drug-resistant epilepsy (DRE) during a phase II, prospective, open-label clinical study.

METHODS

During a phase II expanded access program (EAP) study to evaluate the safety and efficacy of using cannabidiol (CBD) for the long-term treatment of children with drug-resistant epilepsy, secondary outcome measures were also performed, including quality of life (QOLCE), behavior (aberrant behavior checklist ABC), and sleep (children's sleep habit questionnaire, CSHQ). Participants between the ages of 2 and 16 years of age with drug-resistant epilepsy (n = 35) were included in this EAP. Primary outcomes included change in parent-recorded seizure frequency relative to baseline, as well as the safety and tolerability over the course of 24 months of CBD treatment. Secondary outcomes observed in the first 12 months included changes in child behavior, and cognitive function, and sleep quality.

RESULTS

The median change in overall seizure frequency decreased from baseline (n = 33) by -61.3% ([n = 33], Inter Quartile Range (IQR): 43-88%) at month 3, -62.9% at month 6 ([n = 29], IQR: 48-92%), -74.7% at month 12 ([n = 29], IQR: 64-96%), and finally -83.7% ([n = 28], IQR: 68-100%) at the conclusion of 24 months of treatment. Seven (20%) of the 35 patients enrolled withdrew from treatment and observation by month 24: 2 failed inclusion criteria at baseline, 4 due to lack of treatment efficacy, and 1 was lost to follow-up. The 12-month recording of secondary measures revealed a significant improvement in Irritability (-39.4%, [n = 28], ABC), Hyperactivity (-45.4%, [n = 28], ABC), Cognition in Quality of Life (+14.2%, [n = 28], QOLCE), Behavioral function (+14.7%, [n = 28], QOLCE), General Health (+14.7%, [n = 28], QOLCE), Sleep duration (-33.9%, [n = 28], CSHQ), Daytime sleepiness (-23.8%, [n = 28], CSHQ), and nocturnal arousals (-36.2%, [n = 28], CSHQ).

SIGNIFICANCE

The results of this phase II open-label study demonstrate that pharmacological CBD significantly reduces seizure frequency, and improves QOL, behavior deficits, and sleep disruption, in children with drug-resistant epilepsy. The results also suggest that CBD is efficacious in controlled seizures over a 2-year period in childhood DRE.

A Phase 2 Randomized Controlled Trial of the Efficacy and Safety of Cannabidivarin as Add-on Therapy in Participants with Inadequately Controlled Focal Seizures

Objective: We assessed the efficacy, safety, and tolerability of cannabidivarin (CBDV) as add-on therapy in adults with inadequately controlled focal seizures. Materials and Methods: One hundred and sixty-two participants (CBDV n=81; placebo n=81) were enrolled. After a 4-week baseline, participants titrated from 400 to 800 mg CBDV twice daily (b.i.d.) (or placebo) over 2 weeks, followed by 6 weeks stable dosing (at 800 mg b.i.d.) and a 12-day taper period. The primary endpoint was the change from baseline in focal seizure frequency during the 8-week treatment period. Secondary endpoints included additional efficacy measures relating to seizures, physician- and participant-reported outcomes, change in the use of rescue medication, cognitive assessments, and safety. Results: Median baseline focal seizure frequencies were 17-18 per 28 days in both groups, and similar reductions in frequency were observed in the CBDV (40.5%) and placebo (37.7%) groups during the treatment period (treatment ratio [% reduction] CBDV/placebo: 0.95 [4.6]; confidence interval: 0.78-1.17 [-16.7 to 21.9]; p=0.648). There were no differences between the CBDV and placebo groups for any seizure subtype. There were no significant treatment differences between CBDV and placebo groups for any of the secondary efficacy outcome measures. Overall, 59 (72.8%) of participants in the CBDV group and 39 (48.1%) in the placebo group had ≥1 treatment-emergent adverse event (AE); the 3 most common were diarrhea, nausea, and somnolence. The incidence of serious AEs was low (3.7% in the CBDV group vs. 1.2% in the placebo group). There was little or no effect of CBDV on vital signs, physical examination, or electrocardiogram findings. Elevations in serum transaminases (alanine aminotransferase or aspartate aminotransferase) to levels >3×upper limit of normal occurred in three participants taking CBDV (two discontinued as a result) and one taking placebo; however, none met the criteria for potential Hy's Law cases. Conclusion: It is likely the 40.5% seizure reduction with CBDV represents an appropriate pharmacological response in this population with focal seizures. The placebo response was, however, high, which may reflect the participants' expectations of CBDV, and a treatment difference from placebo was not observed. CBDV was generally well tolerated. Clinical Trial Registration number: NCT02365610.

Deep Brain Stimulation for Refractory Focal Epilepsy: Unraveling the Insertional Effect up to Five Months Without Stimulation

INTRODUCTION

Following electrode implantation, a subgroup of patients treated with deep brain stimulation (DBS) for focal epilepsy exhibits a reduction of seizure frequency before stimulation is initiated. Microlesioning of the target structure has been postulated to be the cause of this "insertional" effect (IE). We examined the occurrence and duration of this IE in a group of patients with focal epilepsy following electrode implantation in the anterior nuclei of the thalamus (ANT) and/or nucleus accumbens (NAC) for DBS treatment.

MATERIALS AND METHODS

Changes in monthly seizure frequency compared to preoperative baseline were assessed one month (14 patients) and five months (four patients) after electrode implantation. A group analysis between patients with implantation of bilateral ANT-electrodes (four patients), NAC-electrodes (one patient) as well as ANT and NAC-electrodes (nine patients) was performed.

RESULTS

In this cohort, seizure frequency decreased one month after electrode implantation by 57.1 ± 30.1%, p ≤ 0.001 (compared to baseline). No significant difference within stimulation target subcohorts was found (p > 0.05). Out of the four patients without stimulation for five months following electrode insertion, three patients showed seizure frequency reduction lasting two to three months, while blinded to their stimulation status.

CONCLUSION

An IE might explain seizure frequency reduction in our cohort. This effect seems to be independent of the number of implanted electrodes and of the target itself. The time course of the blinded subgroup of epilepsy patients suggests a peak of the lesional effect at two to three months after electrode insertion.

Imepitoin for treatment of idiopathic head tremor syndrome in dogs: A randomized, blinded, placebo-controlled study

Background

Idiopathic head tremor syndrome is a paroxysmal movement disorder of unknown etiology. Spontaneous remission may occur, but owners may request treatment in severely affected dogs with continued episodes. Controlled studies of the disease are not available.

Hypothesis/Objectives

A drug with gamma amino butyric acid‐ergic and anxiolytic effects will decrease head tremor episodes.

Animals

Twenty‐four dogs with severe nonremitting head tremor and presumptive clinical diagnosis of idiopathic head tremor syndrome.

Methods

Prospective, blinded, placebo‐controlled clinical trial to compare imepitoin with placebo in dogs with frequent episodes of idiopathic head tremor. Evaluation of efficacy used the quotient T2/T1 that represented prolongation of the head tremor‐free period compared to a 3‐month baseline. A dog was considered a responder if tremors subsided or if the head tremor‐free period was 3× longer than the longest period during baseline (T2/T1 ≥ 3). Sample size calculations considered a large effect of imepitoin on T2/T1 (Cohen's d = 0.8).

Results

There were no responders in the placebo group (0/12). In the imepitoin group, the responder rate was 17% (2/12; P = .18) with T2/T1 3.8 and 4.0. Mean T2/T1 was 1.0 ± 1.4 in the imepitoin and 0.4 ± 0.4 in the placebo group (P = .37).

Conclusion and Clinical Importance

Imepitoin did not result in a significant overall benefit. Future studies should focus on treatment of subgroups with a common pathophysiology and similar comorbidities.

Taking Optogenetics into the Human Brain: Opportunities and Challenges in Clinical Trial Design

Optogenetics, the use of light to control the activity of suitably sensitized cells, has led to major advances in the field of basic neuroscience since it first emerged in 2005. Already, the technique has entered clinical trials for conditions such as Retinitis Pigmentosa. A major focus of interest is the use of optogenetics within the brain, where the ability to precisely control the activity of specific subsets of neurons could lead to novel treatments for a wide range of disorders from epilepsy to schizophrenia. However, since any therapy would require both the use of gene therapy techniques to introduce non-human proteins, and implantable electronic devices to provide optical stimulation, applying this technique in the brain presents a unique set of obstacles and challenges. This review looks at the reasons why researchers are exploring the use of optogenetics within the brain. It then explores the challenges facing scientists, engineers and clinicians wanting to take this technology from the lab into the first human brain, discussing different possibilities for a first-in-human clinical trial from a sponsor, patient and regulatory perspective.

Placebo in epilepsy

Placebos impact epilepsy in a number of ways. Through randomized clinical trials, explicit clinical use, and also through implicit clinical use, placebos play a role in epilepsy. This chapter will discuss the reasons placebo is used, the determinants of placebo response in epilepsy, observations about placebo specific to epilepsy, and ways in which clinical trial design is impacted by placebo.

Natural variability in seizure frequency: Implications for trials and placebo

BACKGROUND

Changes in patient-reported seizure frequencies are the gold standard used to test efficacy of new treatments in randomized controlled trials (RCTs). Recent analyses of patient seizure diary data suggest that the placebo response may be attributable to natural fluctuations in seizure frequency, though the evidence is incomplete. Here we develop a data-driven statistical model and assess the impact of the model on interpretation of placebo response.

METHODS

A synthetic seizure diary generator matching statistical properties seen across multiple epilepsy diary datasets was constructed. The model was used to simulate the placebo arm of 5000 RCTs. A meta-analysis of 23 historical RCTs was compared to the simulations.

RESULTS

The placebo 50 %-responder rate (RR50) was 27.3 ± 3.6 % (simulated) and 21.1 ± 10.0 % (historical). The placebo median percent change (MPC) was 22.0 ± 6.0 % (simulated) and 16.7 ± 10.3 % (historical).

CONCLUSIONS

A statistical model of daily seizure count generation which incorporates quantities related to the natural fluctuations of seizure count data produces a placebo response comparable to those seen in historical RCTs. This model may be useful in better understanding the seizure count fluctuations seen in patients in other clinical settings.

Sequential parallel comparison design with two coprimary endpoints

A placebo-controlled randomized clinical trial is required to demonstrate that an experimental treatment is superior to its corresponding placebo on multiple coprimary endpoints. This is particularly true in the field of neurology. In fact, clinical trials for neurological disorders need to show the superiority of an experimental treatment over a placebo in two coprimary endpoints. Unfortunately, these trials often fail to detect a true treatment effect for the experimental treatment versus the placebo owing to an unexpectedly high placebo response rate. Sequential parallel comparison design (SPCD) can be used to address this problem. However, the SPCD has not yet been discussed in relation to clinical trials with coprimary endpoints. In this article, our aim was to develop a hypothesis-testing method and a method for calculating the corresponding sample size for the SPCD with two coprimary endpoints. In a simulation, we show that the proposed hypothesis-testing method achieves the nominal type I error rate and power and that the proposed sample size calculation method has adequate power accuracy. In addition, the usefulness of our methods is confirmed by returning to an SPCD trial with a single primary endpoint of Alzheimer disease-related agitation.

A double-blinded randomised dietary supplement crossover trial design to investigate the short-term influence of medium chain fatty acid (MCT) supplement on canine idiopathic epilepsy: study protocol

Background

Epilepsy is the most common brain disease in dogs. Recently, diets have been reported to have a positive impact on seizure activity and behaviour in various species including dogs with idiopathic epilepsy (IE). Historically, classic high fat ketogenic diets (KD) and medium chain triglycerides (MCT) KD have been successfully used to manage drug-resistant epilepsy. Similarly, an MCT enriched diet has been shown to improve seizure control and behavioural comorbidities in some dogs with IE. However, it is unknown whether an MCT dietary supplement (DS) may provide similar positive effects.

Methods

A 6-month prospective, randomised, double-blinded, placebo-controlled, crossover, multicentre dietary trial is designed comparing a 9% metabolic energy based calculated medium-chain triglyceride (MCT) oil supplement to a conventional ‘control’ DS. Only dogs which will have an International Veterinary Epilepsy Task Force Tier II level like diagnosis of IE which satisfied the following inclusion criteria are included: age between 6 months and ≤ 12 years; weighing between 4 and ≤ 65 kg; unremarkable interictal neurological examinations; no clinically significant findings on routine laboratory diagnostics; unremarkable brain MRI scan; have had at least 3 seizures in the previous 3 months prior to enrolment; treated with at least one ASD and being classified as resistant. All dogs are fed initially for 90 ± 2 days with either the control oil or the MCT oil alongside their normal diet, followed by 97 ± 2 days with the other supplement including a 7-day washout period. Overall, the aim is to recruit thirty-six patients at five different centres and to investigate the effect of MCTs as DS on seizure activity, tolerability, behavioural comorbidities and quality of life (QoL).

Discussion

Dietary interventions are rarely studied in a standardised form in veterinary medicine. The background diet, the cohort of animals and ASD received is standardised in this prospective diet trial to ensure representative data about the potential effect of MCT DS. If the study data confirms former findings, this would provide further evidence for the efficacy of MCTs as a management option for canine epilepsy. This publication should offer a repository of trial conditions and variable description with forecasted statistical analysis.

Electronic supplementary material

The online version of this article (10.1186/s12917-019-1915-8) contains supplementary material, which is available to authorized users.

Geriatric pharmacotherapy: Appraising new drugs for neurologic disorders in older patients

New drug development for neurologic disorders has one of the highest attrition rates of all clinical drug developments. This is problematic when, with innovative technology available in so many aspects of life, modern societies expect to have effective treatments for neurodegenerative disorders and mental health conditions that provide something beyond simple symptomatic relief-the expectation is treatment that impacts and mitigates fundamental mechanisms that drive these disorders. The disease burden of neurologic disorders remains extremely high, whereas the proportion of patients receiving effective therapy is relatively low, demonstrating a sizeable unmet medical need. Whether for novel breakthrough therapies or for drugs considered successful, deciding on the basis of clinical trial data whether a particular treatment will be effective for a specific patient is always a leap of faith. However, expertise at reading trial results combined with knowledge of the patient and of his or her disease, together with an understanding of the effect of age on drug pharmacokinetics and pharmacodynamics, the effect of age on the patient's condition, and the effect of age on the patient's life and outlook will ensure the landing is safe. The focus of this article is to provide such knowledge and thereby optimize this expertise.

Exploring generic brittleness and the demographic factors for its susceptibility in patients with epilepsy

PURPOSE

The purpose of this study was to provide an algorithm for generic brittleness and to elucidate the demographic factors that anticipate generic brittleness for patients with epilepsy.

METHODS

This exploratory, observational, and nontherapeutic study was conducted in patients with epilepsy who were routinely followed at the University of Maryland epilepsy outpatient clinic in Baltimore, Maryland. Patients were taking at least one antiepileptic drug (AED) for treatment of epilepsy. Based on patient interview and medical history, 12 demographic factors were collected. Each patient was assessed to be either generic brittle (GB) or not GB. Demographic factors were subjected to binary logistical regression and other statistical tests, to elucidate determinants of GB status.

RESULTS

N = 148 patients completed the study. An algorithm to define whether a patient was GB or not GB was devised. The two elements that defined GB status are as follows: patient opinion about generics and (if needed) whether patients were currently taking brand or generic of their most problematic AED. About 40% of patients were GB. From binary logistical regression, two demographic factors that contributed to patients being GB were whether a patient was currently taking a problem AED and total number of current medications for a patient, with odds ratios of 4.06 (95% confidence interval [CI] from 1.53 to 10.81) and 1.10 (95% CI from 1.003 to 1.21), respectively. Of the patients on a problem AED, 46.9% were GB, while only 18.2% of patients not currently on a problem AED were GB. The total number of current medications ranged from 1 to 22, with mode of four medications. From regression, for each additional medication that a patient took, the odds of being GB increased 1.10-fold. Although patient seizure and adverse event history was not employed to define GB status, being GB was associated with less seizure control and greater adverse events.

CONCLUSIONS

An algorithm for generic brittleness was derived, and about 40% of patients were GB, usually due to prior history of a switch problem. Two demographic factors favored patients being GB: whether the patient was currently taking a problem AED and the total number of current medications.

A simple test for the treatment effect in clinical trials with a sequential parallel comparison design and negative binomial outcomes

In placebo-controlled, double-blinded, randomized clinical trials, the presence of placebo responders reduces the effect size for comparison of the active drug group with the placebo group. An attempt to resolve this problem is to use the sequential parallel comparison design (SPCD). Although there are SPCDs with dichotomous or continuous outcomes, an SPCD with negative binomial outcomes-with which investigators deal eg, in clinical trials involving multiple sclerosis, where the investigators are still concerned about the presence of placebo responders-has not yet been discussed. In this article, we propose a simple test for the treatment effect in clinical trials with an SPCD and negative binomial outcomes. Through simulations, we show that the analysis method achieves the nominal type I error rate and power, whereas the sample size calculation provides the sample size with adequate power accuracy.

Is seizure frequency variance a predictable quantity?

Background

There is currently no formal method for predicting the range expected in an individual's seizure counts. Having access to such a prediction would be of benefit for developing more efficient clinical trials, but also for improving clinical care in the outpatient setting.

Methods

Using three independently collected patient diary datasets, we explored the predictability of seizure frequency. Three independent seizure diary databases were explored: SeizureTracker (n = 3016), Human Epilepsy Project (n = 93), and NeuroVista (n = 15). First, the relationship between mean and standard deviation in seizure frequency was assessed. Using that relationship, a prediction for the range of possible seizure frequencies was compared with a traditional prediction scheme commonly used in clinical trials. A validation dataset was obtained from a separate data export of SeizureTracker to further verify the predictions.

Results

A consistent mathematical relationship was observed across datasets. The logarithm of the average seizure count was linearly related to the logarithm of the standard deviation with a high correlation (R² > 0.83). The three datasets showed high predictive accuracy for this log-log relationship of 94%, compared with a predictive accuracy of 77% for a traditional prediction scheme. The independent validation set showed that the log-log predicted 94% of the correct ranges while the RR50 predicted 77%.

Conclusion

Reliably predicting seizure frequency variability is straightforward based on knowledge of mean seizure frequency, across several datasets. With further study, this may help to increase the power of RCTs, and guide clinical practice.

A multi-dataset time-reversal approach to clinical trial placebo response and the relationship to natural variability in epilepsy

PURPOSE

Clinical epilepsy drug trials have been measuring increasingly high placebo response rates, up to 40%. This study was designed to examine the relationship between the natural variability in epilepsy, and the placebo response seen in trials. We tested the hypothesis that 'reversing' trial direction, with the baseline period as the treatment observation phase, would reveal effects of natural variability.

METHOD

Clinical trial simulations were run with time running forward and in reverse. Data sources were: SeizureTracker.com (patient reported diaries), a randomized sham-controlled TMS trial, and chronically implanted intracranial EEG electrodes. Outcomes were 50%-responder rates (RR50) and median percentage change (MPC).

RESULTS

The RR50 results showed evidence that temporal reversal does not prevent large responder rates across datasets. The MPC results negative in the TMS dataset, and positive in the other two.

CONCLUSIONS

Typical RR50s of clinical trials can be reproduced using the natural variability of epilepsy as a substrate across multiple datasets. Therefore, the placebo response in epilepsy clinical trials may be attributable almost entirely to this variability, rather than the "placebo effect".

Does accounting for seizure frequency variability increase clinical trial power?

OBJECTIVE

Seizure frequency variability is associated with placebo responses in randomized controlled trials (RCT). Increased variability can result in drug misclassification and, hence, decreased statistical power. We investigated a new method that directly incorporated variability into RCT analysis, Z_V.

METHODS

Two models were assessed: the traditional 50%-responder rate (RR50), and the variability-corrected score, Z_V. Each predicted seizure frequency upper and lower limits using prior seizures. Accuracy was defined as percentage of time-intervals when the observed seizure frequencies were within the predicted limits. First, we tested the Z_V method on three datasets (SeizureTracker: n=3016, Human Epilepsy Project: n=107, and NeuroVista: n=15). An additional independent SeizureTracker validation dataset was used to generate a set of 200 simulated trials each for 5 different sample sizes (total N=100 to 500 by 100), assuming 20% dropout and 30% drug efficacy. "Power" was determined as the percentage of trials successfully distinguishing placebo from drug (p<0.05).

RESULTS

Prediction accuracy across datasets was, Z_V: 91-100%, RR50: 42-80%. Simulated RCT Z_V analysis achieved >90% power at N=100 per arm while RR50 required N=200 per arm.

SIGNIFICANCE

Z_V may increase the statistical power of an RCT relative to the traditional RR50.

Monte Carlo simulations of randomized clinical trials in epilepsy

Background

The placebo response in epilepsy randomized clinical trials (RCTs) has recently been shown to largely reflect underlying natural variability in seizure frequency. Based on this observation, we sought to explore the parameter space of RCT design to optimize trial efficiency and cost.

Methods

We used one of the world's largest patient reported seizure diary databases, SeizureTracker.com to derive virtual patients for simulated RCTs. We ran 1000 randomly generated simulated trials using bootstrapping (sampling with replacement) for each unique combination of trial parameters, sweeping a large set of parameters in durations of the baseline and test periods, number of patients, eligibility criteria, drug effect size, and patient dropout. We studied the resulting trial efficiency and cost.

Results

A total of 6,732,000 trials were simulated, drawing from 5097 patients in the database. We found that the strongest regression predictors of placebo response were durations of baseline and test periods. Drug effect size had a major impact on trial efficiency and cost. Dropout did not have a major impact on trial efficiency or cost. Eligibility requirements impacted trial efficiency to a limited extent. Cost was minimized while maintaining statistical integrity with very short RCT durations.

Discussion

This study suggests that RCT parameters can be improved over current practice to reduce costs while maintaining statistical power. In addition, use of a large‐scale population dataset in a massively parallel computing analysis allows exploration of the wider parameter space of RCT design prior to running a trial, which could help accelerate drug discovery and approval.

A big data approach to the development of mixed-effects models for seizure count data

OBJECTIVE

Our objective was to develop a generalized linear mixed model for predicting seizure count that is useful in the design and analysis of clinical trials. This model also may benefit the design and interpretation of seizure-recording paradigms. Most existing seizure count models do not include children, and there is currently no consensus regarding the most suitable model that can be applied to children and adults. Therefore, an additional objective was to develop a model that accounts for both adult and pediatric epilepsy.

METHODS

Using data from SeizureTracker.com, a patient-reported seizure diary tool with >1.2 million recorded seizures across 8 years, we evaluated the appropriateness of Poisson, negative binomial, zero-inflated negative binomial, and modified negative binomial models for seizure count data based on minimization of the Bayesian information criterion. Generalized linear mixed-effects models were used to account for demographic and etiologic covariates and for autocorrelation structure. Holdout cross-validation was used to evaluate predictive accuracy in simulating seizure frequencies.

RESULTS

For both adults and children, we found that a negative binomial model with autocorrelation over 1 day was optimal. Using holdout cross-validation, the proposed model was found to provide accurate simulation of seizure counts for patients with up to four seizures per day.

SIGNIFICANCE

The optimal model can be used to generate more realistic simulated patient data with very few input parameters. The availability of a parsimonious, realistic virtual patient model can be of great utility in simulations of phase II/III clinical trials, epilepsy monitoring units, outpatient biosensors, and mobile Health (mHealth) applications.

Simulating Clinical Trials With and Without Intracranial EEG Data

OBJECTIVE

It is currently unknown if knowledge of clinically silent (electrographic) seizures improves the statistical efficiency of clinical trials.

METHODS

Using data obtained from 10 patients with chronically implanted subdural electrodes over an average of 1 year, a Monte Carlo bootstrapping simulation study was performed to estimate the statistical power of running a clinical trial based on A) patient reported seizures with intracranial EEG (icEEG) confirmation, B) all patient reported events, or C) all icEEG confirmed seizures. A "drug" was modeled as having 10%, 20%, 30%, 40% and 50% efficacy in 1000 simulated trials each. Outcomes were represented as percentage of trials that achieved p<0.05 using Fisher Exact test for 50%-responder rates (RR50), and Wilcoxon Rank Sum test for median percentage change (MPC).

RESULTS

At each simulated drug strength, the MPC method showed higher power than RR50. As drug strength increased, statistical power increased. For all cases except RR50 with drug of 10% efficacy, using patient reported events (with or without icEEG confirmation) was not as statistically powerful as using all available intracranially confirmed seizures (p<0.001).

SIGNIFICANCE

This study demonstrated using simulation that additional accuracy in seizure detection using chronically implanted icEEG improves statistical power of clinical trials. Newer invasive and noninvasive seizure detection devices may have the potential to provide greater statistical efficiency, accelerate drug discovery and lower trial costs.

Not all that glitters is gold: A guide to the critical interpretation of drug trials in epilepsy

Clinical trials represent the best source of evidence on which to base treatment decisions. For such evidence to be utilized meaningfully, however, it is essential that results are interpreted correctly. This requires a good understanding of strengths and weaknesses of the adopted design, the clinical relevance of the outcome measures, and the many factors that could affect such outcomes. As a general rule, uncontrolled studies tend to provide misleading evidence as a result of the impact of confounders such as regression to the mean, patient‐related bias, and observer bias. On the other hand, although randomized controlled trials (RCTs) are qualitatively superior, aspects of their execution may still decrease their validity. Bias and decreased validity in RCTs may occur by chance alone (for example, treatment groups may not necessarily be balanced for important variables despite randomization) or because of specific features of the trial design. In the case of industry‐driven studies, bias often influences the outcome in favor of the sponsor's product. Factors that need to be carefully scrutinized include (1) the purpose for which the trial is conducted; (2) potential bias due to unblinding or lack of blinding; (3) the appropriateness of the control group; (4) the power of the study in detecting clinically relevant differences; (5) the extent to which eligibility criteria could affect outcomes and be representative of routine clinical practice; (6) whether the treatments being compared are used optimally in terms of dosing, duration of treatment, and other variables; (7) the appropriateness of the statistical comparisons; (8) the clinical relevance of the outcome measures and whether all key outcome information is reported (for example, responder rates in completers); and (9) potential bias in the way results are presented and discussed. This article discusses each of these aspects and illustrates the discussion with examples taken from published antiepileptic drug trials.

Schizophrenia Pharmacology: Past, Present, and Future Targets for Intervention

The first medication for schizophrenia was discovered serendipitously. Years later, it was shown that the medication worked by blocking dopamine, and to this date, all available antipsychotic medications also work by blocking dopamine. They differ, however, in many other respects. The so-called first-generation medications have a wide range of receptor affinities, but in all cases, they have a higher affinity for dopamine receptors than for serotonin receptors. In contrast, so-called second-generation medications have a higher affinity for serotonin receptors than for dopamine receptors. A third category of medication acts as a partial agonist at the dopamine receptor. It is likely that a fourth category will also become available and these medications will act as agonists at the N-methyl-d-aspartate receptor, although clinical trials thus far have struggled to demonstrate efficacy. In addition to medications that treat symptoms of psychosis, medications are under development to directly target some of the more fundamental aspects of cognition that are impaired in schizophrenia, including memory, sensory processing, attention, and executive function. Several promising strategies are discussed.

Incorporating Natural Products, Pharmaceutical Drugs, Self-Care and Digital/Mobile Health Technologies into Molecular-Behavioral Combination Therapies for Chronic Diseases

Merging pharmaceutical and digital (mobile health, mHealth) ingredients to create new therapies for chronic diseases offers unique opportunities for natural products such as omega-3 polyunsaturated fatty acids (n-3 PUFA), curcumin, resveratrol, theanine, or α-lipoic acid. These compounds, when combined with pharmaceutical drugs, show improved efficacy and safety in preclinical and clinical studies of epilepsy, neuropathic pain, osteoarthritis, depression, schizophrenia, diabetes and cancer. Their additional clinical benefits include reducing levels of TNFα and other inflammatory cytokines. We describe how pleiotropic natural products can be developed as bioactive incentives within the network pharmacology together with pharmaceutical drugs and self-care interventions. Since approximately 50% of chronically-ill patients do not take pharmaceutical drugs as prescribed, psychobehavioral incentives may appeal to patients at risk for medication non-adherence. For epilepsy, the incentive-based network therapy comprises anticonvulsant drugs, antiseizure natural products (n-3 PUFA, curcumin or/and resveratrol) coupled with disease-specific behavioral interventions delivered by mobile medical apps. The add-on combination of antiseizure natural products and mHealth supports patient empowerment and intrinsic motivation by having a choice in self-care behaviors. The incentivized therapies offer opportunities: (1) to improve clinical efficacy and safety of existing drugs, (2) to catalyze patient-centered, disease self-management and behavior-changing habits, also improving health-related quality-of-life after reaching remission, and (3) merging copyrighted mHealth software with natural products, thus establishing an intellectual property protection of medical treatments comprising the natural products existing in public domain and currently promoted as dietary supplements. Taken together, clinical research on synergies between existing drugs and pleiotropic natural products, and their integration with self-care, music and mHealth, expands precision/personalized medicine strategies for chronic diseases via pharmacological-behavioral combination therapies.