Placebo in epilepsy

Demonstration of Group-Level and Individual-Level Efficacy Using Time-to-Event Designs for Clinical Trials of Antiseizure Medications

BACKGROUND AND OBJECTIVES

Participants with treatment-resistant epilepsy who are randomized to add-on placebo and remain in a trial for the typical 3 to 5-month maintenance period may be at increased risk of adverse outcomes. A novel trial design has been suggested, time to prerandomization monthly seizure count (T-PSC), which would limit participants' time on ineffective therapy. We reanalyzed 11 completed trials to determine whether the primary efficacy conclusions at T-PSC matched each of the original, longer trials.

METHODS

A total of 11 double-blind, placebo-controlled trials of levetiracetam, brivaracetam, lacosamide, topiramate, and lamotrigine for either focal-onset or generalized-onset epilepsy were selected. We evaluated the group-level and individual-level efficacy of treatments including the median percent reduction (MPR) in seizure frequency and 50% responder rate (50RR) at T-PSC, time to second seizure, and time to first seizure compared with the full-length trial.

RESULTS

The primary efficacy conclusions of 10 of the 11 trials would have been the same with a T-PSC design compared with the traditional design (the exception of lamotrigine had a very high initial placebo response). As a proportion of the full-length effect size, 90% of the MPR and 85% of the 50RR were seen at T-PSC (95% CI 73%-113% and 65%-110%, respectively). Using the T-PSC design, the time on blinded treatment was at least 312 participant-years shorter (40% of total duration) and 142,000 seizures occurred during this time (60% of total seizures). By contrast, the time to first or second seizure designs reproduced group-level effect size, but the primary efficacy conclusions of each trial and individual-level efficacy correspondence were fair to poor.

DISCUSSION

These results support the use of this trial design for new epilepsy medication trials because this reanalysis of 11 randomized controlled trials demonstrated that observation until T-PSC was sufficient to demonstrate efficacy while potentially improving participant safety by reducing the time of exposure to placebo and inadequate treatment. Despite analysis of 11 trials including 3,619 participants, we did not observe a significant reduction in the group-level effect size, which is directly related to statistical power. The next step is to evaluate whether T-PSC is sufficient to evaluate safety as measured by adverse events.

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.

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.

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.

A suggestive seizure induction technique protocol in a short EEG in children and adolescents

The use of a suggestive seizure induction procedure (SSI) in medicine, particularly in the differential diagnosis of psychogenic nonepileptic epileptic seizures (PNES), is well documented. However, there is no description of standardized suggestion procedures used in children and adolescents. The research presents a standardized method of SSI with a cotton swab soaked in water. The protocol was developed based on of 544 placebo trials over ten years in a center for the differential diagnosis of children and adolescents. The protocol is a safe tool that allows inducing specific behavior in children and adolescents in whom there is a well-founded suspicion of PNES.

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.