Seizure Risk Forecasting for Epilepsy

(ECLIPSE Trial)

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Insel Gruppe AG, University Hospital Bern

Disqualifiers: Pregnancy, Psychogenic seizures, Cognitive impairment, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to predict the likelihood of seizures in people with epilepsy. Researchers will use a special brain activity monitor to provide daily forecasts about a participant's seizure risk. The goal is to determine if these predictions can assist individuals in their daily lives by offering useful information about their seizure risk. Suitable candidates have epilepsy that doesn't respond to medication, have experienced a seizure in the past year, and use a specific implant (RNS System) for monitoring seizures. Participants must also have internet access at home and be able to track and report their seizures.

As an unphased trial, this study offers a unique opportunity to contribute to innovative research that could enhance daily life for those with epilepsy.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It is best to discuss this with the trial coordinators or your doctor.

What prior data suggests that this method is safe for forecasting seizure risk?

Research has shown that predicting the risk of seizures is generally well-received by users. One study found that people using a seizure forecasting app had positive experiences. They found the app helpful in managing their condition and noticed improvements in their mood and adjustment to living with epilepsy. Another study discovered that using wearable devices, which don't require surgery or internal procedures, to predict seizures could help reduce injuries and even save lives. These findings suggest that seizure forecasting methods are safe for people with epilepsy and may offer significant benefits. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the Seizure Risk Forecasting for Epilepsy trial because it explores a novel method for predicting seizures before they happen. Unlike the usual approach that focuses on controlling seizures with medications like antiepileptic drugs, this trial tests the potential of forecasting techniques to inform patients and potentially preemptively manage seizure risk. The experimental IEEG-forecast aims to provide a more informative prediction of seizure risk, which could empower patients with timely information to take preventive measures. This proactive forecasting could transform epilepsy management by reducing the unpredictability of seizures and improving quality of life for those affected.

What evidence suggests that this trial's seizure risk forecasting methods could be effective for epilepsy?

Research has shown that special computer programs can predict when seizures might occur, reducing the unpredictability and risk of living with epilepsy. In this trial, participants will join different arms to evaluate the effectiveness of seizure risk forecasting. One arm will receive a potentially informative seizure forecast using patterns from implanted devices, which previous studies have shown can predict seizures days in advance. Another arm will receive an uninformative control seizure forecast. These predictions can help people plan their daily activities better, potentially enhancing safety and improving the well-being of those with epilepsy. ^{2 6 7 8 9}

Who Is on the Research Team?

Maxime O Baud, MD, PhD

Principal Investigator

Department of Neurology, Inselspital Bern

Are You a Good Fit for This Trial?

This trial is for adults with hard-to-treat epilepsy who've had at least one seizure in the past year. They must have internet at home, a specific brain activity monitoring device already implanted, and be able to keep a diary of seizures. People can't join if they have drug or alcohol addiction, are pregnant, have certain other health problems, or can't use the monitoring device properly.

Inclusion Criteria

Home equipped with an internet connection

Informed Consent signed by the subject

Patients previously implanted with the RNS System, on stable detection settings enabling reliable detection of electrographic seizures

Exclusion Criteria

Insufficient number of electrographic seizures or insufficient forecasting performance in the training phase

Drug or alcohol addiction

I am not pregnant at the start of the trial.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Covert Phase

Participants receive double-blinded IEEG forecasts to evaluate performance against electrographic seizures

6-12 months

Overt Phase

Participants receive open-label forecasts to assess informativity and actionability

6-12 months

Withdrawal Phase

Participants experience a withdrawal of forecast information to assess changes in seizure management

3-6 months

Follow-up

Participants are monitored for safety and effectiveness after treatment

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

• Control seizure risk forecast
• Seizure risk forecast

Trial Overview The ECLIPSE trial tests new methods that predict daily seizure risks using data from an implanted brain activity monitor. Participants will receive these predictions to see how well they match actual seizures and whether this information helps them manage their condition better in everyday life.

How Is the Trial Designed?

Group I: IEEG-forecast Experimental Treatment 1 Intervention

Potentially informative seizure forecast.

Group II: Control-forecast Active Control 1 Intervention

Uninformative control seizure forecast.

Who Is Running the Clinical Trial?

Insel Gruppe AG, University Hospital Bern

Lead Sponsor

Trials

831

Recruited

2,353,000+

University of California, San Francisco

Collaborator

Trials

2,636

Recruited

19,080,000+

Published Research Related to This Trial

The Spanish version of the Liverpool Adverse Events Profile (LAEP) was validated in a study involving 266 patients with epilepsy, demonstrating strong internal consistency (Cronbach's alpha=0.84) and test-retest reliability (ICC=0.81).

The LAEP effectively correlated with other established measures of quality of life and mental health, indicating its usefulness in assessing adverse events in Spanish-speaking epilepsy patients.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Validation of the Spanish version of the Liverpool Adverse Events Profile in patients with epilepsy. Carreño, M., Donaire, A., Falip, M., et al.[2022]

In a study of 355 patients on chronic antiepileptic drugs followed for an average of 11 months, 41.6% experienced adverse drug reactions (ADRs), but the frequency of reports decreased over time, indicating improved management of side effects.

The percentage of patients who became seizure-free increased significantly from 24.5% to 42.8%, suggesting that intensive monitoring of ADRs not only helps in identifying drug toxicity but also contributes to better overall epilepsy management.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Adverse reactions to antiepileptic drugs: a follow-up study of 355 patients with chronic antiepileptic drug treatment. Collaborative Group for Epidemiology of Epilepsy. [2019]

Citations

1. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC7935496/

Evaluation and recommendations for effective data ... Seizure forecasting algorithms have become increasingly accurate and may reduce the morbidity and mortality caused by seizure unpredictability.

2. sciencedirect.com sciencedirect.com/science/article/pii/S1525505024002579

User experience of a seizure risk forecasting app This study reports on user experiences and perspectives of a seizure risk forecaster app, as well as the potential impact on mood and adjustment to epilepsy.

3. neurology.org neurology.org/doi/10.1212/WNL.0000000000209621

Seizure Assessment and Forecasting With Efficient Rapid- ... This study provides Class II evidence that rrEEG is noninferior to cEEG in calculating the 2HELPS2B score to predict seizure risk.

4. nature.com nature.com/articles/s41598-024-56827-3

High-performance prediction of epilepsy surgical outcomes ... This study suggests that the hybrid iEEG marker can improve the performance of model predicting the epilepsy surgical outcomes.

5. thelancet.com thelancet.com/journals/laneur/article/PIIS1474-4422(20)30396-3/abstract

Forecasting seizure risk in adults with focal epilepsy This study shows that seizure probability can be forecasted days in advance by leveraging multidien IEA cycles recorded with an implanted device ...

6. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC11269262/

The present and future of seizure detection, prediction, and ... Seizure forecasting aims to identify when a person has a high or low likelihood of seizure, which is related to seizure prediction. Machine ...

7. thelancet.com thelancet.com/journals/ebiom/article/PIIS2352-3964(23)00221-9/fulltext

Forecasting seizure likelihood from cycles of self-reported ... Seizure risk forecasting could reduce injuries and even deaths in people with epilepsy. There is great interest in using non-invasive wearable ...

8. nature.com nature.com/articles/s41598-024-56019-z

Comparison between epileptic seizure prediction and ... The present work aims to explore methodologies capable of seizure forecasting and establish a comparison with seizure prediction results.

9. onlinelibrary.wiley.com onlinelibrary.wiley.com/doi/10.1111/epi.18518?af=R

Seizure forecasting by tracking cortical response to ... The results from this pilot study suggest that seizure forecasting by monitoring the cortical response to electrical stimulation is feasible.