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Early detection rate changes from a brain-responsive neurostimulation system predict efficacy of newly added antiseizure drugs.

ABSTRACT: OBJECTIVE:Brain-responsive neurostimulation (RNS System, NeuroPace) is used to treat medically refractory focal epilepsy and also provides long-term ambulatory neurophysiologic data. We sought to determine whether these data could predict the clinical response to antiseizure drugs (ASDs). METHODS:First, newly added medications were identified in RNS System patients followed at a single epilepsy center. Daily detection rates including "episode starts" (predominantly interictal activity) and "long episodes" (often electrographic seizures) were compared before and after ASD initiation. Efficacy was determined from documentation of clinical improvement and medication retention. Next, the analysis was repeated on an independent sample of patients from a multicenter long-term treatment trial, using an efficacy measure of ?50% reduction in diary-recorded seizure frequency after 3 months. RESULTS:In the single center cohort, long episodes, but not episode starts, had a significantly greater reduction in the first week for clinically efficacious compared to inefficacious medications. In this cohort, having no long episodes in the first week was highly predictive of ASD efficacy. In the multicenter cohort, both long episodes and episode starts had a significantly greater reduction for effective medications starting in the first 1-2 weeks. In this larger dataset, a ?50% decrease in episode starts was 90% specific for efficacy with a positive predictive value (PPV) of 67%, and a ?84% decrease in long episodes was 80% specific with a PPV of 48%. Conversely, a <25% decrease in long episodes (including any increase) or a <20% decrease in episode starts had a predictive value for inefficacy of >80%. SIGNIFICANCE:In RNS System patients with stable detection settings, when new ASDs are started, detection rates within the first 1-2 weeks may provide an early, objective indication of efficacy. These data could be used to identify responses to medication trials early to allow more rapid medication adjustments than conventionally possible.

SUBMITTER: Quraishi IH

PROVIDER: S-EPMC7003822 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Early detection rate changes from a brain-responsive neurostimulation system predict efficacy of newly added antiseizure drugs.

Quraishi Imran H IH Mercier Michael R MR Skarpaas Tara L TL Hirsch Lawrence J LJ

Epilepsia 20191217 1

<h4>Objective</h4>Brain-responsive neurostimulation (RNS System, NeuroPace) is used to treat medically refractory focal epilepsy and also provides long-term ambulatory neurophysiologic data. We sought to determine whether these data could predict the clinical response to antiseizure drugs (ASDs).<h4>Methods</h4>First, newly added medications were identified in RNS System patients followed at a single epilepsy center. Daily detection rates including "episode starts" (predominantly interictal acti ...[more]

PMID: 31849045

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Project description:Drug-resistant epilepsy occurs in 25-30% of patients. Furthermore, treatment with a first-generation antiseizure drug (ASD) fails in 30-40% of individuals because of their intolerable adverse effects. Over the past three decades, 20 newer- (second- and third-)generation ASDs with unique mechanisms of action and pharmacokinetic profiles have been introduced into clinical practice. This advent has expanded the therapeutic armamentarium of epilepsy and broadens the choices of ASDs to match the individual patient's characteristics. In recent years, research has been focused on defining the ASD of choice for different seizure types. In 2017, the International League Against Epilepsy published a new classification for seizure types and epilepsy syndrome. This classification has been of paramount importance to accurately classify the patient's seizure type(s) and prescribe the ASD that is appropriate. A year later, the American Academy of Neurology published a new guideline for ASD selection in adult and pediatric patients with new-onset and treatment-resistant epilepsy. The guideline primarily relied on studies that compare the first-generation and second-generation ASDs, with limited data for the efficacy of third-generation drugs. While researchers have been called for investigating those drugs in future research, epilepsy specialists may wish to share their personal experiences to support the treatment guidelines. Given the rapid advances in the development of ASDs in recent years and the continuous updates in definitions, classifications, and treatment guidelines for seizure types and epilepsy syndromes, this review aims to present a complete overview of the current state of the literature about the efficacy and tolerability of ASDs and provide guidance to clinicians about selecting appropriate ASDs for initial treatment of epilepsy according to different seizure types and epilepsy syndromes based on the current literature and recent US and UK practical guidelines.

Project description:ImportanceTolerability is a key determinant of the effectiveness of epilepsy treatment. It is important to evaluate whether the overall tolerability has improved.ObjectiveTo identify factors associated with poor tolerability of antiseizure medications (ASMs) and examine temporal changes in tolerability.Design, setting, and participantsThis was a longitudinal cohort study at a specialist clinic in Glasgow, Scotland. Patients with newly diagnosed and treated epilepsy between July 1982 and October 2012 were included from 2282 eligible individuals. They were followed up until April 2016 or death. Data analysis was completed in August 2019.ExposuresAntiseizure medications.Main outcomes and measuresUnivariable and multivariable survival analyses were performed to examine associations between potential risk factors and development of intolerable adverse effects (AEs). Intolerable AE rates of the ASMs as the initial monotherapy were compared between 3 epochs (July 1982-June 1992, July 1992-June 2002, and July 2002-April 2016).ResultsOf 1795 patients, 969 (54.0%) were male, and the median (interquartile range) age was 33 (21-50) years. A total of 3241 ASMs were prescribed during the period, of which 504 (15.6%) were discontinued within 6 months owing to intolerable AEs. Children younger than 18 years had lower intolerable AE rates than adults (vs aged 18-64 years: adjusted hazard ratio [aHR], 1.58; 95% CI, 1.07-2.32; vs aged ≥65 years: aHR, 1.90; 95% CI, 1.19-3.02) while female individuals (aHR, 1.60; 95% CI, 1.30-1.96) and those who had more than 5 pretreatment seizures (aHR, 1.24; 95% CI, 1.03-1.49) were associated with having higher risk. For each ASM trial, the risk of intolerable AEs increased with the number of previous drug withdrawals due to AEs (aHR, 1.18; 95% CI, 1.09-1.28) and the number of concomitant ASMs (aHR, 1.31; 95% CI, 1.04-1.64). The proportion of second-generation ASMs prescribed as the initial monotherapy increased from 22.3% (33 of 148) in the first epoch to 68.7% (645 of 939) in the last (P < .001). Although differences in intolerable AE rates and types of AEs were found between the ASMs, there was no difference in the overall intolerable AEs rates to the initial monotherapy across the 3 epochs (first: 10.1% [15 of 148]; second: 13.8% [98 of 708]; third: 14.0% [131 of 939]; P = .41).Conclusions and relevanceIn this cohort study, the increased use of the second-generation ASMs had not improved overall treatment tolerability. Greater effort to improve tolerability in ASM development is needed.

Project description:Responsive neurostimulation is a promising treatment for drug-resistant focal epilepsy; however, clinical outcomes are highly variable across individuals. The therapeutic mechanism of responsive neurostimulation likely involves modulatory effects on brain networks; however, with no known biomarkers that predict clinical response, patient selection remains empiric. This study aimed to determine whether functional brain connectivity measured non-invasively prior to device implantation predicts clinical response to responsive neurostimulation therapy. Resting-state magnetoencephalography was obtained in 31 participants with subsequent responsive neurostimulation device implantation between 15 August 2014 and 1 October 2020. Functional connectivity was computed across multiple spatial scales (global, hemispheric, and lobar) using pre-implantation magnetoencephalography and normalized to maps of healthy controls. Normalized functional connectivity was investigated as a predictor of clinical response, defined as percent change in self-reported seizure frequency in the most recent year of clinic visits relative to pre-responsive neurostimulation baseline. Area under the receiver operating characteristic curve quantified the performance of functional connectivity in predicting responders (≥50% reduction in seizure frequency) and non-responders (<50%). Leave-one-out cross-validation was furthermore performed to characterize model performance. The relationship between seizure frequency reduction and frequency-specific functional connectivity was further assessed as a continuous measure. Across participants, stimulation was enabled for a median duration of 52.2 (interquartile range, 27.0-62.3) months. Demographics, seizure characteristics, and responsive neurostimulation lead configurations were matched across 22 responders and 9 non-responders. Global functional connectivity in the alpha and beta bands were lower in non-responders as compared with responders (alpha, pfdr < 0.001; beta, pfdr < 0.001). The classification of responsive neurostimulation outcome was improved by combining feature inputs; the best model incorporated four features (i.e. mean and dispersion of alpha and beta bands) and yielded an area under the receiver operating characteristic curve of 0.970 (0.919-1.00). The leave-one-out cross-validation analysis of this four-feature model yielded a sensitivity of 86.3%, specificity of 77.8%, positive predictive value of 90.5%, and negative predictive value of 70%. Global functional connectivity in alpha band correlated with seizure frequency reduction (alpha, P = 0.010). Global functional connectivity predicted responder status more strongly, as compared with hemispheric predictors. Lobar functional connectivity was not a predictor. These findings suggest that non-invasive functional connectivity may be a candidate personalized biomarker that has the potential to predict responsive neurostimulation effectiveness and to identify patients most likely to benefit from responsive neurostimulation therapy. Follow-up large-cohort, prospective studies are required to validate this biomarker. These findings furthermore support an emerging view that the therapeutic mechanism of responsive neurostimulation involves network-level effects in the brain.

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Early detection rate changes from a brain-responsive neurostimulation system predict efficacy of newly added antiseizure drugs.

Publications

Early detection rate changes from a brain-responsive neurostimulation system predict efficacy of newly added antiseizure drugs.

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