Dataset Information

Impact of timing of antiseizure medication withdrawal on seizure recurrence in glioma patients: a retrospective observational study.

ABSTRACT:

Background

Withdrawal of antiseizure medication treatment (ASM) can be considered after completion of antitumour treatment in glioma patients who no longer suffer from seizures. We compared the risk for recurrent seizures after ASM withdrawal between patients with short-term, medium-term versus long-term seizure freedom after antitumour treatment.

Methods

In this retrospective observational study, the primary outcome was time to recurrent seizure, from the starting date of no ASM treatment up to 36 months follow-up. Cox proportional hazards models were used to study the effect of risk factors on time to recurrent seizure. Stratification was done with information known at baseline. Short-term seizure freedom was defined as ≥ 3 months, but < 12 months; medium-term as 12-24 months; and long-term as ≥ 24 months seizure freedom from the date of last antitumour treatment.

Results

This study comprised of 109 patients; 31% (34/109) were in the short-term, 29% (32/109) in the medium-term, and 39% (43/109) in the long-term group. A recurrent seizure was experienced by 47% (16/34) of the patients in the short-term, 31% (10/32) in the medium-term, and 44% (19/43) in the long-term group. Seizure recurrence risk was similar between patients in the short-term group as compared to the medium-term (cause-specific adjusted hazard ratio [aHR] = 0.65 [95%CI = 0.29-1.46]) and long-term group (cause-specific aHR = 1.04 [95%CI = 0.52-2.09]).

Conclusions

Seizure recurrence risk is relatively similar between patients with short-term, medium-term, and long-term seizure freedom after completion of antitumour treatment.

SUBMITTER: van der Meer PB

PROVIDER: S-EPMC10589365 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Publications

Impact of timing of antiseizure medication withdrawal on seizure recurrence in glioma patients: a retrospective observational study.

van der Meer Pim B PB Dirven Linda L Fiocco Marta M Vos Maaike J MJ Kerkhof Melissa M Kouwenhoven Mathilde C M MCM van den Bent Martin J MJ Taphoorn Martin J B MJB Koekkoek Johan A F JAF

Journal of neuro-oncology 20230927 3

<h4>Background</h4>Withdrawal of antiseizure medication treatment (ASM) can be considered after completion of antitumour treatment in glioma patients who no longer suffer from seizures. We compared the risk for recurrent seizures after ASM withdrawal between patients with short-term, medium-term versus long-term seizure freedom after antitumour treatment.<h4>Methods</h4>In this retrospective observational study, the primary outcome was time to recurrent seizure, from the starting date of no ASM ...[more]

PMID: 37755633

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Project description:ObjectiveGuidelines suggest considering antiseizure medication (ASM) discontinuation in seizure-free patients with epilepsy. Past work has poorly explored how discontinuation effects vary between patients. We evaluated (1) what factors modify the influence of discontinuation on seizure risk; and (2) the range of seizure risk increase due to discontinuation across low- versus high-risk patients.MethodsWe pooled three datasets including seizure-free patients who did and did not discontinue ASMs. We conducted time-to-first-seizure analyses. First, we evaluated what individual patient factors modified the relative effect of ASM discontinuation on seizure risk via interaction terms. Then, we assessed the distribution of 2-year risk increase as predicted by our adjusted logistic regressions.ResultsWe included 1626 patients, of whom 678 (42%) planned to discontinue all ASMs. The mean predicted 2-year seizure risk was 43% [95% confidence interval (CI) 39%-46%] for discontinuation versus 21% (95% CI 19%-24%) for continuation. The mean 2-year absolute seizure risk increase was 21% (95% CI 18%-26%). No individual interaction term was significant after correcting for multiple comparisons. The median [interquartile range (IQR)] risk increase across patients was 19% (IQR 14%-24%; range 7%-37%). Results were unchanged when restricting analyses to only the two RCTs.SignificanceNo single patient factor significantly modified the influence of discontinuation on seizure risk, although we captured how absolute risk increases change for patients that are at low versus high risk. Patients should likely continue ASMs if even a 7% 2-year increase in the chance of any more seizures would be too much and should likely discontinue ASMs if even a 37% risk increase would be too little. In between these extremes, individualized risk calculation and a careful understanding of patient preferences are critical. Future work will further develop a two-armed individualized seizure risk calculator and contextualize seizure risk thresholds below which to consider discontinuation.Plain language summaryUnderstanding how much antiseizure medications (ASMs) decrease seizure risk is an important part of determining which patients with epilepsy should be treated, especially for patients who have not had a seizure in a while. We found that there was a wide range in the amount that ASM discontinuation increases seizure risk-between 7% and 37%. We found that no single patient factor modified that amount. Understanding what a patient's seizure risk might be if they discontinued versus continued ASM treatment is critical to making informed decisions about whether the benefit of treatment outweighs the downsides.

Project description:Objective This study aimed to examine the epidemiology of seizures, clinical outcomes, and antiseizure medication treatment patterns among seizure patients treated in United States hospitals. Design A retrospective cross-sectional study was conducted using data from a large geographically diverse hospital discharge database. Setting 860 acute care hospitals in the United States. Participants Patients aged ≥18 years with an outpatient emergency department or inpatient visit between 1 July 2016–31 December 2019 were included. Intervention None. Main outcomes and measures Key outcomes included prevalence of seizure, seizure type, admission point of origin, intensive care unit admission, discharge status, and injectable antiseizure medication utilization. Seizures were identified by the International Classification of Disease, Tenth Revision, Clinical Modification diagnosis codes. Results Among 36,598,627 unique emergency department outpatients (72,372,464 outpatient visits) and 16,543,592 unique inpatients (24,923,489 inpatient admissions) analyzed, seizure was present in 2.1% of outpatients (1.87% of outpatient visits) and 4.9% of inpatients (4.8% of inpatient admissions). In overall seizure patients, 49.1% were unclassified, 4.4% had generalized onset, 2.9% had focal onset, and 42.8% were categorized as other (including 38.5% with convulsion). Among seizure-associated inpatient admissions, <1% were transferred directly from skilled nursing facility or other long-term care facilities but 22.7% were discharged to such facilities. Nearly a third (31%) of all inpatients were admitted to ICU. About 88.3% of patients with injectable ASM use had monotherapy, 4.6% had polytherapy with 1 day or multiple non-consecutive days of overlap, and 7.0% had polytherapy with ≥2 consecutive days of overlap. The percentage of patients with no step down to any oral ASM ranged between 34.0–57.0%. Conclusions Seizures affect a substantial number of hospital-based emergency department outpatient and inpatient encounters and are associated with poor clinical outcomes and significant healthcare burden. Concomitant use of injectable ASMs is uncommon and a high percentage of IV ASM users with a diagnosis of seizure had no step down to oral therapy. Relevance The study findings may inform clinicians and hospital decision makers about current clinical practice and burden of seizures and identify areas to improve overall outcomes for patients with seizures.

Project description:Background and objectiveStatus epilepticus in poststroke epilepsy is a challenging condition because of multiple vascular comorbidities and the advanced age of patients. Data on third-generation antiseizure medication (ASM) in this condition are limited. The aim of this study was to evaluate the efficacy of third-generation ASMs in the second- or third-line therapy of benzodiazepine-refractory status epilepticus in poststroke epilepsy following acute ischemic stroke.MethodsData on the effectiveness of third-generation ASMs in patients with status epilepticus in poststroke epilepsy were gathered from two German Stroke Registries and the Mainz Epilepsy Registry. We included only cases with epilepsy remote to the ischemic event. No patients with acute symptomatic seizures were included. The following third-generation ASMs were included: brivaracetam, lacosamide, eslicarbazepine, perampanel, topiramate, and zonisamide. The assessment of effectiveness was based on seizure freedom within 48 h since the start of therapy with the respective ASM. Seizure freedom was evaluated both clinically (clinical evaluation at least three times per day) and by daily electroencephalogram records.ResultsOf the 138 patients aged 70.8 ± 8.1 years with benzodiazepine-refractory status epilepticus in ischemic poststroke epilepsy, 33 (23.9%) were treated with lacosamide, 24 (17.4%) with brivaracetam, 23 (16.7%) with eslicarbazepine, 21 (15.2%) with perampanel, 20 (14.5%) with topiramate, and 17 (12.3%) with zonisamide. Seizure freedom within 48 h was achieved in 66.7% of patients with lacosamide, 65.2% with eslicarbazepine, 38.1% with perampanel, 37.5% with brivaracetam, 35.0% with topiramate, and 35.3% with zonisamide (p < 0.05 for comparison of lacosamide or eslicarbazepine to other ASMs).ConclusionsBased on these data, lacosamide and eslicarbazepine might be more favorable in the treatment of refractory status epilepticus in poststroke epilepsy, when administered as second- or third-line ASMs before anesthesia. Because of the fact that these ASMs share the same mechanism of action (slow inactivation of sodium channels), our findings could motivate further research on the role that this pharmaceutical mechanism of action has in the treatment of poststroke epilepsy.Clinical trial registrationThis study was registered at ClinicalTrials.gov (NCT05267405).

Project description:ObjectiveChoosing candidates for antiseizure medication (ASM) withdrawal in well-controlled epilepsy is challenging. We evaluated (a) the correlation between neurologists' seizure risk estimation ("clinician predictions") vs calculated predictions, (b) how viewing calculated predictions influenced recommendations, and (c) barriers to using risk calculation.MethodsWe asked US and European neurologists to predict 2-year seizure risk after ASM withdrawal for hypothetical vignettes. We compared ASM withdrawal recommendations before vs after viewing calculated predictions, using generalized linear models.ResultsThree-hundred and forty-six neurologists responded. There was moderate correlation between clinician and calculated predictions (Spearman coefficient 0.42). Clinician predictions varied widely, for example, predictions ranged 5%-100% for a 2-year seizure-free adult without epileptiform abnormalities. Mean clinician predictions exceeded calculated predictions for vignettes with epileptiform abnormalities (eg, childhood absence epilepsy: clinician 65%, 95% confidence interval [CI] 57%-74%; calculated 46%) and surgical vignettes (eg, focal cortical dysplasia 6-month seizure-free mean clinician 56%, 95% CI 52%-60%; calculated 28%). Clinicians overestimated the influence of epileptiform EEG findings on withdrawal risk (26%, 95% CI 24%-28%) compared with calculators (14%, 95% 13%-14%). Viewing calculated predictions slightly reduced willingness to withdraw (-0.8/10 change, 95% CI -1.0 to -0.7), particularly for vignettes without epileptiform abnormalities. The greatest barrier to calculator use was doubting its accuracy (44%).SignificanceClinicians overestimated the influence of abnormal EEGs particularly for low-risk patients and overestimated risk and the influence of seizure-free duration for surgical patients, compared with calculators. These data may question widespread ordering of EEGs or time-based seizure-free thresholds for surgical patients. Viewing calculated predictions reduced willingness to withdraw particularly without epileptiform abnormalities.

Project description:BackgroundA third of people with juvenile myoclonic epilepsy (JME) are drug-resistant. Three-quarters have a seizure relapse when attempting to withdraw anti-seizure medication (ASM) after achieving seizure-freedom. It is currently impossible to predict who is likely to become drug-resistant and safely withdraw treatment. We aimed to identify predictors of drug resistance and seizure recurrence to allow for individualised prediction of treatment outcomes in people with JME.MethodsWe performed an individual participant data (IPD) meta-analysis based on a systematic search in EMBASE and PubMed - last updated on March 11, 2021 - including prospective and retrospective observational studies reporting on treatment outcomes of people diagnosed with JME and available seizure outcome data after a minimum one-year follow-up. We invited authors to share standardised IPD to identify predictors of drug resistance using multivariable logistic regression. We excluded pseudo-resistant individuals. A subset who attempted to withdraw ASM was included in a multivariable proportional hazards analysis on seizure recurrence after ASM withdrawal. The study was registered at the Open Science Framework (OSF; https://osf.io/b9zjc/).FindingsOur search yielded 1641 articles; 53 were eligible, of which the authors of 24 studies agreed to collaborate by sharing IPD. Using data from 2518 people with JME, we found nine independent predictors of drug resistance: three seizure types, psychiatric comorbidities, catamenial epilepsy, epileptiform focality, ethnicity, history of CAE, family history of epilepsy, status epilepticus, and febrile seizures. Internal-external cross-validation of our multivariable model showed an area under the receiver operating characteristic curve of 0·70 (95%CI 0·68-0·72). Recurrence of seizures after ASM withdrawal (n = 368) was predicted by an earlier age at the start of withdrawal, shorter seizure-free interval and more currently used ASMs, resulting in an average internal-external cross-validation concordance-statistic of 0·70 (95%CI 0·68-0·73).InterpretationWe were able to predict and validate clinically relevant personalised treatment outcomes for people with JME. Individualised predictions are accessible as nomograms and web-based tools.FundingMING fonds.

Dataset Information

Impact of timing of antiseizure medication withdrawal on seizure recurrence in glioma patients: a retrospective observational study.

Background

Methods

Results

Conclusions

Publications

Impact of timing of antiseizure medication withdrawal on seizure recurrence in glioma patients: a retrospective observational study.

Similar Datasets

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