Predictive models for starting antiseizure medication withdrawal following epilepsy surgery in adults.

More than half of adults with epilepsy undergoing resective epilepsy surgery achieve long-term seizure freedom and might consider withdrawing antiseizure medications. We aimed to identify predictors of seizure recurrence after starting postoperative antiseizure medication withdrawal and develop and validate predictive models. We performed an international multicentre observational cohort study in nine tertiary epilepsy referral centres. We included 850 adults who started antiseizure medication withdrawal following resective epilepsy surgery and were free of seizures other than focal non-motor aware seizures before starting antiseizure medication withdrawal. We developed a model predicting recurrent seizures, other than focal non-motor aware seizures, using Cox proportional hazards regression in a derivation cohort (n = 231). Independent predictors of seizure recurrence, other than focal non-motor aware seizures, following the start of antiseizure medication withdrawal were focal non-motor aware seizures after surgery and before withdrawal [adjusted hazard ratio (aHR) 5.5, 95% confidence interval (CI) 2.7-11.1], history of focal to bilateral tonic-clonic seizures before surgery (aHR 1.6, 95% CI 0.9-2.8), time from surgery to the start of antiseizure medication withdrawal (aHR 0.9, 95% CI 0.8-0.9) and number of antiseizure medications at time of surgery (aHR 1.2, 95% CI 0.9-1.6). Model discrimination showed a concordance statistic of 0.67 (95% CI 0.63-0.71) in the external validation cohorts (n = 500). A secondary model predicting recurrence of any seizures (including focal non-motor aware seizures) was developed and validated in a subgroup that did not have focal non-motor aware seizures before withdrawal (n = 639), showing a concordance statistic of 0.68 (95% CI 0.64-0.72). Calibration plots indicated high agreement of predicted and observed outcomes for both models. We show that simple algorithms, available as graphical nomograms and online tools (predictepilepsy.github.io), can provide probabilities of seizure outcomes after starting postoperative antiseizure medication withdrawal. These multicentre-validated models may assist clinicians when discussing antiseizure medication withdrawal after surgery with their patients.

Indicators of questionable research practices were identified in 163,129 randomized controlled trials.

OBJECTIVES: To explore indicators of the following questionable research practices (QRPs) in randomized controlled trials (RCTs): (1) risk of bias in four domains (random sequence generation, allocation concealment, blinding of participants and personnel, and blinding of outcome assessment); (2) modifications in primary outcomes that were registered in trial registration records (proxy for selective reporting bias); (3) ratio of the achieved to planned sample sizes; and (4) statistical discrepancy. STUDY DESIGN AND SETTING: Full texts of all human RCTs published in PubMed in 1996-2017 were automatically identified and information was collected automatically. Potential indicators of QRPs included author-specific, publication-specific, and journal-specific characteristics. Beta, logistic, and linear regression models were used to identify associations between these potential indicators and QRPs. RESULTS: We included 163,129 RCT publications. The median probability of bias assessed using Robot Reviewer software ranged between 43% and 63% for the four risk of bias domains. A more recent publication year, trial registration, mentioning of CONsolidated Standards Of Reporting Trials-checklist, and a higher journal impact factor were consistently associated with a lower risk of QRPs. CONCLUSION: This comprehensive analysis provides an insight into indicators of QRPs. Researchers should be aware that certain characteristics of the author team and publication are associated with a higher risk of QRPs.

Individualised prediction of drug resistance and seizure recurrence after medication withdrawal in people with juvenile myoclonic epilepsy: A systematic review and individual participant data meta-analysis.

Background: A 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. Methods: We 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/). Findings: Our 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). Interpretation: We 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. Funding: MING fonds.

Cumulative effects of antiseizure medication on intelligence in children with focal epilepsy

Objective: Antiseizure medication may have long-term effects on the neurodevelopment of children. We aimed to investigate the association between cumulative antiseizure medication load and intelligence quotient (IQ) in relation to brain volume and cortical thickness. Methods: A retrospective analysis of children with focal epilepsy who underwent neuropsychological assessment and MRI between the ages of 5-12 years in a tertiary epilepsy centre was performed. Cumulative medication load was presented in medication years. We studied the association between total medication load and IQ with multivariable linear regression, corrected for epilepsy-related confounders: age at first treatment, aetiology, maximum seizure frequency, duration of active epilepsy, history of secondary generalized seizures, history of status epilepticus, and the number of antiseizure medications used at time of neuropsychological assessment. Results: We included 59 children. Median medication load was 5.3 medication-years (interquartile range: 2.0 ­ 11.1) and mean total IQ (± standard deviation) was 77.4±18.9. A significant negative relation between medication load and total IQ was found with a decrease of 1.2 IQ-points per medication-year (95% confidence interval: -2.0 to -0.3) after correcting for confounders. Medication load and IQ were both not significantly associated with brain volume or cortical thickness. Significance: Higher cumulative medication load is associated with lower total IQ after adjusting for epilepsy-related confounders. We found no evidence to support the hypothesis that the medication-related IQ decrease was mediated by volumetric brain changes. However, these results should be interpreted with caution, and prospective, longitudinal confirmation of these findings is required. Lastly, it should be stressed that effective seizure prevention often outweighs the potential negative effects of antiseizure medication.

The methodological quality of 176,620 randomized controlled trials published between 1966 and 2018 reveals a positive trend but also an urgent need for improvement.

Many randomized controlled trials (RCTs) are biased and difficult to reproduce due to methodological flaws and poor reporting. There is increasing attention for responsible research practices and implementation of reporting guidelines, but whether these efforts have improved the methodological quality of RCTs (e.g., lower risk of bias) is unknown. We, therefore, mapped risk-of-bias trends over time in RCT publications in relation to journal and author characteristics. Meta-information of 176,620 RCTs published between 1966 and 2018 was extracted. The risk-of-bias probability (random sequence generation, allocation concealment, blinding of patients/personnel, and blinding of outcome assessment) was assessed using a risk-of-bias machine learning tool. This tool was simultaneously validated using 63,327 human risk-of-bias assessments obtained from 17,394 RCTs evaluated in the Cochrane Database of Systematic Reviews (CDSR). Moreover, RCT registration and CONSORT Statement reporting were assessed using automated searches. Publication characteristics included the number of authors, journal impact factor (JIF), and medical discipline. The annual number of published RCTs substantially increased over 4 decades, accompanied by increases in authors (5.2 to 7.8) and institutions (2.9 to 4.8). The risk of bias remained present in most RCTs but decreased over time for allocation concealment (63% to 51%), random sequence generation (57% to 36%), and blinding of outcome assessment (58% to 52%). Trial registration (37% to 47%) and the use of the CONSORT Statement (1% to 20%) also rapidly increased. In journals with a higher impact factor (>10), the risk of bias was consistently lower with higher levels of RCT registration and the use of the CONSORT Statement. Automated risk-of-bias predictions had accuracies above 70% for allocation concealment (70.7%), random sequence generation (72.1%), and blinding of patients/personnel (79.8%), but not for blinding of outcome assessment (62.7%). In conclusion, the likelihood of bias in RCTs has generally decreased over the last decades. This optimistic trend may be driven by increased knowledge augmented by mandatory trial registration and more stringent reporting guidelines and journal requirements. Nevertheless, relatively high probabilities of bias remain, particularly in journals with lower impact factors. This emphasizes that further improvement of RCT registration, conduct, and reporting is still urgently needed.

Seizure outcome and use of antiepileptic drugs after epilepsy surgery according to histopathological diagnosis: a retrospective multicentre cohort study.

BACKGROUND: Surgery is a widely accepted treatment option for drug-resistant focal epilepsy. A detailed analysis of longitudinal postoperative seizure outcomes and use of antiepileptic drugs for different brain lesions causing epilepsy is not available. We aimed to analyse the association between histopathology and seizure outcome and drug freedom up to 5 years after epilepsy surgery, to improve presurgical decision making and counselling. METHODS: In this retrospective, multicentre, longitudinal, cohort study, patients who had epilepsy surgery between Jan 1, 2000, and Dec 31, 2012, at 37 collaborating tertiary referral centres across 18 European countries of the European Epilepsy Brain Bank consortium were assessed. We included patients of all ages with histopathology available after epilepsy surgery. Histopathological diagnoses and a minimal dataset of clinical variables were collected from existing local databases and patient records. The primary outcomes were freedom from disabling seizures (Engel class 1) and drug freedom at 1, 2, and 5 years after surgery. Proportions of individuals who were Engel class 1 and drug-free were reported for the 11 main categories of histopathological diagnosis. We analysed the association between histopathology, duration of epilepsy, and age at surgery, and the primary outcomes using random effects multivariable logistic regression to control for confounding. FINDINGS: 9147 patients were included, of whom seizure outcomes were available for 8191 (89·5%) participants at 2 years, and for 5577 (61·0%) at 5 years. The diagnoses of low-grade epilepsy associated neuroepithelial tumour (LEAT), vascular malformation, and hippocampal sclerosis had the best seizure outcome at 2 years after surgery, with 77·5% (1027 of 1325) of patients free from disabling seizures for LEAT, 74·0% (328 of 443) for vascular malformation, and 71·5% (2108 of 2948) for hippocampal sclerosis. The worst seizure outcomes at 2 years were seen for patients with focal cortical dysplasia type I or mild malformation of cortical development (50·0%, 213 of 426 free from disabling seizures), those with malformation of cortical development-other (52·3%, 212 of 405 free from disabling seizures), and for those with no histopathological lesion (53·5%, 396 of 740 free from disabling seizures). The proportion of patients being both Engel class 1 and drug-free was 0-14% at 1 year and increased to 14-51% at 5 years. Children were more often drug-free; temporal lobe surgeries had the best seizure outcomes; and a longer duration of epilepsy was associated with reduced chance of favourable seizure outcomes and drug freedom. This effect of duration was evident for all lesions, except for hippocampal sclerosis. INTERPRETATION: Histopathological diagnosis, age at surgery, and duration of epilepsy are important prognostic factors for outcomes of epilepsy surgery. In every patient with refractory focal epilepsy presumed to be lesional, evaluation for surgery should be considered. FUNDING: None.

A Prediction Model to Determine Childhood Epilepsy After 1 or More Paroxysmal Events.

OBJECTIVES: The clinical profile of children who had possible seizures is heterogeneous, and accuracy of diagnostic testing is limited. We aimed to develop and validate a prediction model that determines the risk of childhood epilepsy by combining available information at first consultation. METHODS: We retrospectively collected data of 451 children who visited our outpatient department for diagnostic workup related to 1 or more paroxysmal event(s). At least 1 year of follow-up was available for all children who were diagnosed with epilepsy or in whom diagnosis remained inconclusive. Clinical characteristics (sex, age of first seizure, event description, medical history) and EEG report were used as predictor variables for building a multivariate logistic regression model. Performance was validated in an external cohort (n = 187). RESULTS: Model discrimination was excellent, with an area under the receiver operating characteristic curve of 0.86 (95% confidence interval [CI]; 0.80-0.92), a positive predictive value of 0.93 (95% CI 0.83-0.97) and a negative predictive value of 0.76 (95% CI 0.70-0.80). Model discrimination in a selective subpopulation of children with uncertain diagnosis after initial clinical workup was good, with an area under the receiver operating characteristic curve of 0.73 (95% CI 0.58-0.87). CONCLUSIONS: This model may prove to be valuable because predictor variables together with a first interictal EEG can be available at first consultation. A Web application is provided (http://epilepsypredictiontools.info/first-consultation) to facilitate the diagnostic process for clinicians who are confronted with children with paroxysmal events, suspected of having an epileptic origin.

Why the TimeToStop trial failed to recruit: a survey on antiepileptic drug withdrawal after paediatric epilepsy surgery.

Following the results of the multicentre European retrospective "TimeToStop" cohort study, we initiated a randomised trial to determine cognitive benefits of early postoperative antiepileptic drug withdrawal. Unfortunately, the trial failed to recruit and was terminated, as almost all parents preferred early drug withdrawal. The objectives of the current survey were to obtain insight into current practices regarding drug withdrawal after paediatric epilepsy surgery among epileptologists, and better understand the reasons for difficulties in recruitment. A survey was sent to three international epilepsy surgery networks, questioning drug withdrawal policies. Forty-seven (19%) surveys were returned. For polytherapy, withdrawal was started at a median of three and six months by the TimeToStop collaborators and other paediatric epileptologists, respectively. Withdrawal was completed at a median of 12 and 20 months, respectively. For monotherapy, tapering was initiated at five and 11 months in these two groups, and ended at a median of seven and 12 months, respectively. Most TimeToStop collaborators believed that it was not justified to wait 12 months after surgery before reducing AEDs, regardless of the number of AEDs taken. Current AED policies in Europe have changed as a consequence of the retrospective TimeToStop results, and this accounts for why recruitment in a randomised trial was not feasible.

Statistical power of clinical trials increased while effect size remained stable: an empirical analysis of 136,212 clinical trials between 1975 and 2014.

OBJECTIVES: To study the statistical power of randomized clinical trials and examine developments over time. STUDY DESIGN AND SETTING: We analyzed the statistical power in 136,212 clinical trials between 1975 and 2014 extracted from meta-analyses from the Cochrane database of systematic reviews. We determined study power to detect standardized effect sizes, where power was based on the meta-analyzed effect size. Average power, effect size, and temporal patterns were examined for all meta-analyses and a subset of significant meta-analyses. RESULTS: The number of trials with power ≥80% was low (7%) but increased over time: from 5% in 1975-1979 to 9% in 2010-2014. In significant meta-analyses, the proportion of trials with sufficient power increased from 9% to 15% in these years (median power increased from 16% to 23%). This increase was mainly due to increasing sample sizes, while effect sizes remained stable with a median Cohen's h of 0.09 (interquartile range 0.04-0.22) and a median Cohen's d of 0.20 (0.11-0.40). CONCLUSION: This study demonstrates that sufficient power in clinical trials is still problematic, although the situation is slowly improving. Our data encourage further efforts to increase statistical power in clinical trials to guarantee rigorous and reproducible evidence-based medicine.

European trends in epilepsy surgery.

OBJECTIVE: Resective surgery is effective in treating drug-resistant focal epilepsy, but it remains unclear whether improved diagnostics influence postsurgical outcomes. Here, we compared practice and outcomes over 2 periods 15 years apart. METHODS: Sixteen European centers retrospectively identified 2 cohorts of children and adults who underwent epilepsy surgery in the period of 1997 to 1998 (n = 562) or 2012 to 2013 (n = 736). Data collected included patient (sex, age) and disease (duration, localization and diagnosis) characteristics, type of surgery, histopathology, Engel postsurgical outcome, and complications, as well as imaging and electrophysiologic tests performed for each case. Postsurgical outcome predictors were included in a multivariate logistic regression to assess the strength of date of surgery as an independent predictor. RESULTS: Over time, the number of operated cases per center increased from a median of 31 to 50 per 2-year period (p = 0.02). Mean disease duration at surgery decreased by 5.2 years (p < 0.001). Overall seizure freedom (Engel class 1) increased from 66.7% to 70.9% (adjusted p = 0.04), despite an increase in complex surgeries (extratemporal and/or MRI negative). Surgeries performed during the later period were 1.34 times (adjusted odds ratio; 95% confidence interval 1.02-1.77) more likely to yield a favorable outcome (Engel class I) than earlier surgeries, and improvement was more marked in extratemporal and MRI-negative temporal epilepsy. The rate of persistent neurologic complications remained stable (4.6%-5.3%, p = 0.7). CONCLUSION: Improvements in European epilepsy surgery over time are modest but significant, including higher surgical volume, shorter disease duration, and improved postsurgical seizure outcomes. Early referral for evaluation is required to continue on this encouraging trend.

Adequate statistical power in clinical trials is associated with the combination of a male first author and a female last author.

Clinical trials have a vital role in ensuring the safety and efficacy of new treatments and interventions in medicine. A key characteristic of a clinical trial is its statistical power. Here we investigate whether the statistical power of a trial is related to the gender of first and last authors on the paper reporting the results of the trial. Based on an analysis of 31,873 clinical trials published between 1974 and 2017, we find that adequate statistical power was most often present in clinical trials with a male first author and a female last author (20.6%, 95% confidence interval 19.4-21.8%), and that this figure was significantly higher than the percentage for other gender combinations (12.5-13.5%; P<0.0001). The absolute number of female authors in clinical trials gradually increased over time, with the percentage of female last authors rising from 20.7% (1975-85) to 28.5% (after 2005). Our results demonstrate the importance of gender diversity in research collaborations and emphasize the need to increase the number of women in senior positions in medicine.

Individualized prediction of seizure relapse and outcomes following antiepileptic drug withdrawal after pediatric epilepsy surgery.

The objective of this study was to create a clinically useful tool for individualized prediction of seizure outcomes following antiepileptic drug withdrawal after pediatric epilepsy surgery. We used data from the European retrospective TimeToStop study, which included 766 children from 15 centers, to perform a proportional hazard regression analysis. The 2 outcome measures were seizure recurrence and seizure freedom in the last year of follow-up. Prognostic factors were identified through systematic review of the literature. The strongest predictors for each outcome were selected through backward selection, after which nomograms were created. The final models included 3 to 5 factors per model. Discrimination in terms of adjusted concordance statistic was 0.68 (95% confidence interval [CI] 0.67-0.69) for predicting seizure recurrence and 0.73 (95% CI 0.72-0.75) for predicting eventual seizure freedom. An online prediction tool is provided on www.epilepsypredictiontools.info/ttswithdrawal. The presented models can improve counseling of patients and parents regarding postoperative antiepileptic drug policies, by estimating individualized risks of seizure recurrence and eventual outcome.

Individualised prediction model of seizure recurrence and long-term outcomes after withdrawal of antiepileptic drugs in seizure-free patients: a systematic review and individual participant data meta-analysis.

BACKGROUND: People with epilepsy who became seizure-free while taking antiepileptic drugs might consider discontinuing their medication, with the possibility of increased quality of life because of the elimination of adverse events. The risk with this action, however, is seizure recurrence. The objectives of our study were to identify predictors of seizure recurrence and long-term seizure outcomes and to produce nomograms for estimation of individualised outcomes. METHODS: We did a systematic review and meta-analysis, and identified eligible articles and candidate predictors, using PubMed and Embase databases with a last update on Nov 6, 2014. Eligible articles had to report on cohorts of patients with epilepsy who were seizure-free and had started withdrawal of antiepileptic drugs; articles also had to contain information regarding seizure recurrences during and after withdrawal. We excluded surgical cohorts, reports with fewer than 30 patients, and reports on acute symptomatic seizures because these topics were beyond the scope of our objective. Risk of bias was assessed using the Quality in Prognosis Studies system. Data analysis was based on individual participant data. Survival curves and proportional hazards were computed. The strongest predictors were selected with backward selection. Models were converted to nomograms and a web-based tool to determine individual risks. FINDINGS: We identified 45 studies with 7082 patients; ten studies (22%) with 1769 patients (25%) were included in the meta-analysis. Median follow-up was 5·3 years (IQR 3·0-10·0, maximum 23 years). Prospective and retrospective studies and randomised controlled trials were included, covering non-selected and selected populations of both children and adults. Relapse occurred in 812 (46%) of 1769 patients; 136 (9%) of 1455 for whom data were available had seizures in their last year of follow-up, suggesting enduring seizure control was not regained by this timepoint. Independent predictors of seizure recurrence were epilepsy duration before remission, seizure-free interval before antiepileptic drug withdrawal, age at onset of epilepsy, history of febrile seizures, number of seizures before remission, absence of a self-limiting epilepsy syndrome, developmental delay, and epileptiform abnormality on electroencephalogram (EEG) before withdrawal. Independent predictors of seizures in the last year of follow-up were epilepsy duration before remission, seizure-free interval before antiepileptic drug withdrawal, number of antiepileptic drugs before withdrawal, female sex, family history of epilepsy, number of seizures before remission, focal seizures, and epileptiform abnormality on EEG before withdrawal. Adjusted concordance statistics were 0·65 (95% CI 0·65-0·66) for predicting seizure recurrence and 0·71 (0·70-0·71) for predicting long-term seizure freedom. Validation was stable across the individual study populations. INTERPRETATION: We present evidence-based nomograms with robust performance across populations of children and adults. The nomograms facilitate prediction of outcomes following drug withdrawal for the individual patient, including both the risk of relapse and the chance of long-term freedom from seizures. The main limitations were the absence of a control group continuing antiepileptic drug treatment and a consistent definition of long-term seizure freedom. FUNDING: Epilepsiefonds.

Cognitive consequences of early versus late antiepileptic drug withdrawal after pediatric epilepsy surgery, the TimeToStop (TTS) trial: study protocol for a randomized controlled trial.

BACKGROUND: The goals of intentional curative pediatric epilepsy surgery are to achieve seizure-freedom and antiepileptic drug (AED) freedom. Retrospective cohort studies have indicated that early postoperative AED withdrawal unmasks incomplete surgical success and AED dependency sooner, but not at the cost of long-term seizure outcome. Moreover, AED withdrawal seemed to improve cognitive outcome. A randomized trial is needed to confirm these findings. We hypothesized that early AED withdrawal in children is not only safe, but also beneficial with respect to cognitive functioning. DESIGN: This is a multi-center pragmatic randomized clinical trial to investigate whether early AED withdrawal improves cognitive function, in terms of attention, executive function and intelligence, quality of life and behavior, and to confirm safety in terms of eventual seizure freedom, seizure recurrences and "seizure and AED freedom." Patients will be randomly allocated in parallel groups (1:1) to either early or late AED withdrawal. Randomization will be concealed and stratified for preoperative IQ and medical center. In the early withdrawal arm reduction of AEDs will start 4 months after surgery, while in the late withdrawal arm reduction starts 12 months after surgery, with intended complete cessation of drugs after 12 and 20 months respectively. Cognitive outcome measurements will be performed preoperatively, and at 1 and 2 years following surgery, and consist of assessment of attention and executive functioning using the EpiTrack Junior test and intelligence expressed as IQ (Wechsler Intelligence Scales). Seizure outcomes will be assessed at 24 months after surgery, and at 20 months following start of AED reduction. We aim to randomize 180 patients who underwent anticipated curative epilepsy surgery below 16 years of age, were able to perform the EpiTrack Junior test preoperatively, and have no predictors of poor postoperative seizure prognosis (multifocal magnetic resonance imaging (MRI) abnormalities, incomplete resection of the lesion, epileptic postoperative electroencephalogram (EEG) abnormalities, or more than three AEDs at the time of surgery). DISCUSSION: Growing experience with epilepsy surgery has changed the view towards postoperative medication policy. In a European collaboration, we designed a multi-center pragmatic randomized clinical trial comparing early with late AED withdrawal to investigate benefits and safety of early AED withdrawal. The TTS trial is supported by the Dutch Epilepsy Fund (NL 08-10) ISRCTN88423240/ 08/05/2013.

Antiepileptic drug withdrawal in medically and surgically treated patients: a meta-analysis of seizure recurrence and systematic review of its predictors.

AIM: Many seizure-free patients consider withdrawal of antiepileptic drugs, both when seizure control is achieved by medication alone, or once they became seizure-free following epilepsy surgery. The risk of recurrence is consequently of very important prognostic value. However, estimations of recurrence risks are outdated for both populations. In addition, although many publications have reported predictors of seizure relapse, no comprehensive overview of prognostic factors is available. METHODS: A systematic review of the databases of PubMed and EMBASE was conducted, identifying articles on antiepileptic drug withdrawal in patient cohorts. Recurrence risk meta-analyses were performed for both populations at one, two, three to four, and five or more years of follow-up. Within the selected articles, studies presenting multivariable analysis of predictors were identified; all studied predictors were listed, as well as all significant independent predictors. The quality of separate analyses of predictors was assessed. RESULTS: There was no significant difference of long-term cumulative recurrence risk between surgical and medication-only populations, with respectively 29% and 34% recurrences. In medication-only treated patients, 25 factors have been reported as significant independent predictors; 12 have been reported in surgical cohorts. The quality of most analyses of predictors was low to moderate. No predictor was consistently found among all analyses, and for most predictors, study results were contradictory. CONCLUSION: No consistent set of predictors could be identified because a large number of variables have been identified in the literature, many studies reported contradicting results, study populations varied considerably, and the quality of the original studies was often low. Meta-analysis of individual participant data is necessary, because it allows for (1) correction for differences in follow-up duration between subjects and studies, (2) a study of interaction effects, (3) calculation of more accurate estimates valid across several populations, and (4) the assessment of each predictor's effect size.

Changing profiles of pediatric epilepsy surgery candidates over time: A nationwide single-center experience from 1990 to 2011.

OBJECTIVE: Over the past decades, the number of epilepsy surgeries in children has increased and indications for surgery have broadened. We studied the changes in patient characteristics between 1990 and 2011 in a nationwide cohort and related these to seizure outcome and postoperative medication status. Second, we tried to identify predictors for seizure outcome after pediatric epilepsy surgery. METHODS: To study changes over time, we divided this retrospective cohort of 234 children into two consecutive time periods of 11 years, and statistically compared the epochs in terms of patient characteristics, surgical variables, complications, seizure outcome, and postoperative medication status. To identify predictors of postoperative seizure freedom, we performed univariable and multivariable logistic regression analyses. RESULTS: The number of surgeries per year increased from an average of 5 in the first, to 16 in the past epoch. Over time, significantly more surgeries were performed for malformations of cortical development, and more patients underwent magnetoencephalography (MEG) and invasive monitoring. Four percent of patients had a serious complication. Complete seizure freedom (Engel class IA) at 2 years after surgery was achieved in 74% of patients, which did not change significantly over time. The proportion of patients who were free from seizures and antiepileptic medication 2 years after surgery significantly increased from 13% to 32%. Factors predictive of seizure recurrence were preoperative intracranial monitoring, multilobar surgery, etiology, and longer duration of epilepsy before surgery. SIGNIFICANCE: Although more complex cases were operated over time and medication was withdrawn earlier after surgery, success rates at 2 years remained stable. In combination with low complication rates, this underscores the efficacy and safety of pediatric epilepsy surgery. It is important to consider epilepsy surgery early, as longer duration of epilepsy increased the risk of postoperative seizure recurrence.