Herm J. Lamberink

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

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.

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 However, estimations of recurrence risks are outdated for both populations.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 predictors effect size.

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.

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.

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 Cohens h of 0.09 (interquartile range 0.04-0.22) and a median Cohens 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.

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.