Validation of Two Prognostic Models Predicting Outcome at Two Years after Diagnosis in a New Cohort of Children with Epilepsy: The Dutch Study of Epilepsy in Childhood

Abstract

Summary:Purpose: To validate two prognostic models for childhood-onset epilepsy designed to predict a terminal remission of <6 months at 2 years after diagnosis in children referred to the hospital.Methods: A hospital-based cohort of children with newly diagnosed epilepsy was recruited and followed up for 2 years to validate previously developed models. One model was based on variables collected at intake, and the other was based on intake variables plus variables collected during the first 6 months of follow-up. The accuracy of both models was estimated by measuring the area under the receiver-operant-characteristic curves (ROC area).Results: The ROC area of the model developed with intake variables was 0.69 [95% confidence interval (CI), 0.64-0.74] for the original cohort and 0.62 (95% CI, 0.55-0.69) for the validation cohort. The best combination of sensitivity and specificity for the original cohort was 61.6% and 69.1%, whereas it was 60.0% and 61.4% for the validation cohort. For the model with intake and 6-month variables combined, the ROC area was 0.78 (95% CI, 0.73-0.82) for the original cohort and 0.71 (95% CI, 0.64-0.78) for the validation cohort. The sensitivity and specificity were 72.6% and 73.1%, respectively, for the original cohort and 67.4% and 60.2%, respectively, for the validation cohort.Conclusions: Although both models predict outcome better than chance, they are insufficiently accurate to be of practical value. Both models performed marginally less well with the validation cohort than with the original cohort, but in both instances, the model based on intake and 6-month variables was more accurate.

Risk Factors for Drug Resistance in Epileptic Children with Age of Onset above Five Years: A Case-Control Study

“…The definition of initial response varies between studies, usually defined as seizure freedom within 3 to 12 months of the initial treatment. It is frequently found to be a strong predictor of long-term seizure freedom [ 11 , 16 , 29 , 30 ]. In accordance with our own findings, other studies also found that children who had achieved seizures control did so on low to moderate ASM doses [ 31 , 32 ].…”

“…In a study that only included children with younger age of onset of younger than 36 months, risk factors for drug resistance that were found included the age of onset ≤ 12 months, abnormal brain imaging, developmental delay at diagnosis, and focal slowing on initial EEG after multivariate analysis [ 16 ]. The Nova Scotia Study and the Dutch Study of Epilepsy in Childhood, which included 1055 children with the age of onset of epilepsy between 1 month and 16 years, found symptomatic or cryptogenic epilepsy to be the most important risk factor after multivariate analysis [ 30 , 33 ]. This result persisted after 15 years of follow-up [ 34 ].…”

Respons Awal Obat Antiepilepsi Monoterapi pada Pasien Epilepsi Baru

“…Penelitian prospektif berbasis rumah sakit sebelumnya juga melibatkan subyek yang sebagian besar merupakan pasien rujukan. [2][3][4][5] Batasan operasional dalam menentukan etiologi sebenarnya lebih kepada klinis karena tidak semua pasien dilakukan pemeriksaan pencitraan, seperti MRI, functional MRI (fMRI), magnetic resonance spectroscopy (MRS) sehingga kelainan struktural sebagai etiologi belum sepenuhnya dapat ditentukan. Pemeriksaan analisis genetik sebagai etiologi epilepsi tidak dilakukan karena keterbatasan fasilitas.…”

Predicting antiepileptic drug response in children with epilepsy

“…Most of the studies dealing with factors predicting long-term seizure outcome are observational, retrospective, short-lasting, clinic-based and carried out in small samples of patients. Lack of specificity and sensitivity of observed risk factors is of concern [45]. Lack of predefined definitions of seizure-free periods, short duration of follow-up, small sample size and selection bias all contribute to a biased assessment of the treatment outcome and to a biased identification of the risk factors.…”