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Table 3 Statistical prediction models for AEDs withdrawal

From: Models for predicting treatment efficacy of antiepileptic drugs and prognosis of treatment withdrawal in epilepsy patients

Study Study design Prediction target Development cohorts Final factors Validation cohort Adjusted concordance-statistic Calibration
Lamberink et al. 2017 [25] Systematic review and meta-analysis Seizure relapse and long-term outcomes after withdrawal of AEDs Ten studies with 1 769 patients Duration before remission, seizure-free interval before AEDs withdrawal, age at onset, history of febrile seizures, number of seizures before remission, epilepsy syndrome, developmental delay, EEG before withdrawal, sex, family history of epilepsy Internal and external validation 0.65 for predicting seizure recurrence and 0.71 for predicting long-term seizure freedom Calibration plots showed good calibration
Lamberink et al. 2018 [27] Retrospective Seizure relapse and outcomes after AEDs withdrawal after pediatric epilepsy surgery 766 children from 15 European epilepsy centers Age at withdrawal, time to AEDs reduction, preoperative MRI, postoperative EEG, completeness of resection of the anatomical lesion, average frequency before surgery, number of AEDs at surgery Internal validation 0.68 for predicting seizure recurrence and 0.73 for predicting eventual seizure freedom Calibration plots showed good calibration
  1. AEDs Antiepileptic drugs, EEG Electroencephalogram, MRI Magnetic resonance imaging