Prediction for relapse and prognosis of newly diagnosed epilepsy

Abstract

OBJECTIVE: The objective of this study was to investigate the timing of therapy initiation and other clinical factors as potential predictors for relapse and prognosis of epilepsy, based on hospital-based prospective observational data in China. METHODS: One hundred and seventy-one newly diagnosed patients with one or more seizures were recruited and followed for at least 2 years. Kaplan-Meier survival analysis was used for calculating recurrence and remission rates. Univariate and multivariate analyses for risk factors were performed using Cox proportional hazards model. RESULTS: Among the 171 patients analyzed, more patients had partial (54.4%) than generalized seizures (45.6%). The range of patients' age was 6-70 years, but 70% were under 16 years of age. Multiple seizure types (HR = 2.01; 95% CI, 1.31-3.10), epileptiform electroencephalogram (EEG) abnormality (HR = 1.95; 95% CI, 1.09-3.49), and >1 seizure monthly before treatment (HR = 2.74; 95% CI, 1.69-4.51) were predictors of seizure recurrence. The best negative predictors of remission were as follows: relapse (HR = 0.13; 95% CI, 0.07-0.23) and epileptiform EEG within 1 year of treatment (HR = 0.61; 95% CI, 0.39-0.97). Delayed treatment after three or more seizures did not significantly increase the risk of recurrence (P = 0.70) or remission (P = 0.31) compared with early treatment after one or two seizures. CONCLUSIONS: Multiple seizure types, epileptiform EEG abnormality, and >1 seizure monthly before treatment predict seizure recurrence. Relapse and epileptiform EEG within 1 year of treatment predict adverse seizure outcome. Early treatment does not affect relapse or prognosis.