title: The accuracy of outcome prediction models for childhood-onset epilepsy.
abstract: OBJECTIVE
  Two large prospective cohort studies of childhood epilepsy (Nova Scotia and the Netherlands) each developed a statistical model to predict long-term outcome. We sought to evaluate the accuracy of a prognostic model based on the two studies combined.
  
  
  METHODS
  Analyses with classification tree models and stepwise logistic regression produced predictive models for the combined dataset and the two separate cohorts. The resulting models were then externally validated on the opposite cohort. Remission was defined as no longer receiving daily medication for any length of time at the end of follow-up.
  
  
  RESULTS
  The combined cohorts yielded 1,055 evaluable patients. At the end of follow-up (>or=5 years in >96%), 622 (59%) were in remission. By using the combined data, the classification tree model and the logistic regression model predicted the outcome correctly in approximately 70%. The classification tree model split the data on epilepsy type and age at first seizure. Predictors in the logistic regression model were: seizure number before treatment, age at first seizure, absence seizures, epilepsy types of symptomatic generalized and symptomatic partial, preexisting neurologic signs, intelligence, and the combination of febrile seizures and cryptogenic partial epilepsy. When the prediction models from each cohort were cross-validated on the opposite cohort, the outcome was predicted slightly less accurately than did the model from the combined data.
  
  
  CONCLUSIONS
  Based on currently available clinical and EEG variables, predicting the outcome of childhood epilepsy may be difficult and appears to be incorrect in about one of every three patients.
authors.affiliation: Department of Pediatric Neurology, Erasmus MC, Sophia Children's Hospital, Rotterdam, The Netherlands.
authors.forename: Miranda
authors.initials: M
authors.lastname: Geelhoed
authors.forename: Anne Olde
authors.initials: AO
authors.lastname: Boerrigter
authors.forename: Peter
authors.initials: P
authors.lastname: Camfield
authors.forename: Ada T
authors.initials: AT
authors.lastname: Geerts
authors.forename: Willem
authors.initials: W
authors.lastname: Arts
authors.forename: Bruce
authors.initials: B
authors.lastname: Smith
authors.forename: Carol
authors.initials: C
authors.lastname: Camfield
mesh_terms: D017668:Age of Onset; D000927:Anticonvulsants / Q000627:therapeutic use; D002648:Child; D002675:Child, Preschool; D015331:Cohort Studies; D004569:Electroencephalography / Q000706:statistics & numerical data; D004827:Epilepsy / Q000145:classification / Q000175:diagnosis* / Q000188:drug therapy; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007361:Intelligence Tests / Q000706:statistics & numerical data; D016015:Logistic Models; D008297:Male; D015233:Models, Statistical; D009426:Netherlands; D009674:Nova Scotia; D017063:Outcome Assessment, Health Care; D011379:Prognosis; D011446:Prospective Studies
chemical_list: D000927:Anticonvulsants