title: Looking for childhood-onset schizophrenia: diagnostic algorithms for classifying children and adolescents with psychosis.
abstract: OBJECTIVE
  Among children <13 years of age with persistent psychosis and contemporaneous decline in functioning, it is often difficult to determine if the diagnosis of childhood onset schizophrenia (COS) is warranted. Despite decades of experience, we have up to a 44% false positive screening diagnosis rate among patients identified as having probable or possible COS; final diagnoses are made following inpatient hospitalization and medication washout. Because our lengthy medication-free observation is not feasible in clinical practice, we constructed diagnostic classifiers using screening data to assist clinicians practicing in the community or academic centers.
  
  
  METHODS
  We used cross-validation, logistic regression, receiver operating characteristic (ROC) analysis, and random forest to determine the best algorithm for classifying COS (n=85) versus histories of psychosis and impaired functioning in children and adolescents who, at screening, were considered likely to have COS, but who did not meet diagnostic criteria for schizophrenia after medication washout and inpatient observation (n=53). We used demographics, clinical history measures, intelligence quotient (IQ) and screening rating scales, and number of typical and atypical antipsychotic medications as our predictors.
  
  
  RESULTS
  Logistic regression models using nine, four, and two predictors performed well with positive predictive values>90%, overall accuracy>77%, and areas under the curve (AUCs)>86%.
  
  
  CONCLUSIONS
  COS can be distinguished from alternate disorders with psychosis in children and adolescents; greater levels of positive and negative symptoms and lower levels of depression combine to make COS more likely. We include a worksheet so that clinicians in the community and academic centers can predict the probability that a young patient may be schizophrenic, using only two ratings.
authors.affiliation: 1 Child Psychiatry Branch, National Institute of Mental Health (NIMH)/National Institutes of Health (NIH) , Bethesda, Maryland.
authors.forename: Deanna
authors.initials: D
authors.lastname: Greenstein
authors.forename: Rachna
authors.initials: R
authors.lastname: Kataria
authors.forename: Peter
authors.initials: P
authors.lastname: Gochman
authors.forename: Abhijit
authors.initials: A
authors.lastname: Dasgupta
authors.forename: James D
authors.initials: JD
authors.lastname: Malley
authors.forename: Judith
authors.initials: J
authors.lastname: Rapoport
authors.forename: Nitin
authors.initials: N
authors.lastname: Gogtay
mesh_terms: D000293:Adolescent; D000465:Algorithms; D014150:Antipsychotic Agents / Q000627:therapeutic use; D002648:Child; D005260:Female; D006801:Humans; D007361:Intelligence Tests; D016015:Logistic Models; D008297:Male; D011237:Predictive Value of Tests; D011569:Psychiatric Status Rating Scales; D011618:Psychotic Disorders / Q000175:diagnosis* / Q000188:drug therapy; D012372:ROC Curve; D012561:Schizophrenia, Childhood / Q000175:diagnosis* / Q000188:drug therapy
chemical_list: D014150:Antipsychotic Agents