title: Development and validation of a prediction algorithm for use by health professionals in prediction of recurrence of major depression.
abstract: BACKGROUND
  There exists very little evidence to guide clinical management for preventing recurrence of major depression. The objective of this study was to develop and validate a prediction algorithm for recurrence of major depression.
  
  
  METHODS
  Wave 1 and wave 2 longitudinal data from the U.S. National Epidemiological Survey on Alcohol and Related Condition (2001/2002–2003/2004) were used. Participants with a major depressive episode at baseline and who had visited health professionals for depression were included in this analysis (n = 2,711). Mental disorders were assessed based on the DSM-IV criteria.
  
  
  RESULTS
  With the development data (n = 1,518), a prediction model with 19 unique factors had a C statistics of 0.7504 and excellent calibration (P = .23). The model had a C statistics of 0.7195 in external validation data (n = 1,195) and 0.7365 in combined data. The algorithm calibrated very well in validation data. In the combined data, the 3-year observed and predicted risk of recurrence was 25.40% (95% CI: 23.76%, 27.04%) and 25.34% (95% CI: 24.73%, 25.95%), respectively. The predicted risk in the 1st and 10th decile risk group was 5.68% and 60.21%, respectively.
  
  
  CONCLUSIONS
  The developed prediction model for recurrence of major depression has acceptable discrimination and excellent calibration, and is feasible to be used by physicians. The prognostic model may assist physicians and patients in quantifying the probability of recurrence so that physicians can develop specific treatment plans for those who are at high risk of recurrence, leading to personalized treatment and better use of resources.
authors.forename: Jian Li
authors.initials: JL
authors.lastname: Wang
authors.forename: Scott
authors.initials: S
authors.lastname: Patten
authors.forename: Jitender
authors.initials: J
authors.lastname: Sareen
authors.forename: James
authors.initials: J
authors.lastname: Bolton
authors.forename: Norbert
authors.initials: N
authors.lastname: Schmitz
authors.forename: Glenda
authors.initials: G
authors.lastname: MacQueen
mesh_terms: D000328:Adult; D000465:Algorithms; D003661:Decision Support Techniques; D003865:Major Depressive Disorder / Q000175:diagnosis* / Q000523:psychology / Q000628:therapy*; D005260:Female; D006801:Humans; D008016:Life Change Events; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D008960:Models, Psychological; D010552:Personality Assessment; D011379:Prognosis; D011594:Psychometrics; D011788:Quality of Life / Q000523:psychology; D012008:Recurrence; D015203:Reproducibility of Results; D018570:Risk Assessment