Prediction of primary care depression outcomes at six months: Validation of DOC-6 ©

Kurt B. Angstman, Gregory M. Garrison, Cesar A. Gonzalez, Daniel W. Cozine, Elizabeth W. Cozine, David J Katzelnick

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Background: The goal of this study was to develop and validate an assessment tool for adult primary care patients diagnosed with depression to determine predictive probability of clinical outcomes at 6 months. Methods: We retrospectively reviewed 3096 adult patients enrolled in collaborative care management (CCM) for depression. Patients enrolled on or before December 31, 2013, served as the training set (n = 2525), whereas those enrolled after that date served as the preliminary validation set (n = 571). Results: Six variables (2 demographic and 4 clinical) were statistically significant in determining clinical outcomes. Using the validation data set, the remission classifier produced the receiver operating characteristics (ROC) curve with a c-statistic or area under the curve (AUC) of 0.62 with predicted probabilities than ranged from 14.5% to 79.1%, with a median of 50.6%. The persistent depressive symptoms (PDS) classifier produced an ROC curve with a c-statistic or AUC of 0.67 and predicted probabilities that ranged from 5.5% to 73.1%, with a median of 23.5%. Conclusions: We were able to identify readily available variables and then validated these in the prediction of depression remission and PDS at 6 months. The DOC-6 tool may be used to predict which patients may be at risk for worse outcomes.

Original languageEnglish (US)
Pages (from-to)281-287
Number of pages7
JournalJournal of the American Board of Family Medicine
Issue number3
StatePublished - May 1 2017


  • Depression
  • Primary health care
  • Retrospective studies
  • ROC curve

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Family Practice


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