PT  - JOURNAL ARTICLE
AU  - Angstman, Kurt B.
AU  - Garrison, Gregory M.
AU  - Gonzalez, Cesar A.
AU  - Cozine, Daniel W.
AU  - Cozine, Elizabeth W.
AU  - Katzelnick, David J.
TI  - Prediction of Primary Care Depression Outcomes at Six Months: Validation of DOC-6 ©
AID  - 10.3122/jabfm.2017.03.160313
DP  - 2017 May 01
TA  - The Journal of the American Board of Family
                Medicine
PG  - 281--287
VI  - 30
IP  - 3
4099  - http://www.jabfm.org/content/30/3/281.short
4100  - http://www.jabfm.org/content/30/3/281.full
SO  - J Am Board Fam Med2017 May 01; 30
AB  - 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.