Health-Related Quality-of-Life Measure Enhances Acute Treatment Response Prediction in Depressed Inpatients
J Clin Psychiatry 2001;62(4):261-268
© Copyright 2017 Physicians Postgraduate Press, Inc.
Purchase This PDF for $40.00
If you are not a paid subscriber, you may purchase the PDF.
(You'll need the free Adobe Acrobat Reader.)
Receive immediate full-text access to JCP. You can subscribe to JCP online-only ($86) or print + online ($156 individual).
With your subscription, receive a free PDF collection of the NCDEU Festschrift articles. Hurry! This offer ends December 31, 2011.
If you are a paid subscriber to JCP and do not yet have a username and password, activate your subscription now.
As a paid subscriber who has activated your subscription, you have access to the HTML and PDF versions of this item.
Click here to login.
Did you forget your password?
Still can't log in? Contact the Circulation Department at 1-800-489-1001 x4 or send email
Background: Many nonbiological variables are
reported to predict treatment response for major depression;
however, there is little agreement about which variables are most
Method: Inpatient subjects (N = 59) diagnosed
with current DSM-IV major depressive disorder completed weekly
depressive symptom ratings with the Hamilton Rating Scale for
Depression (HAM-D-17) and Beck Depression Inventory (BDI), and
weekly health-related quality-of-life (HRQL) ratings with the
Quality of Well-Being Scale (QWB). Acute responders were
identified by a 50% decrease in HAM-D-17 score from baseline
within 4 weeks of medication treatment. Predictor variables were
initially chosen from a literature review and then tested for
their association with acute treatment response.
Results: An initial predictive model
including age at first depression, admission BDI score, and
melancholia predicted acute treatment response with 69% accuracy
and was designated as the benchmark model. Adding the admission
QWB index score to the benchmark model did not improve the
prediction rate; however, adding the admission QWB subscales for
physical and social activity to the benchmark model significantly
improved acute treatment response prediction to 86% accuracy (p =
Conclusion: In addition to being designed for
use in cost-effectiveness analyses, the QWB subscales appear to
be useful HRQL variables for predicting acute inpatient
depression treatment response.