BACKGROUND: Many nonbiological variables are reported to predict treatment response for major depression; however, there is little agreement about which variables are most predictive. 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 = .001). 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.
RCT Entities:
BACKGROUND: Many nonbiological variables are reported to predict treatment response for major depression; however, there is little agreement about which variables are most predictive. 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 = .001). 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.
Authors: Arianna Goracci; Mirko Martinucci; Umberto Scalcione; Andrea Fagiolini; Paolo Castrogiovanni Journal: Qual Life Res Date: 2005-04 Impact factor: 4.147
Authors: Dmitry Khodyakov; Mienah Zulfacar Sharif; Elizabeth L Dixon; Peter Mendel; Bowen Chung; Barbara Linkski; Janis Bush Jones Journal: Community Ment Health J Date: 2013-04-27
Authors: Andrew J Sarkin; Erik J Groessl; Jordan A Carlson; Steven R Tally; Robert M Kaplan; William J Sieber; Theodore G Ganiats Journal: Qual Life Res Date: 2012-10-27 Impact factor: 4.147
Authors: Stephan Köhler; Theresa Unger; Sabine Hoffmann; Arthur Mackert; Barbara Ross; Thomas Fydrich Journal: Qual Life Res Date: 2014-09-21 Impact factor: 4.147