Ostergaard, Søren D2; Bech, Per3; Trivedi, Madhukar H2; Wisniewski, Stephen R2; Rush, A John2; Fava, Maurizio2
1 Department of Clinical Medicine, Department of Clinical Medicine, Faculty of Health and Medical Sciences, Københavns Universitet2 unknown3 Department of Clinical Medicine, Department of Clinical Medicine, Faculty of Health and Medical Sciences, Københavns Universitet
Implications for the Research
BACKGROUND: Most depression rating scales are multidimensional and the resulting heterogeneity may impede identification of coherent biomarkers. The aim of this study was to compare the psychometric performance of the multidimensional 17-item Hamilton Depression Rating Scale (HAM-D17) and the 30-item Inventory of Depressive Symptomatology (IDS-C30) to that of their unidimensional six-item melancholia subscales (HAM-D6 and IDS-C6). METHODS: A total of 2242 subjects from level 1 (citalopram) of the Sequenced Treatment Alternatives to Relieve Depression (STAR* study were included in the analysis. Symptom change, response and remission rates were compared for HAM-D6 versus HAM-D17 and for IDS-C6 versus IDS-C30. The changes in total scores on these scales were compared to the change in Quality of Life Enjoyment and Satisfaction Questionnaire (QLES-Q) score using correlation analysis. RESULTS: The response to treatment was significantly greater according to the HAM-D6 and IDS-C6. Furthermore, the correlation of changes in depression-ratings with changes in QLES-Q scores were comparable for the subscales and full scales. LIMITATIONS: STAR*D was not designed to answer the research questions addressed in this analysis. CONCLUSIONS: Our findings indicate that the HAM-D6 and IDS-C6 melancholia scales capture a coherent construct in depression. The syndrome reflected in these scales is unidimensional, sensitive to specific pharmacological intervention, and therefore likely to have biological validity. We therefore believe that "melancholia" thus defined could be a valuable construct under the Research Domain Criteria (RDoC), which specifically aims at identifying the neurobiology underlying mental disorders and providing drugable targets.
Journal of Affective Disorders, 2014, Vol 163, p. 18-24