Sensitivity to changes during antidepressant treatment: a comparison of unidimensional subscales of the Inventory of Depressive Symptomatology (IDS-C) and the Hamilton Depression Rating Scale (HAMD) in patients with mild major, minor or subsyndromal depression.

Abstract

In the efficacy evaluation of antidepressant treatments, the total score of the Hamilton Depression Rating Scale (HAMD) is still regarded as the 'gold standard'. We previously had shown that the Inventory of Depressive Symptomatology (IDS) was more sensitive to detect depressive symptom changes than the HAMD17 (Helmreich et al. 2011). Furthermore, studies suggest that the unidimensional subscales of the HAMD, which capture the core depressive symptoms, outperform the full HAMD regarding the detection of antidepressant treatment effects. The aim of the present study was to compare several unidimensional subscales of the HAMD and the IDS regarding their sensitivity to changes in depression symptoms in a sample of patients with mild major, minor or subsyndromal depression (MIND). Biweekly IDS-C28 and HAMD17 data from 287 patients of a 10-week randomised, placebo-controlled trial comparing the effectiveness of sertraline and cognitive-behavioural group therapy in patients with MIND were converted to subscale scores and analysed during the antidepressant treatment course. We investigated sensitivity to depressive change for all scales from assessment-to-assessment, in relation to depression severity level and placebo-verum differences. The subscales performed similarly during the treatment course, with slight advantages for some subscales in detecting treatment effects depending on the treatment modality and on the items included. Most changes in depressive symptomatology were detected by the IDS short scale, but regarding the effect sizes, it performed worse than most subscales. Unidimensional subscales are a time- and cost-saving option in judging drug therapy outcomes, especially in antidepressant treatment efficacy studies. However, subscales do not cover all facets of depression (e.g. atypical symptoms, sleep disturbances), which might be important for comprehensively understanding the nature of the disease depression. Therefore, the cost-to-benefit ratio must be carefully assessed in the decision for using unidimensional subscales.