A statistical model for the classification of imipramine response in depressed inpatients
- 1 October 1982
- journal article
- research article
- Published by Springer Nature in Psychopharmacology
- Vol. 78 (2) , 185-189
- https://doi.org/10.1007/bf00432260
Abstract
We present a statistical model, recently developed for application in mathematical economics, that yields empirical evidence for the existence of two distinct subtypes of depression. We reanalyze previously reported data on 65 depressed patients treated with imipramine and repeatedly rated on the Hamilton Rating Scale (HRS). The estimated model paraeters suggest two underlying response processes. Patients in the first subgroup were initially more severely depressed (as measured by the total HRS score), but exhibited a rapid rate of symptomatic response over time. In contrast, patients in the second subgroup were initially less severely depressed, yet showed a much slower rate of improvement. These findings recommend a refinement of the clinical definitions of endogenous depression. While this model suggests that there are two underlying response processes, it does not classify individual patients. Subject classification was made possible by fitting an item-response model to the data. This model relates the 17 individual symptom ratings, at baseline, to the total post-treatment HRS scores. The results of this analysis suggest that the previously described relationship between high initial severity of depression and more rapid improvement over time is characteristic of subjects who exhibit initial motor retardation and decreased sexual interest. Graphical analysis clearly indicates that subjects who exhibit both motor retardation and decreased sexual interest at baseline have higher total HRS scores at baseline and show more pronounced improvement in total HRS scores in response to treatment with imipramine. Patients not exhibiting motor retardation and decreased sexual interest were less severely depressed initially and show virtually no clinical response over time.Keywords
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