Symptom Clusters as Predictors of Late Response to Antidepressant Treatment
J Clin Psychiatry 2005;66(8):1064-1070
© Copyright 2017 Physicians Postgraduate Press, Inc.
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Objective: While there is some indication from
studies in the acute phase of antidepressant treatment that there
are differences in the timing of improvement in symptoms,
relatively little work has explored the patterns of change for
specific symptom clusters and the predictability of these changes
to signal eventual response during the acute phase of treatment.
This article investigates the use of clusters of symptoms on the
17-item Hamilton Rating Scale for Depression (HAM-D-17) to define
the pattern of late response versus nonresponse to antidepressant
Method: Using principal component analysis, the
HAM-D-17 was divided into 4 symptom clusters (mood, sleep/psychic
anxiety, appetite, and somatic anxiety/weight). Data for 996
patients with major depressive disorder (DSM-III-R criteria), who
participated in a 12-week acute phase study with nefazodone, were
subjected to a post hoc analysis of changes in symptom cluster
scores. Patients were divided into 3 groups: early responders
(< 4 weeks), late responders (4-12 weeks), and nonresponders
(> 12 weeks) as defined by < 50% reduction in HAM-D-17 scores
from baseline. The late-responder and nonresponder groups were
subjected to the principal component analysis. Data were
collected from October 1992 to November 1994.
Results: There were significant differences in
the pattern of symptom change on the mood cluster (weeks 3-4)
(p < .0001), the sleep/psychic anxiety cluster (weeks 3-4)
(p < .003), and the somatic anxiety/weight cluster (weeks 3-4)
(p < .01) for the late responders compared to the nonresponders.
Using change scores, a discriminant function analysis correctly
assigned 127 of the 182 late responders and 85 of the 133
nonresponders, or 70% of the late responders and 64% of the
nonresponders, to their final response groups.
Conclusion: Monitoring changes in symptom
clusters from the HAM-D-17 during this crucial early stage (first
4 weeks) can be used to distinguish late responders (after week
4) from nonresponders. Successful identification of nonresponders
based on symptom cluster change in the first 4 weeks would
facilitate a shortening of an ineffective treatment trial and
allow for necessary changes in treatment strategy, helping
physicians more closely follow treatment guidelines.