Identifying patients with therapy-resistant depression by using factor analysis.
BACKGROUND
Attempts to identify the factor structure in patients with treatment-resistant depression have been very limited.


METHODS
Principal component analysis was performed using the baseline datasets from 3 add-on studies [2 with repetitive transcranial magnetic stimulation and one with transcranial pulsed electromagnetic fields (T-PEMF)], in which the relative effect as percentage of improvement during the treatment period was analysed.


RESULTS
We identified 2 major factors, the first of which was a general factor. The second was a dual factor consisting of a depression subscale comprising the negatively loaded items (covering the pure depression items) and a treatment resistant subscale comprising the positively loaded items (covering lassitude, concentration difficulties and sleep problems). These 2 dual subscales were used as outcome measures. Improvement on the treatment resistant subscale was 40% in the active treatment group compared to 17-30% improvement in the sham treatments.


CONCLUSIONS
It is possible to describe patients with therapy-resistant depression by a factor structure. Both rTMS and T-PEMF had a clinical effect on the factor-derived scales when compared to sham treatment.
Andreasson
K
K
Psychiatric Research Unit, Frederiksborg General Hospital, Hillerød, Denmark.
Liest
V
V
Lunde
M
M
Martiny
K
K
Unden
M
M
Dissing
S
S
Bech
P
P
D000928:Antidepressive Agents / Q000627:therapeutic use*; D002986:Clinical Trials as Topic; D003865:Major Depressive Disorder / Q000175:diagnosis* / Q000188:drug therapy* / Q000523:psychology; D004351:Drug Resistance; D005163:Factor Analysis, Statistical; D005260:Female; D006801:Humans; D008297:Male; D010919:Placebos; D025341:Principal Component Analysis; D011569:Psychiatric Status Rating Scales; D050781:Transcranial Magnetic Stimulation; D017211:Treatment Failure; D016896:Treatment Outcome
D000928:Antidepressive Agents; D010919:Placebos