Optimizing patient expectancy in the pharmacologic treatment of major depressive disorder.
BACKGROUND
Patient expectancy is an important source of placebo effects in antidepressant clinical trials, but all prior studies measured expectancy prior to the initiation of medication treatment. Little is known about how expectancy changes during the course of treatment and how such changes influence clinical outcome. Consequently, we undertook the first analysis to date of in-treatment expectancy during antidepressant treatment to identify its clinical and demographic correlates, typical trajectories, and associations with treatment outcome.


METHODS
Data were combined from two randomized controlled trials of antidepressant medication for major depressive disorder in which baseline and in-treatment expectancy assessments were available. Machine learning methods were used to identify pre-treatment clinical and demographic predictors of expectancy. Multilevel models were implemented to test the effects of expectancy on subsequent treatment outcome, disentangling within- and between-patient effects.


RESULTS
Random forest analyses demonstrated that whereas more severe depressive symptoms predicted lower pre-treatment expectancy, in-treatment expectancy was unrelated to symptom severity. At each measurement point, increased in-treatment patient expectancy significantly predicted decreased depressive symptoms at the following measurement (B = -0.45, t = -3.04, p = 0.003). The greater the gap between expected treatment outcomes and actual depressive severity, the greater the subsequent symptom reductions were (B = 0.49, t = 2.33, p = 0.02).


CONCLUSIONS
Greater in-treatment patient expectancy is associated with greater subsequent depressive symptom reduction. These findings suggest that clinicians may benefit from monitoring and optimizing patient expectancy during antidepressant treatment. Expectancy may represent another treatment parameter, similar to medication compliance and side effects, to be regularly monitored during antidepressant clinical management.
['Zilcha-Mano|Sigal|S|', 'Brown|Patrick J|PJ|', 'Roose|Steven P|SP|', 'Cappetta|Kiley|K|', 'Rutherford|Bret R|BR|']
D000328:Adult D000368:Aged D000369:Aged, 80 and over D059031:Anticipation, Psychological D000928:Antidepressive Agents D003865:Depressive Disorder, Major D005260:Female D006801:Humans D000069550:Machine Learning D008297:Male D008875:Middle Aged D055361:Multilevel Analysis D015990:Placebo Effect D011569:Psychiatric Status Rating Scales D035842:Research Subjects D012720:Severity of Illness Index D016896:Treatment Outcome D055815:Young Adult
expectancy major depressive disorder placebo effects