Toward an online cognitive and emotional battery to predict treatment remission in depression.
OBJECTIVE
To evaluate the performance of a cognitive and emotional test battery in a representative sample of depressed outpatients to inform likelihood of remission over 8 weeks of treatment with each of three common antidepressant medications.


METHODS
Outpatients 18-65 years old with nonpsychotic major depressive disorder (17 sites) were randomized to escitalopram, sertraline or venlafaxine-XR (extended release). Participants scored ≥12 on the baseline 16-item Quick Inventory of Depressive Symptomatology - Self-Report and completed 8 weeks of treatment. The baseline test battery measured cognitive and emotional status. Exploratory multivariate logistic regression models predicting remission (16-item Quick Inventory of Depressive Symptomatology - Self-Report score ≤5 at 8 weeks) were developed independently for each medication in subgroups stratified by age, sex, or cognitive and emotional test performance. The model with the highest cross-validated accuracy determined the participant proportion in each arm for whom remission could be predicted with an accuracy ≥10% above chance. The proportion for whom a prediction could be made with very high certainty (positive predictive value and negative predictive value exceeding 80%) was calculated by incrementally increasing test battery thresholds to predict remission/non-remission.


RESULTS
The test battery, individually developed for each medication, improved identification of remitting and non-remitting participants by ≥10% beyond chance for 243 of 467 participants. The overall remission rates were escitalopram: 40.8%, sertraline: 30.3%, and venlafaxine-XR: 31.1%. Within this subset for whom prediction exceeded chance, test battery thresholds established a negative predictive value of ≥80%, which identified 40.9% of participants not remitting on escitalopram, 77.1% of participants not remitting on sertraline, and 38.7% of participants not remitting on venlafaxine-XR (all including 20% false negatives).


CONCLUSIONS
The test battery identified about 50% of each medication group as being ≥10% more or less likely to remit than by chance, and identified about 38% of individuals who did not remit with ≥80% certainty. Clinicians might choose to avoid this specific medication in these particular patients.
Brain Resource, San Francisco, CA, USA.
Evian
E
Gordon
Duke-NUS, Singapore.
A John
AJ
Rush
Brain Resource, Sydney, NSW, Australia ; Brain Dynamics Center, Sydney Medical School - Westmead and Westmead Millennium Institute, The University of Sydney, Sydney, NSW, Australia.
Donna M
DM
Palmer
Brain Resource, Sydney, NSW, Australia.
Taylor A
TA
Braund
Brain Resource, San Francisco, CA, USA.
William
W
Rekshan
antidepressant medication; biomarkers; cognitive tests; depression; treatment prediction; treatment selection