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- Title
A Cognitive-Emotional Biomarker for Predicting Remission with Antidepressant Medications: A Report from the iSPOT-D Trial.
- Authors
Etkin, Amit; Patenaude, Brian; Song, Yun Ju C; Usherwood, Timothy; Rekshan, William; Schatzberg, Alan F; Rush, A John; Williams, Leanne M
- Abstract
Depression involves impairments in a range of cognitive and emotional capacities. It is unknown whether these functions can inform medication choice when considered as a composite predictive biomarker. We tested whether behavioral tests, grounded in the neurobiology of cognitive and emotional functions, predict outcome with common antidepressants. Medication-free outpatients with nonpsychotic major depressive disorder (N=1008; 665 completers) were assessed before treatment using 13 computerized tests of psychomotor, executive, memory-attention, processing speed, inhibitory, and emotional functions. Matched healthy controls (N=336) provided a normative reference sample for test performance. Depressed participants were then randomized to escitalopram, sertraline, or venlafaxine-extended release, and were assessed using the 16-item Quick Inventory of Depressive Symptomatology (QIDS-SR16) and the 17-item Hamilton Rating Scale for Depression. Given the heterogeneity of depression, analyses were furthermore stratified by pretreatment performance. We then used pattern classification with cross-validation to determine individual patient-level composite predictive biomarkers of antidepressant outcome based on test performance. A subgroup of depressed participants (approximately one-quarter of patients) were found to be impaired across most cognitive tests relative to the healthy norm, from which they could be discriminated with 91% accuracy. These patients with generally impaired cognitive task performance had poorer treatment outcomes. For this impaired subgroup, task performance furthermore predicted remission on the QIDS-SR16 at 72% accuracy specifically following treatment with escitalopram but not the other medications. Therefore, tests of cognitive and emotional functions can form a clinically meaningful composite biomarker that may help drive general treatment outcome prediction for optimal treatment selection in depression, particularly for escitalopram.
- Subjects
BIOMARKERS; MENTAL depression; DRUGS; ANTIDEPRESSANTS; PSYCHOMOTOR disorders
- Publication
Neuropsychopharmacology, 2015, Vol 40, Issue 6, p1332
- ISSN
0893-133X
- Publication type
Article
- DOI
10.1038/npp.2014.333