A cognitive-emotional biomarker for predicting remission with antidepressant medications: a report from the iSPOT-D trial

Neuropsychopharmacology. 2015 May;40(6):1332-42. doi: 10.1038/npp.2014.333. Epub 2014 Dec 30.

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.

Publication types

  • Multicenter Study
  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Antidepressive Agents / therapeutic use*
  • Citalopram / therapeutic use
  • Cognition
  • Computers
  • Delayed-Action Preparations
  • Depressive Disorder, Major / diagnosis*
  • Depressive Disorder, Major / drug therapy*
  • Depressive Disorder, Major / psychology
  • Emotions
  • Female
  • Humans
  • Male
  • Middle Aged
  • Prognosis
  • Psychiatric Status Rating Scales
  • Psychological Tests*
  • Sertraline / therapeutic use
  • Treatment Outcome
  • Venlafaxine Hydrochloride / therapeutic use
  • Young Adult

Substances

  • Antidepressive Agents
  • Delayed-Action Preparations
  • Citalopram
  • Venlafaxine Hydrochloride
  • Sertraline