title: Predictive socioeconomic and clinical profiles of antidepressant response and remission.
abstract: BACKGROUND
  There are many prognostic factors for treatment outcome in major depressive disorder (MDD). The predictive power of any single factor, however, is limited. We aimed to develop profiles of antidepressant response and remission based upon hierarchical combinations of baseline clinical and demographic factors.
  
  
  METHODS
  Using data from Level 1 of the Sequenced Treatment Alternatives to Relieve Depression trial (STAR*D), in which 2,876 participants with MDD were treated with citalopram, a signal-detection analysis was performed to identify hierarchical predictive profiles for patients with different treatment outcome. An automated algorithm was used to determine the optimal predictive variables by evaluating sensitivity, specificity, positive and negative predictive value, and test efficiency.
  
  
  RESULTS
  Hierarchical combinations of baseline clinical and demographic factors yielded profiles that significantly predicted treatment outcome. In contrast to an overall 47% response rate in STAR*D Level 1, response rates of profiled patient subgroups ranged from 31 to 63%. In contrast to an overall remission rate of 28%, identified subsets of patients had a 12 to 55% probability of remission. The predictors of antidepressant treatment outcome most commonly incorporated into profiles were related to socioeconomic status (e.g., income, education), whereas indicators of depressive symptom type and severity, as well as comorbid clinical conditions, were useful but less powerful predictors.
  
  
  CONCLUSIONS
  Hierarchical profiles of demographic and clinical baseline variables categorized patients according to the likelihood they would benefit from a single antidepressant trial. Socioeconomic factors had greater predictive power than symptoms or other clinical factors, and profiles combining multiple factors were stronger predictors than individual factors alone.
authors.affiliation: Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, California 90024, USA. fjain@mednet.ucla.edu
authors.forename: Felipe A
authors.initials: FA
authors.lastname: Jain
authors.forename: Aimee M
authors.initials: AM
authors.lastname: Hunter
authors.forename: John O
authors.initials: JO
authors.lastname: Brooks
authors.forename: Andrew F
authors.initials: AF
authors.lastname: Leuchter
mesh_terms: D000328:Adult; D000465:Algorithms; D000928:Antidepressive Agents / Q000627:therapeutic use*; D015283:Citalopram / Q000627:therapeutic use*; D003865:Major Depressive Disorder / Q000188:drug therapy*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D011569:Psychiatric Status Rating Scales; D012372:ROC Curve; D016032:Randomized Controlled Trials as Topic; D012074:Remission Induction; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D017603:Signal Detection, Psychological; D012959:Socioeconomic Factors; D016896:Treatment Outcome
chemical_list: D000928:Antidepressive Agents; D015283:Citalopram
keywords: antidepressants; anxiety/anxiety disorders; clinical trials; depression, gender; pharmacotherapy; treatment