Improving the prediction of treatment response in depression: integration of clinical, cognitive, psychophysiological, neuroimaging, and genetic measures

CNS Spectr. 2008 Dec;13(12):1066-86; quiz 1087-8. doi: 10.1017/s1092852900017120.

Abstract

Antidepressants are important in the treatment of depression, and selective serotonin reuptake inhibitors are first-line pharmacologic options. However, only 50% to 70% of patients respond to first treatment and <40% remit. Since depression is associated with substantial morbidity, mortality, and family burden, it is unfortunate and demanding on health resources that patients must remain on their prescribed medications for at least 4 weeks without knowing whether the particular antidepressant will be effective. Studies have suggested a number of predictors of treatment response, including clinical, psychophysiological, neuroimaging, and genetics, each with varying degrees of success and nearly all with poor prognostic sensitivity and specificity. Studies are yet to be conducted that use multiple measures from these different domains to determine whether sensitivity and specificity can be improved to predict individual treatment response. It is proposed that a focus on standardized testing methodologies across multiple testing modalities and their integration will be crucial for translation of research findings into clinical practice.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Antidepressive Agents / therapeutic use*
  • Cognition / drug effects*
  • Depressive Disorder / drug therapy*
  • Depressive Disorder / genetics
  • Depressive Disorder / pathology
  • Genetic Predisposition to Disease
  • Humans
  • Magnetic Resonance Imaging / methods
  • Prognosis
  • Selective Serotonin Reuptake Inhibitors / therapeutic use*
  • Serotonin Plasma Membrane Transport Proteins / genetics
  • Treatment Outcome

Substances

  • Antidepressive Agents
  • Serotonin Plasma Membrane Transport Proteins
  • Serotonin Uptake Inhibitors