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Predicting antidepressant response using early changes in cognition: A systematic review.

Caroline Park1, Zihang Pan1, Elisa Brietzke2

  • 1Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada.

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Early cognitive changes may predict antidepressant response in major depressive disorder (MDD). This finding could help clinicians tailor treatments, moving beyond trial-and-error for better patient outcomes.

Keywords:
Antidepressant responseCognitionEarly cognitive changesMajor depressive disorder (MDD)Personalized medicineResponse predictors

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Area of Science:

  • Neuroscience
  • Psychiatry
  • Clinical Psychology

Background:

  • Antidepressant selection currently relies on trial-and-error, leading to treatment failures.
  • Identifying reliable predictors of antidepressant response is crucial for effective clinical practice.
  • Cognitive changes may emerge early in treatment, preceding mood symptom improvement.

Purpose of the Study:

  • To systematically review evidence on whether early cognitive changes predict treatment response in major depressive disorder (MDD).
  • To explore the potential of cognitive measures as early indicators of antidepressant efficacy.

Main Methods:

  • A systematic review was conducted using major scientific databases (PubMed/Medline, Embase, PsychINFO).
  • Studies evaluating early cognitive changes as predictors of later treatment response in MDD were included.

Main Results:

  • Seven articles were identified, suggesting early cognitive changes can predict MDD treatment response.
  • This predictive relationship was observed across various antidepressant classes (SSRIs, SNRIs, NRIs, etc.) and therapies (pharmacotherapy, rTMS).
  • Early improvements in facial emotion recognition, a 'hot' cognitive process, show emerging potential as a predictor.

Conclusions:

  • Early cognitive changes show promise as predictors of antidepressant treatment response in MDD.
  • This could lead to more personalized and effective treatment strategies, reducing trial-and-error.
  • Further research is needed to address heterogeneity in cognitive assessments and confirm predictive values.