Towards Personalizing Treatment for Depression

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Abstract

Background:

While ‘personalized medicine' commonly refers to genetic markers or profiles associated with pharmacological treatment response, tailoring treatments to patient preferences and values is equally important.

Objective:

To describe and demonstrate a method to develop ‘values markers,' or profiles based on the relative importance of attributes of depression treatment.

Study Design:

Discrete choice analysis was used to assess individuals' relative preferences for features of depression treatment. Preference profiles were developed using latent profile analysis.

Patients or Other Participants:

Eighty-six adults participating in an internet-based discrete choice questionnaire.

Main Outcome Measure:

Participants were presented with two depression scenarios representing mild and severe depression. For each scenario, they were asked to compare 18 choice sets based on the type of medication side effect (nausea, dizziness, and sexual dysfunction) and severity (mild, moderate, and severe); and for counseling frequency (once per week or every other week) and provider setting (the office of a mental health professional, primary care doctor, or spiritual counselor).

Results:

Three profiles were identified: profile 1 was associated with a preference for counseling and an avoidance of medication side effects; profile 2 with an avoidance of strong medication side effects and for receiving counseling in medical settings; and profile 3 with a preference for medication over counseling. When presented with a severe depression scenario, there was a higher prevalence for profile 1 and patients were more likely to prefer mental health over primary care and spiritual settings.

Conclusions:

Values markers may provide a foundation for personalized medicine, and reflect current initiatives emphasizing patient-centered care. Next steps should assess whether values markers are predictive of treatment initiation and adherence.

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