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Activity Number: 629
Type: Invited
Date/Time: Thursday, August 4, 2016 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract #318119 View Presentation
Title: Depression Trajectories in Multiple Sclerosis Patients for Treatment Decision Making
Author(s): Douglas Gunzler*
Companies: Case Western Reserve University
Keywords: latent class growth analysis ; structural equation modeling ; electronic health records ; patient reported outcomes ; multiple sclerosis ; depression

Trajectories of depression over time may be heterogeneous in multiple sclerosis (MS) patients. Latent class growth analysis was applied to 3,507 MS patients using an electronic health records (EHR) data base to identify subgroups of MS patients based on self-reported depression screening (PHQ-9). Subsequently, we describe clinical characteristics of these subgroups and the influence of anti-depressant treatment response. Three subgroups were found characterized by high but declining (10.0% [of participants]), wavering above and below moderate (26.2%) and low and variable (63.8%) depression level trajectories. Patients on anti-depressant treatment at baseline have significantly increased odds of being in the moderate depression subgroup (OR = 1.53, 95% CI = 1.14, 2.04, p = 0.005) relative to the low depression subgroup. Describing depression trajectories in MS patients can help clinicians make improved use of an EHR data base to support clinical decision making in real time.

Authors who are presenting talks have a * after their name.

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