Abstract

Background: The chronic phase of post-traumatic stress disorder (PTSD) and the limited effectiveness of existing treatments creates the need for the development of potential biomarkers to predict response to antidepressant medication at an early stage. However, findings at present focus on acute therapeutic effect without following-up the long-term clinical outcome of PTSD. So far, studies predicting the long-term clinical outcome of short-term treatment based on both pre-treatment and post-treatment functional MRI in PTSD remains limited.Methods: Twenty-two PTSD patients were scanned using resting-state functional MRI (rs-fMRI) before and after 12 weeks of treatment with paroxetine. Twenty patients were followed up using the same psychopathological assessments 2 years after they underwent the second MRI scan. Based on clinical outcome, the follow-up patients were divided into those with remitted PTSD or persistent PTSD. Amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) derived from pre-treatment and post-treatment rs-fMRI were used as classification features in a support vector machine (SVM) classifier.Results: Prediction of long-term clinical outcome by combined ALFF and DC features derived from pre-treatment rs-fMRI yielded an accuracy rate of 72.5% (p < 0.005). The most informative voxels for outcome prediction were mainly located in the precuneus, superior temporal area, insula, dorsal medial prefrontal cortex, frontal orbital cortex, supplementary motor area, lingual gyrus, and cerebellum. Long-term outcome could not be successfully classified by post-treatment imaging features with accuracy rates <50%.Conclusions: Combined information from ALFF and DC from rs-fMRI data before treatment could predict the long-term clinical outcome of PTSD, which is critical for defining potential biomarkers to customize PTSD treatment and improve the prognosis.

Highlights

  • Posttraumatic stress disorder (PTSD) is a debilitating psychiatric disorder characterized by re-experiencing, avoidance, numbing, and hyperarousal [1], and is a major worldwide public health problem [2, 3]

  • Since we found a significant correlation between the changes of mean ALFF and Clinician-Administered PTSD Scale (CAPS) scores in the PTSD group before and after treatment in our previous study [10] and the 2-year follow-up data of the current study is continuation of our previous work [10], we hypothesized that the post-treatment rs-fMRI would be more predictive than the pre-treatment rs-fMRI data

  • 21 patients responded to the pharmacotherapy with a CAPS improvement of at least 50%, and only one patient did not respond to the pharmacotherapy with a CAPS decrease by three scores

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Summary

Background

The chronic phase of post-traumatic stress disorder (PTSD) and the limited effectiveness of existing treatments creates the need for the development of potential biomarkers to predict response to antidepressant medication at an early stage. Findings at present focus on acute therapeutic effect without following-up the long-term clinical outcome of PTSD. Studies predicting the long-term clinical outcome of short-term treatment based on both pre-treatment and post-treatment functional MRI in PTSD remains limited

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