Browsing by Author "Gordon, Evian"

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    Antidepressant side effects and their impact on treatment outcome in people with major depressive disorder: an iSPOT-D report.
    (Translational psychiatry, 2021-08-04) Braund, Taylor A; Tillman, Gabriel; Palmer, Donna M; Gordon, Evian; Rush, A John; Harris, Anthony WF
    Side effects to antidepressant medications are common and can impact the prognosis of successful treatment outcome in people with major depressive disorder (MDD). However, few studies have investigated the severity of side effects over the course of treatment and their association with treatment outcome. Here we assessed the severity of side effects and the impact of treatment type and anxiety symptoms over the course of treatment, as well as whether side effects were associated with treatment outcome. Participants were N = 1008 adults with a current diagnosis of single-episode or recurrent, nonpsychotic MDD. Participants were randomised to receive escitalopram, sertraline, or venlafaxine-extended release with equal probability and reassessed at 8 weeks regarding Hamilton Rating Scale Depression (HRSD17) and Quick Inventory of Depressive Symptomatology (QIDS-SR16) remission and response. Severity of side effects were assessed using the Frequency, Intensity, and Burden of Side Effects Rating (FIBSER) scale and assessed at day 4 and weeks 2, 4, 6, and 8. Frequency, intensity, and burden of side effects were greatest at week 2, then only frequency and intensity of side effects gradually decreased up to week 6. Treatment type and anxiety symptoms did not impact the severity of side effects. A greater burden-but not frequency or intensity-of side effects was associated with poorer treatment outcome and as early as 4 days post-treatment. Together, this work provides an informative mapping of the progression of side effects throughout the treatment course and their association with treatment outcome. Importantly, the burden of side effects that are present as early as 4 days post-treatment predicts poorer treatment outcome and should be monitored closely. iSPOT-D: Registry name: ClinicalTrials.gov. Registration number: NCT00693849.
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    Gender-specific structural abnormalities in major depressive disorder revealed by fixel-based analysis.
    (NeuroImage. Clinical, 2019-01-08) Lyon, Matt; Welton, Thomas; Varda, Adrina; Maller, Jerome J; Broadhouse, Kathryn; Korgaonkar, Mayuresh S; Koslow, Stephen H; Williams, Leanne M; Gordon, Evian; Rush, A John; Grieve, Stuart M

    Background

    Major depressive disorder (MDD) is a chronic disease with a large global impact. There are currently no clinically useful predictors of treatment outcome, and the development of biomarkers to inform clinical treatment decisions is highly desirable.

    Methods

    In this exploratory study we performed fixel-based analysis of diffusion MRI data from the International Study to Predict Optimized Treatment in Depression with the aim of identifying novel biomarkers at baseline that may relate to diagnosis and outcome to treatment with antidepressant medications. Analyses used MR data from individuals with MDD (n = 221) and healthy controls (n = 67).

    Results

    We show focal, gender-specific differences in the anterior limb of the internal capsule (males) and bilaterally in the genu of the corpus callosum (females) associated with diagnosis. Lower fibre cross-section in the tapetum, the conduit between the right and left hippocampi, were also associated with a decreased probability of remission. Analysis of conventional fractional anisotropy showed scattered abnormalities in the corona radiata, cerebral peduncles and mid-brain which were much lower in total volume compared to fixel-based analysis.

    Conclusions

    Fixel-based analysis appeared to identify different underlying abnormalities than conventional tensor-based metrics, with almost no overlap between significant regions. We show that MDD is associated with gender specific abnormalities in the genu of the corpus callosum (females) and in the anterior limb of the internal capsule (males), as well as gender-independent differences in the tapetum that predict remission. Diffusion MRI may play a key role in future guidance of clinical decision-making for MDD.
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    Sensitivity, specificity, and predictive power of the "Brief Risk-resilience Index for SCreening," a brief pan-diagnostic web screen for emotional health.
    (Brain and behavior, 2012-09) Williams, Leanne M; Cooper, Nicholas J; Wisniewski, Stephen R; Gatt, Justine M; Koslow, Stephen H; Kulkarni, Jayashri; Devarney, Savannah; Gordon, Evian; John Rush, Augustus
    Few standardized tools are available for time-efficient screening of emotional health status across diagnostic categories, especially in primary care. We evaluated the 45-question Brief Risk-resilience Index for SCreening (BRISC) and the 15-question mini-BRISC in identifying poor emotional health and coping capacity across a range of diagnostic groups - compared with a detailed clinical assessment - in a large sample of adult outpatients. Participants 18-60 years of age (n = 1079) recruited from 12 medical research and clinical sites completed the computerized assessments. Three index scores were derived from the full BRISC and the mini-BRISC: one for risk (negativity-positivity bias) and two for coping (resilience and social capacity). Summed answers were converted to standardized z-scores. BRISC scores were compared with detailed health assessment and diagnostic interview (for current psychiatric, psychological, and neurological conditions) by clinicians at each site according to diagnostic criteria. Clinicians were blinded to BRISC scores. Clinical assessment stratified participants as having "clinical" (n = 435) or "healthy" (n = 644) diagnostic status. Receiver operating characteristic analyses showed that a z-score threshold of -1.57 on the full BRISC index of emotional health provided an optimal classification of "clinical" versus "healthy" status (sensitivity: 81.2%, specificity: 92.7%, positive predictive power: 80.2%, and negative predictive power: 93.1%). Comparable findings were revealed for the mini-BRISC. Negativity-positivity bias index scores contributed the most to prediction. The negativity-positivity index of emotional health was most sensitive to classifying major depressive disorder (100%), posttraumatic stress disorder (95.8%), and panic disorder (88.7%). The BRISC and mini-BRISC both offer a brief, clinically useful screen to identify individuals at risk of disorders characterized by poor emotion regulation, from those with good emotional health and coping.