Effect of olanzapine exposure on relapse and brain structure in patients with major depressive disorder with psychotic features.

Some data suggest that antipsychotics may adversely affect brain structure. We examined the relationship among olanzapine exposure, relapse, and changes in brain structure in patients with major depressive disorder with psychotic features. We analyzed data from the Study of the Pharmacotherapy of Psychotic Depression II trial (STOP-PD II), a randomized, placebo-controlled trial in patients with psychotic depression who attained remission on sertraline and olanzapine and were randomized to continue sertraline plus olanzapine or placebo for 36 weeks. Olanzapine steady state concentration (SSC) were calculated based on sparsely-sampled levels. Rates of relapse and changes in brain structure were assessed as outcomes. There were significant associations between dosage and relapse rates (N = 118; HR = 0.94, 95% CI [0.897, 0.977], p = 0.002) or changes in left cortical thickness (N = 44; B = -2.0 × 10-3, 95% CI [-3.1 × 10-3, -9.6 × 10-4], p < 0.001) and between SSC and changes in left cortical thickness (N = 44; B = -8.7 × 10-4, 95% CI [-1.4 × 10-3, -3.6 × 10-4], p = 0.001). Similar results were found for the right cortex. These associations were no longer significant when the analysis was restricted to participants treated with olanzapine. Our findings suggest that, within its therapeutic range, the effect of olanzapine on relapse or cortical thickness does not depend on its dosage or SSC. Further research is needed on the effect of olanzapine and other antipsychotics on mood symptoms and brain structure.

Trajectories of remitted psychotic depression: identification of predictors of worsening by machine learning.

BACKGROUND: Remitted psychotic depression (MDDPsy) has heterogeneity of outcome. The study's aims were to identify subgroups of persons with remitted MDDPsy with distinct trajectories of depression severity during continuation treatment and to detect predictors of membership to the worsening trajectory. METHOD: One hundred and twenty-six persons aged 18-85 years participated in a 36-week randomized placebo-controlled trial (RCT) that examined the clinical effects of continuing olanzapine once an episode of MDDPsy had remitted with sertraline plus olanzapine. Latent class mixed modeling was used to identify subgroups of participants with distinct trajectories of depression severity during the RCT. Machine learning was used to predict membership to the trajectories based on participant pre-trajectory characteristics. RESULTS: Seventy-one (56.3%) participants belonged to a subgroup with a stable trajectory of depression scores and 55 (43.7%) belonged to a subgroup with a worsening trajectory. A random forest model with high prediction accuracy (AUC of 0.812) found that the strongest predictors of membership to the worsening subgroup were residual depression symptoms at onset of remission, followed by anxiety score at RCT baseline and age of onset of the first lifetime depressive episode. In a logistic regression model that examined depression score at onset of remission as the only predictor variable, the AUC (0.778) was close to that of the machine learning model. CONCLUSIONS: Residual depression at onset of remission has high accuracy in predicting membership to worsening outcome of remitted MDDPsy. Research is needed to determine how best to optimize the outcome of psychotic MDDPsy with residual symptoms.

Effects of antipsychotic medication on functional connectivity in major depressive disorder with psychotic features.

The effect of antipsychotic medication on resting state functional connectivity in major depressive disorder (MDD) is currently unknown. To address this gap, we examined patients with MDD with psychotic features (MDDPsy) participating in the Study of the Pharmacotherapy of Psychotic Depression II. All participants were treated with sertraline plus olanzapine and were subsequently randomized to continue sertraline plus olanzapine or be switched to sertraline plus placebo. Participants completed an MRI at randomization and at study endpoint (study completion at Week 36, relapse, or early termination). The primary outcome was change in functional connectivity measured within and between specified networks and the rest of the brain. The secondary outcome was change in network topology measured by graph metrics. Eighty-eight participants completed a baseline scan; 73 completed a follow-up scan, of which 58 were usable for analyses. There was a significant treatment X time interaction for functional connectivity between the secondary visual network and rest of the brain (t = -3.684; p = 0.0004; pFDR = 0.0111). There was no significant treatment X time interaction for graph metrics. Overall, functional connectivity between the secondary visual network and the rest of the brain did not change in participants who stayed on olanzapine but decreased in those switched to placebo. There were no differences in changes in network topology measures when patients stayed on olanzapine or switched to placebo. This suggests that olanzapine may stabilize functional connectivity, particularly between the secondary visual network and the rest of the brain.

Depressive symptom complexes of community-dwelling older adults: a latent network model.

Late-life depression has multiple, heterogeneous clinical presentations. The aim of the study was to identify higher-order homogeneous clinical features (symptom complexes), while accounting for their potential causal interactions within the network approach to psychopathology. We analyzed cross-sectional data from community-dwelling adults aged 65-85 years recruited by the European MentDis_ICF65+ study (n = 2623, mean age 74, 49% females). The severity of 33 depressive symptoms was derived from the age-adapted Composite International Diagnostic Interview. Symptom complexes were identified using multiple detection algorithms for symptom networks, and their fit to data was assessed with latent network models (LNMs) in exploratory and confirmatory analyses. Sensitivity analyses included the Partial Correlation Likelihood Test (PCLT) to investigate the data-generating structure. Depressive symptoms were organized by the Walktrap algorithm into eight symptom complexes, namely sadness/hopelessness, anhedonia/lack of energy, anxiety/irritability, self-reproach, disturbed sleep, agitation/increased appetite, concentration/decision making, and thoughts of death. An LNM adequately fit the distribution of individual symptoms' data in the population. The model suggested the presence of reciprocal interactions between the symptom complexes of sadness and anxiety, concentration and self-reproach and between self-reproach and thoughts of death. Results of the PCLT confirmed that symptom complex data were more likely generated by a network, rather than a latent-variable structure. In conclusion, late-life depressive symptoms are organized into eight interacting symptom complexes. Identification of the symptom complexes of late-life depression may streamline clinical assessment, provide targets for personalization of treatment, and aid the search for biomarkers and for predictors of outcomes of late-life depression.

Genomic Investigation of Remission and Relapse of Psychotic Depression Treated with Sertraline plus Olanzapine: The STOP-PD II Study.

INTRODUCTION: Little is known regarding genetic factors associated with treatment outcome of psychotic depression. We explored genomic associations of remission and relapse of psychotic depression treated with pharmacotherapy. METHODS: Genomic analyses were performed in 171 men and women aged 18-85 years with an episode of psychotic depression who participated in the Study of the Pharmacotherapy of Psychotic Depression II (STOP-PD II). Participants were treated with open-label sertraline plus olanzapine for up to 12 weeks; those who achieved remission or near-remission and maintained it following 8 weeks of stabilization were eligible to participate in a 36-week randomized controlled trial that compared sertraline plus olanzapine with sertraline plus placebo in preventing relapse. RESULTS: There were no genome-wide significant associations with either remission or relapse. However, at a suggestive threshold, SNP rs1026501 (31 kb from SYNPO2) in the whole sample and rs6844137 (within the intronic region of SYNPO2) in the European ancestry subsample were associated with a decreased likelihood of remission. In polygenic risk analyses, participants who had greater improvement after antidepressant treatments showed a higher likelihood of reaching remission. Those who achieved remission and had a higher polygenic risk for Alzheimer's disease had a significantly decreased likelihood of relapse. CONCLUSION: Our analyses provide preliminary insights into the genetic architecture of remission and relapse in a well-characterized group of patients with psychotic depression.

Risk stratification models for predicting preventable hospitalization in commercially insured late middle-aged adults with depression.

BACKGROUND: A significant number of late middle-aged adults with depression have a high illness burden resulting from chronic conditions which put them at high risk of hospitalization. Many late middle-aged adults are covered by commercial health insurance, but such insurance claims have not been used to identify the risk of hospitalization in individuals with depression. In the present study, we developed and validated a non-proprietary model to identify late middle-aged adults with depression at risk for hospitalization, using machine learning methods. METHODS: This retrospective cohort study involved 71,682 commercially insured older adults aged 55-64 years diagnosed with depression. National health insurance claims were used to capture demographics, health care utilization, and health status during the base year. Health status was captured using 70 chronic health conditions, and 46 mental health conditions. The outcomes were 1- and 2-year preventable hospitalization. For each of our two outcomes, we evaluated seven modelling approaches: four prediction models utilized logistic regression with different combinations of predictors to evaluate the relative contribution of each group of variables, and three prediction models utilized machine learning approaches - logistic regression with LASSO penalty, random forests (RF), and gradient boosting machine (GBM). RESULTS: Our predictive model for 1-year hospitalization achieved an AUC of 0.803, with a sensitivity of 72% and a specificity of 76% under the optimum threshold of 0.463, and our predictive model for 2-year hospitalization achieved an AUC of 0.793, with a sensitivity of 76% and a specificity of 71% under the optimum threshold of 0.452. For predicting both 1-year and 2-year risk of preventable hospitalization, our best performing models utilized the machine learning approach of logistic regression with LASSO penalty which outperformed more black-box machine learning models like RF and GBM. CONCLUSIONS: Our study demonstrates the feasibility of identifying depressed middle-aged adults at higher risk of future hospitalization due to burden of chronic illnesses using basic demographic information and diagnosis codes recorded in health insurance claims. Identifying this population may assist health care planners in developing effective screening strategies and management approaches and in efficient allocation of public healthcare resources as this population transitions to publicly funded healthcare programs, e.g., Medicare in the US.

Placebo Effect in Randomized Trials of Major Depressive Disorder With Psychotic Features: A Systematic Review and Descriptive Meta-Analysis.

BACKGROUND: In the 1980s, the response rate of major depressive disorder with psychotic features (MDD-Psy) to placebo pills was reported to be close to 0%. To our knowledge, this placebo response rate has not been systematically reassessed. We undertook a systematic review of randomized controlled trials (RCTs) that have used a placebo or sham control group for MDD-Psy. METHODS: We searched MEDLINE and identified 9 relevant publications reporting on 10 studies comparing a placebo or sham interventions versus an active intervention. We extracted reported rates of response or of dropout for all causes associated with placebo versus active intervention(s) and aggregated response and dropout rates across trials. RESULTS: Two sham-controlled electroconvulsive therapy (ECT) trials did not provide response rates. In the 3 pharmacotherapy studies published in the 1980s, 0 of 12 participants (0%) responded to placebo versus 13 of 38 (34.2%) responding to the active interventions. In contrast, 5 RCTs published in the 2000s, 114 of 339 participants (33.6%) randomized to placebo responded versus 149 of 373 participants (39.9%) randomized to active interventions; dropout rates were 71/236 (30.1%) for placebo versus 84/282 (29.8%) for the active interventions. CONCLUSIONS: As expected, response rates to placebo pills in RCTs for MDD-Psy increased markedly from the 1980s to the 2000s. Methodological issues in the design and conduct of more recent RCTs may have contributed to the high placebo response. However, one needs to consider this placebo response rate when interpreting the result of recent trials of MDD-Psy, which typically have not included a "pure" placebo condition.

Comparing the streamlined psychotherapy "Engage" with problem-solving therapy in late-life major depression. A randomized clinical trial.

Effective psychotherapies for late-life depression are underutilized, mainly because of their complexity. "Engage" is a novel, streamlined psychotherapy that relies on neurobiology to identify core behavioral pathology of late-life depression and targets it with simple interventions, co-designed with community therapists so that they can be delivered in community settings. Consecutively recruited adults (≥60 years) with major depression (n = 249) were randomly assigned to 9 weekly sessions of "Engage" or to the evidence-based Problem-Solving Therapy (PST) offered by 35 trained community social workers and assessed by blind raters. "Engage" therapists required an average of 30% less training time to achieve fidelity to treatment than PST therapists and had one-third of the PST therapists' skill drift. Both treatments led to reduction of HAM-D scores over 9 weeks. The mixed effects model-estimated HAM-D ratings were not significantly different between the two treatments at any assessment point of the trial. The one-sided 95% CI for treatment-end difference was (-∞, 0.07) HAM-D points, indicating a non-inferiority margin of 1.3 HAM-D points or greater; this margin is lower than the pre-determined 2.2-point margin. The two treatment arms had similar response (HR = 1.08, 95% CI (0.76, 1.52), p = 0.67) and remission rates (HR = 0.89, 95% CI (0.57, 1.39), p = 0.61). We conclude that "Engage" is non-inferior to PST. If disseminated, "Engage" will increase the number of therapists who can reliably treat late-life depression and make effective psychotherapy available to large numbers of depressed older adults.

Modifiable predictors of nonresponse to psychotherapies for late-life depression with executive dysfunction: a machine learning approach.

The study aimed to: (1) Identify distinct trajectories of change in depressive symptoms by mid-treatment during psychotherapy for late-life depression with executive dysfunction; (2) examine if nonresponse by mid-treatment predicted poor response at treatment end; and (3) identify baseline characteristics predicting an early nonresponse trajectory by mid-treatment. A sample of 221 adults 60 years and older with major depression and executive dysfunction were randomized to 12 weeks of either problem-solving therapy or supportive therapy. We used Latent Growth Mixture Models (LGMM) to detect subgroups with distinct trajectories of change in depression by mid-treatment (6th week). We conducted regression analyses with LGMM subgroups as predictors of response at treatment end. We used random forest machine learning algorithms to identify baseline predictors of LGMM trajectories. We found that ~77.5% of participants had a declining trajectory of depression in weeks 0-6, while the remaining 22.5% had a persisting depression trajectory, with no treatment differences. The LGMM trajectories predicted remission and response at treatment end. A random forests model with high prediction accuracy (80%) showed that the strongest modifiable predictors of the persisting depression trajectory were low perceived social support, followed by high neuroticism, low treatment expectancy, and low perception of the therapist as accepting. Our results suggest that modifiable risk factors of early nonresponse to psychotherapy can be identified at the outset of treatment and addressed with targeted personalized interventions. Therapists may focus on increasing meaningful social interactions, addressing concerns related to treatment benefits, and creating a positive working relationship.

Risk Prediction Models for Depression in Community-Dwelling Older Adults.

OBJECTIVE: To develop streamlined Risk Prediction Models (Manto RPMs) for late-life depression. DESIGN: Prospective study. SETTING: The Survey of Health, Ageing and Retirement in Europe (SHARE) study. PARTICIPANTS: Participants were community residing adults aged 55 years or older. MEASUREMENTS: The outcome was presence of depression at a 2-year follow up evaluation. Risk factors were identified after a literature review of longitudinal studies. Separate RPMs were developed in the 29,116 participants who were not depressed at baseline and in the combined sample of 39,439 of non-depressed and depressed subjects. Models derived from the combined sample were used to develop a web-based risk calculator. RESULTS: The authors identified 129 predictors of late-life depression after reviewing 227 studies. In non-depressed participants at baseline, the RPMs based on regression and Least Absolute Shrinkage and Selection Operator (LASSO) penalty (34 and 58 predictors, respectively) and the RPM based on Artificial Neural Networks (124 predictors) had a similar performance (AUC: 0.730-0.743). In the combined depressed and non-depressed participants at baseline, the RPM based on neural networks (35 predictors; AUC: 0.807; 95% CI: 0.80-0.82) and the model based on linear regression and LASSO penalty (32 predictors; AUC: 0.81; 95% CI: 0.79-0.82) had satisfactory accuracy. CONCLUSIONS: The Manto RPMs can identify community-dwelling older individuals at risk for developing depression over 2 years. A web-based calculator based on the streamlined Manto model is freely available at https://manto.unife.it/ for use by individuals, clinicians, and policy makers and may be used to target prevention interventions at the individual and the population levels.

Adaptation and Pilot Study of a Behavioral Intervention Targeting Morning Activation Deficits in Dementia Caregivers: Scheduling Activity and Monitoring Mornings (SAMM).

OBJECTIVES: Morning activation deficits (MADs) correlate with depression symptom persistence in older dementia caregivers. To clarify the potential of MADs as a target for depression interventions, we aimed to: 1) adapt an existing behavioral activation program, Engage therapy, to target mornings; and 2) evaluate effects on self-reported MADs and depression symptoms. METHODS: While trialing the 9-week Engage adaption (targeting mornings) in six older dementia caregivers, we incorporated feedback and finalized an adapted program called Scheduling Activity and Monitoring Mornings (SAMM). We delivered the SAMM protocol to 13 dementia caregivers (all female; mean age = 69, standard deviation = 7). We report modifications made/rationale, as well as changes in subjective MADs (relevant items from the Composite Scale of Morningness) and depression symptoms (Patient Health Questionnaire - 9). RESULTS: Using caregiver and expert input, we adapted the protocol to: include educational materials/content describing the potential relationship between morning inactivity and depression; target activity scheduling within 2 hours of awakening (preferably earlier); and focus only on the main components of morning activity scheduling, planning, and monitoring. This program was associated with decreases in subjective MADs averaging 29% at week 4, 52% at week 6, and 57% by week 9 (all p's <0.005). Initial depression symptoms were significantly reduced, by 62%, at week 9. CONCLUSIONS: These preliminary findings suggest that subjective MADs can be modified pragmatically, and that doing so may have antidepressant effects. A controlled trial with measures of the putative mechanism is needed to clarify whether, and if so how, targeting MAD with SAMM causally perturbs depression's mechanisms.

Estimated Regional White Matter Hyperintensity Burden, Resting State Functional Connectivity, and Cognitive Functions in Older Adults.

OBJECTIVE: White matter hyperintensities (WMH) are linked to deficits in cognitive functioning, including cognitive control and memory; however, the structural, and functional mechanisms are largely unknown. We investigated the relationship between estimated regional disruptions to white matter fiber tracts from WMH, resting state functional connectivity (RSFC), and cognitive functions in older adults. DESIGN: Cross-sectional study. SETTING: Community. PARTICIPANTS: Fifty-eight cognitively-healthy older adults. MEASUREMENTS: Tasks of cognitive control and memory, structural MRI, and resting state fMRI. We estimated the disruption to white matter fiber tracts from WMH and its impact on gray matter regions in the cortical and subcortical frontoparietal network, default mode network, and ventral attention network by overlaying each subject's WMH mask on a normative tractogram dataset. We calculated RSFC between nodes in those same networks. We evaluated the interaction of regional WMH burden and RSFC in predicting cognitive control and memory. RESULTS: The interaction of estimated regional WMH burden and RSFC in cortico-striatal regions of the default mode network and frontoparietal network was associated with delayed recall. Models predicting working memory, cognitive inhibition, and set-shifting were not significant. CONCLUSION: Findings highlight the role of network-level structural and functional alterations in resting state networks that are related to WMH and impact memory in older adults.

Association between psychomotor disturbance and treatment outcome in psychotic depression: a STOP-PD II report.

BACKGROUND: Little is known about the relationship between psychomotor disturbance (PMD) and treatment outcome of psychotic depression. This study examined the association between PMD and subsequent remission and relapse of treated psychotic depression. METHODS: Two hundred and sixty-nine men and women aged 18-85 years with an episode of psychotic depression were treated with open-label sertraline plus olanzapine for up to 12 weeks. Participants who remained in remission or near-remission following an 8-week stabilization phase were eligible to participate in a 36-week randomized controlled trial (RCT) that compared the efficacy and tolerability of sertraline plus olanzapine (n = 64) with sertraline plus placebo (n = 62). PMD was measured with the psychiatrist-rated sign-based CORE at acute phase baseline and at RCT baseline. Spearman's correlations and logistic regression analyses were used to analyze the association between CORE total score at acute phase baseline and remission/near-remission and CORE total score at RCT baseline and relapse. RESULTS: Higher CORE total score at acute phase baseline was associated with lower frequency of remission/near-remission. Higher CORE total score at RCT baseline was associated with higher frequency of relapse, in the RCT sample as a whole, as well as in each of the two randomized groups. CONCLUSIONS: PMD is associated with poorer outcome of psychotic depression treated with sertraline plus olanzapine. Future research needs to examine the neurobiology of PMD in psychotic depression in relation to treatment outcome.

Pharmacotherapy Prescriptions for Relapse Prevention of Psychotic Depression After Electroconvulsive Therapy.

PURPOSE/BACKGROUND: Electroconvulsive therapy (ECT) is effective in the treatment of acute episodes of psychotic depression. However, no adequately powered studies have directly investigated the efficacy of antipsychotic pharmacotherapy in relapse prevention of psychotic depression after ECT. In the absence of such literature, we reviewed the clinical practice of 4 academic medical centers that have made research contributions in the treatment of psychotic depression over the past 20 years. METHODS/PROCEDURES: We reviewed medical records of patients with a diagnosis of psychotic depression who received 1 or more acute courses of ECT over the span of 3 years. Chi-square tests were used to compare pharmacotherapy prescribed at the time of completion of ECT. FINDINGS/RESULTS: A total of 163 patients received 176 courses of ECT for separate episodes of psychotic depression. The combination of an antidepressant plus an antipsychotic was the most common regimen, ranging from 61.9% to 85.5% of all prescriptions. One center added lithium in 45.5% of cases treated with the combination of an antidepressant plus an antipsychotic. An antipsychotic alone was prescribed in less than 10% of cases. An antidepressant alone or other drug combinations were rare. IMPLICATIONS/CONCLUSIONS: The combination of an antidepressant plus an antipsychotic was the most commonly prescribed regimen at the completion of ECT for relapse prevention in patients with psychotic depression acutely treated with ECT. Although this report offers a view of the clinical practice of 4 academic medical centers, it also points to the need of randomized controlled trials on continuation pharmacotherapy after treatment of psychotic depression with ECT.

The symptom network structure of depressive symptoms in late-life: Results from a European population study.

The network theory conceptualizes mental disorders as complex networks of symptoms influencing each other by creating feedback loops, leading to a self-sustained syndromic constellation. Symptoms central to the network have the greatest impact in sustaining the rest of symptoms. This analysis focused on the network structure of depressive symptoms in late-life because of their distinct etiologic factors, clinical presentation, and outcomes. We analyzed cross-sectional data from wave 2 of the 19 country Survey of Health, Ageing, and Retirement in Europe (SHARE) and included non-institutionalized adults aged 65 years or older (mean age 74 years, 59% females) endorsing at least one depressive symptom on the EURO-D scale for depression (N =8,557). We characterized the network structure of depressive symptoms in late-life and used indices of "strength", "betweenness", and "closeness" to identify symptoms central to the network. We used a case-dropping bootstrap procedure to assess network stability. Death wishes, depressed mood, loss of interest, and pessimism had the highest values of centrality. Insomnia, fatigue and appetite changes had lower centrality values. The identified network remained stable after dropping 74.5% of the sample. Sex or age did not significantly influence the network structure. In conclusion, death wishes, depressed mood, loss of interest, and pessimism constitute the "backbone" that sustains depressive symptoms in late-life. Symptoms central to the network of depressive symptoms may be used as targets for novel, focused interventions and in studies investigating neurobiological processes central to late-life depression.

Adapting and Optimizing Problem Adaptation Therapy (PATH) for People With Mild-Moderate Dementia and Depression.

OBJECTIVE: To adapt and optimize problem adaptation therapy for depression in dementia by grounding it in the lives of people with dementia, caregivers and clinicians. METHODS: A person-centered qualitative approach was taken to elicit the unique cognitive, psychological and social needs of people with dementia relevant to the adaptation of the intervention. A two-stage design was used: the first involved interviews and focus groups to identify priorities and concerns surrounding depression in dementia, the second trialling of the adapted intervention. PARTICIPANTS: Ten people with dementia and nine caregivers participated in individual interviews, 35 healthcare practitioners and clinical academics with experience of working with dementia participated in focus groups. RESULTS: The findings highlight the importance of addressing key themes that typified the experience of depression among people with dementia including: a profound sense of isolation and role loss, the feeling of being both a burden and poorly understood, polarized thinking, interpersonal tensions, diverging views among carers and people with dementia about their capabilities, and changeability in cognitive ability and mood. These themes were used to inform adaptation of the intervention manual, ensuring that its content and delivery addressed the concerns of both people with depression and dementia and those who support them. CONCLUSION: Implications for PATH included a focus on facilitating open communication, supporting the continuation of valued roles, and improving confidence.

Cortical Thickness of the Salience Network and Change in Apathy Following Antidepressant Treatment for Late-Life Depression.

OBJECTIVE: Apathy is common in late-life depression and is associated with poor response to antidepressant drugs. In depressed older adults, apathy may be characterized by neuroanatomical abnormalities of the salience network. The current study examined whether cortical thickness of select salience network structures predicted change in apathy following a 12-week treatment with escitalopram. METHODS: A sample of 46 older adults with major depressive disorder received 12 weeks of escitalopram treatment at a daily target dose of 20 mg. All participants underwent a structural brain MRI scan at baseline, and cortical thickness was estimated in key cortical nodes of the salience network: the caudal anterior cingulate cortex and the insula. We measured baseline and post-treatment symptoms using the Apathy Evaluation Scale and the Hamilton Depression Rating Scale. RESULTS: A thicker insula at baseline predicted reduction in apathy symptoms following 12 weeks of treatment with escitalopram, even when controlling for age, baseline depression severity and change in depressive symptoms. CONCLUSION: Reduced insular thickness predicted residual apathetic symptoms following escitalopram treatment. These results converge with our previous findings of abnormal functional connectivity of the insular cortex in older depressed individuals with apathy. Older depressed adults with apathy may benefit from alternative treatment approaches or augmentative interventions that target abnormalities of the salience network.

Effect of Older vs Younger Age on Anthropometric and Metabolic Variables During Treatment of Psychotic Depression With Sertraline Plus Olanzapine: The STOP-PD II Study.

OBJECTIVE: To examine the effect of older versus younger age on change in anthropometric and metabolic measures during extended treatment of psychotic depression with sertraline plus olanzapine. METHODS: Two hundred and sixty-nine men and women aged 18-85 years with an episode of psychotic depression were treated with open-label sertraline plus olanzapine for up to 12 weeks. Participants who remained in remission following an 8-week stabilization phase were eligible to participate in a 36-week randomized controlled trial (RCT) that compared the efficacy and tolerability of sertraline plus olanzapine with sertraline plus placebo. Weight, waist circumference and plasma lipids, glucose, HbA1c, and insulin were measured at regular intervals during the acute, stabilization and randomized phases of the study. Linear mixed models were used to analyze the trajectories of anthropometric and metabolic measures. RESULTS: Participants aged 60 years or older experienced less weight gain and less increase in cholesterol during the combined acute and stabilization phases of the study compared with those aged 18-59 years. At the acute-stabilization termination visit, mean weight in older participants was 6.5 lb. less than premorbid weight, whereas it was 17.9 lb. more than premorbid weight in younger participants. In the RCT, there was a significant interaction of treatment and age group for the trajectory of weight, but the post hoc tests that compared age groups within each treatment arm were not statistically significant. There were no clinically significant differences between younger and older participants in glycemic measures. CONCLUSION: Older patients with psychotic depression experienced less increase in weight and total cholesterol than their younger counterparts during acute and stabilization treatment with sertraline plus olanzapine. In the older group, weight gained during the acute and stabilization phases appeared to be partial restoration of weight lost during the index episode of depression, whereas weight gain in younger participants was not.

PROTECT: a novel psychotherapy for late-life depression in elder abuse victims.

Elder abuse is prevalent, and victims have high rates of depression and low quality of life. We established an academic-community partnership to test the feasibility, acceptability, and impact of a brief psychotherapy for depression (PROTECT) among elder abuse victims with capacity to make decisions. Elder abuse service providers referred depressed (Patient Health Questionnaire-9 [PHQ-9] ≥ 10) older victims (age ≥ 55 years) for potential pilot study participation. Forty eligible victims who consented were randomized to PROTECT psychotherapy (N = 25) or a Usual Care (N = 15) condition involving a community psychotherapy referral. Follow-up research assessments were conducted at 6 weeks (mid-treatment) and 9 weeks (end of treatment) after study initial assessment. We used mixed-effects regression models to examine treatment effects on depression severity and quality of life over time. Most victims (75%) reported two or more types of abuse. The a priori acceptability benchmark was met at the end of PROTECT therapy. All PROTECT participants initiated therapy; this engagement rate is greater than the a priori 75% standard set for feasibility. We found a significant reduction in depression severity (Montgomery-Åsberg Depression Rating Scale [MADRS]), with PROTECT leading to greater benefits compared to Usual Care. Both study groups had a similar improvement in quality of life. The pilot project results found that PROTECT psychotherapy is feasible, acceptable, and effective in reducing depression. With the support of our partnership, we found that PROTECT could be delivered alongside elder abuse services with victims willing to initiate therapy that leads to meaningful treatment effects.

Behavioral Activation and Depression Symptomatology: Longitudinal Assessment of Linguistic Indicators in Text-Based Therapy Sessions.

BACKGROUND: Behavioral activation (BA) is rooted in the behavioral theory of depression, which states that increased exposure to meaningful, rewarding activities is a critical factor in the treatment of depression. Assessing constructs relevant to BA currently requires the administration of standardized instruments, such as the Behavioral Activation for Depression Scale (BADS), which places a burden on patients and providers, among other potential limitations. Previous work has shown that depressed and nondepressed individuals may use language differently and that automated tools can detect these differences. The increasing use of online, chat-based mental health counseling presents an unparalleled resource for automated longitudinal linguistic analysis of patients with depression, with the potential to illuminate the role of reward exposure in recovery. OBJECTIVE: This work investigated how linguistic indicators of planning and participation in enjoyable activities identified in online, text-based counseling sessions relate to depression symptomatology over time. METHODS: Using distributional semantics methods applied to a large corpus of text-based online therapy sessions, we devised a set of novel BA-related categories for the Linguistic Inquiry and Word Count (LIWC) software package. We then analyzed the language used by 10,000 patients in online therapy chat logs for indicators of activation and other depression-related markers using LIWC. RESULTS: Despite their conceptual and operational differences, both previously established LIWC markers of depression and our novel linguistic indicators of activation were strongly associated with depression scores (Patient Health Questionnaire [PHQ]-9) and longitudinal patient trajectories. Emotional tone; pronoun rates; words related to sadness, health, and biology; and BA-related LIWC categories appear to be complementary, explaining more of the variance in the PHQ score together than they do independently. CONCLUSIONS: This study enables further work in automated diagnosis and assessment of depression, the refinement of BA psychotherapeutic strategies, and the development of predictive models for decision support.