Predictors, moderators, and mediators (correlates) of treatment outcome in major depressive disorder

Association between polygenic risk scores combined with clinical characteristics and antidepressant efficacy

BACKGROUND

While millions of people suffer from major depressive disorder (MDD), research has shown that individual differences in antidepressant efficacy exist, potentially attributable to various factors. Polygenic risk scores (PRSs) carry clinical potential, but associations with treatment response are seldom reported. Here, we examined whether PRSs for MDD and schizophrenia (SCZ) are associated with antidepressant effectiveness and the influence of other factors.

METHODS

A total of 999 patients were included, and the PRSs for the MDD and SCZ were calculated. The main outcome was a change in the 17-item Hamilton Depression Rating Scale (HAMD17) scores from before to after 2-week treatment. The Mann-Whitney test, Spearman correlation analysis, multiple stepwise linear regression analysis, and interaction analysis were used for statistical analysis.

RESULTS

In the 912 subjects passing quality control, a difference in the HAM-D17 score reduction rate between the MDD phenotype PRS (MDD-PRS) high-risk and the low-risk groups was discovered (P = 0.009), and a correlation was found between the MDD-PRS and the HAM-D17 score reduction rate (r = -0.075, P = 0.024). Moreover, antidepressant efficacy was related to MDD-PRS (β = -4.086, P = 0.039), the Snaith-Hamilton Pleasure Scale-total score (β = -0.009, P = 0.005), and non-first episode (β = -0.039, P < 0.001). However, the result of the interaction analysis was nonsignificant.

LIMITATIONS

The main limitation was that only 1309 targeted genes were selected based on pathways known to be involved in MDD and/or antidepressant effects.

CONCLUSION

These findings suggest a difference in antidepressant efficacy between patients in different MDD-PRS groups. Moreover, the MDD-PRS combined with clinical characteristics partially explained inter-individual differences in antidepressant efficacy.

Comorbid anxiety, loneliness, and chronic pain as predictors of intervention outcomes for subclinical depressive symptoms in older adults: evidence from a large community-based study in Hong Kong

BACKGROUND

Depression is among the leading causes of the global burden of disease and is associated with substantial morbidity in old age. The importance of providing timely intervention, particularly those with subclinical symptoms, has thus increasingly been emphasised. Despite their overall effectiveness, a small but notable subgroup tends to be less responsive to interventions. Identifying predictors of non-remission and non-response is critical to inform future strategies for optimising intervention outcomes.

METHODS

A total of 4153 older adults aged 60 years and above with subclinical depressive symptoms (Patient Health Questionnaire-9 [PHQ-9] = 5-19) were recruited from JC JoyAge, a large-scale collaborative stepped-care intervention service across Hong Kong. A wide range of clinical and modifiable risk and protective factors at baseline were assessed, including depressive symptoms, anxiety symptoms, loneliness, suicidal ideation, cognitive capacity, multimorbidity, chronic pain, need for informal care due to mental health reasons, history of abuse, and sociodemographic characteristics. Separate multivariable logistic regression models were applied to identify predictors of non-remission (PHQ-9 ≥ 5) and non-response (< 50% reduction in PHQ-9) following intervention.

RESULTS

The rates of non-remission and non-response were 18.9% (n = 784) and 23.0% (n = 956), respectively. Comorbid anxiety symptoms (adjusted odds ratio [aOR] = 2.08, CI = 1.72-2.51; 1.28, 1.05-1.57), loneliness (2.00, 1.66-2.42; 1.67, 1.38-2.01), need for informal care (1.86, 1.49-2.33; 1.48, 1.18-1.85), lower cognitive capacity (0.95, 0.93-0.97; 0.94, 0.92-0.96), and absence of chronic pain (0.59, 0.48-0.72; 0.76, 0.64-0.91) predicted both non-remission and non-response. Meanwhile, moderate-to-severe depressive symptoms predicted higher odds of non-remission (1.41, 1.18-1.69) and lower odds of non-response (0.28, 0.23-0.34), respectively. Subgroup analyses conducted separately in older adults with mild and moderate-to-severe depressive symptoms at baseline revealed that comorbid anxiety, loneliness, need for informal care, and absence of chronic pain were consistent predictors of non-remission. Those with non-remission and non-response showed more depression-related functional impairments and poorer health-related quality of life post-intervention.

CONCLUSIONS

Older adults with subclinical depressive symptoms showing comorbid anxiety, higher loneliness, need for informal care, and chronic pain may be offered more targeted interventions in future services. A personalised risk-stratification approach may be helpful.

TRIAL REGISTRATION

ClinicalTrials.gov identifiers: NCT03593889 (registered 29 May 2018), NCT04863300 (registered 23 April 2021).

Global burden of major depressive disorders attributable to intimate partner violence against women: Magnitude, temporal trends, and regional inequalities

AIMS

This study aimed to analyze the temporal trends, spatial heterogeneities, and potential improvements in the burden of major depressive disorders (MDD) attributable to intimate partner violence (IPV) against women across 21 global burden of disease (GBD) regions, and 204 countries and territories from 1990 to 2019.

METHODS

We evaluated the burden of MDD attributable to IPV against women, as measured in disability-adjusted life years (DALYs) per 100,000 people across 21 GBD regions and 204 GBD countries and territories, using data from the 2019 GBD Study. The average annual percentage change (AAPC) of the DALY age-standardized rates (ASRs) was used to reflect trends over time. LOESS and quantile regression were used to model the relationship between the five GBD sociodemographic index (SDI) categories and DALY ASRs. Frontier analysis determined the minimum achievable DALY ASR associated with developmental status, as measured by the SDI.

RESULTS

The overall AAPC in age-standardized DALY rates for MDD attributable to IPV declined globally between 1990 and 2019. Despite the overall global decline (AAPC -0.08 [95 % UI -0.2, 0.03]), certain GBD regions, particularly high-income North America and Central Latin America, have experienced increases in DALY ASRs. The relationship between SDI and MDD burden showed a U-shaped variability, with low-SDI regions consistently exhibiting higher and stable DALY rates. Frontier analysis revealed that several countries, regardless of their SDI, have substantial gaps between observed and potentially achievable DALY rates, indicating areas for targeted intervention to reduce the burden of MDD due to IPV.

CONCLUSIONS

Significant spatial and temporal heterogeneity in MDD due to IPV was observed globally from 1990 to 2019, highlighting the substantial potential for improvement in various countries. Protective measures should be customized to suit the unique cultural contexts, developmental statuses, and regional disparities of each country.

Optimizing precision medicine for second-step depression treatment: a machine learning approach

BACKGROUND

Less than a third of patients with depression achieve successful remission with standard first-step antidepressant monotherapy. The process for determining appropriate second-step care is often based on clinical intuition and involves a protracted course of trial and error, resulting in substantial patient burden and unnecessary delay in the provision of optimal treatment. To address this problem, we adopt an ensemble machine learning approach to improve prediction accuracy of remission in response to second-step treatments.

METHOD

Data were derived from the Level 2 stage of the STAR*D dataset, which included 1439 patients who were randomized into one of seven different second-step treatment strategies after failing to achieve remission during first-step antidepressant treatment. Ensemble machine learning models, comprising several individual algorithms, were evaluated using nested cross-validation on 155 predictor variables including clinical and demographic measures.

RESULTS

The ensemble machine learning algorithms exhibited differential classification performance in predicting remission status across the seven second-step treatments. For the full set of predictors, AUC values ranged from 0.51 to 0.82 depending on the second-step treatment type. Predicting remission was most successful for cognitive therapy (AUC = 0.82) and least successful for other medication and combined treatment options (AUCs = 0.51-0.66).

CONCLUSION

Ensemble machine learning has potential to predict second-step treatment. In this study, predictive performance varied by type of treatment, with greater accuracy in predicting remission in response to behavioral treatments than to pharmacotherapy interventions. Future directions include considering more informative predictor modalities to enhance prediction of second-step treatment response.

Network Analysis of Behavioral Activation/Inhibition Systems and Brain Volume in Individuals With and Without Major Depressive Disorder or Social Anxiety Disorder

BACKGROUND

Social anxiety disorder (SAD) and major depressive disorder (MDD) are characterized by behavioral abnormalities in motivational systems, namely the behavioral inhibition system (BIS) and behavioral activation system (BAS). Limited studies indicate brain volume in regions that support emotion, learning/memory, reward, and cognitive functions relate to BIS/BAS. To increase understanding of BIS/BAS, the current study used a network approach.

METHODS

Patients with SAD (n = 59), patients with MDD (n = 64), and healthy control participants (n = 36) completed a BIS/BAS questionnaire and structural magnetic resonance imaging scans; volumetric regions of interest comprised cortical and limbic structures based on previous BIS/BAS studies. A Bayesian Gaussian graphical model was used for each diagnostic group, and groups were compared. Among network metrics, bridge centrality was of primary interest. Analysis of variance evaluated BIS/BAS behaviors between groups.

RESULTS

Bridge centrality showed hippocampus positively related to BAS, but not to BIS, in the MDD group; no findings were observed in the SAD or control groups. Yet, network density (i.e., overall strength of relationships between variables) and degree centrality (i.e., overall relationship between one variable to all other variables) showed that cortical (e.g., precuneus, medial orbitofrontal) and subcortical (e.g., amygdala, hippocampus) regions differed between diagnostic groups. Analysis of variance results showed BAS was lower in the MDD/SAD groups compared with the control group, while BIS was higher in the SAD group relative to the MDD group, which in turn was higher than the control group.

CONCLUSIONS

Preliminary findings indicate that network-level aberrations may underlie motivational abnormalities in MDD and SAD. Evidence of BIS/BAS differences builds on previous work that points to shared and distinct motivational differences in internalizing psychopathologies.

Process-Based psychotherapy personalization: considering causality with continuous-time dynamic modeling

Psychotherapy can be improved by integrating the study of mediators (how it works) and moderators (for whom it works). To demonstrate this integration, we studied the relationship between resource activation, problem-coping experiences and symptoms in cognitive-behavior therapy (CBT) for depression, to obtain preliminary insights on causal inference (which process leads to symptom improvement?) and prediction (which one for whom?).

A sample of 715 patients with depression who received CBT was analyzed. Hierarchical Bayesian continuous time dynamic modeling was used to study the temporal dynamics between the variables analyzed within the first ten sessions. Depression and self-efficacy at baseline were examined as predictors of these dynamics.

There were significant cross-effects between the processes studied. Under typical assumptions, resource activation had a significant effect on symptom improvement. Problem-coping experience had a significant effect on resource activation. Depression and self-efficacy moderated these effects. However, when system noise was considered, these effects may be affected by other processes.

Resource activation was strongly associated with symptom improvement. To the extent of inferring causality, for patients with mild-moderate depression and high self-efficacy, promoting resource activation can be recommended. For patients with severe depression and low self-efficacy, promoting problem-coping experiences can be recommended.

Predictors and moderators of treatment outcome in late-life anxiety: A systematic review

BACKGROUND

The aim of this review was to identify and critically appraise predictors and moderators of outcomes of psychological and pharmacological treatments for late-life anxiety disorders. Their identification may guide the development of personalised treatments for older people with anxiety disorders.

METHODS

Web of Science, PsychINFO, CINAHL, Embase, and Pubmed were searched for studies published up to 12 May 2022. Randomised controlled trials and observational studies reporting treatment predictors and moderators were included. Participants with a diagnosis of any anxiety disorder who were aged over 60 years were included. Treatment outcomes included response, remission, and change in anxiety score.

RESULTS

Thirteen studies met the inclusion criteria. Twenty-three out of 49 predictors or moderators assessed at post-treatment, and 14 out of 33 predictors or moderators assessed at follow-up were statistically significant. Only one predictor, baseline worry severity at post-treatment, was reported in at least three studies. Most studies were rated as having a low risk of bias in at least three areas and satisfied important quality criteria for predictor and moderator analyses.

LIMITATIONS

Samples were predominantly white, female and highly educated, and most studies were secondary analyses.

CONCLUSIONS

There is evidence that baseline worry severity appears to predict treatment outcome in late-life anxiety disorders. However, this was only explored in psychological intervention studies and therefore its predictive ability in pharmacotherapy remains unknown. Future research should explore predictors and moderators in a range of anxiety disorders and design methodologically-strong and adequately-powered studies with the primary aim of assessing predictors of treatment outcomes.

Hard-to-treat or hard-to-catch? Clinical features and therapeutic outcomes of help-seeking foster care youths with mood disorders

Introduction

The high level of emotional problems in youths placed in foster care contrasts with the limited use of evidence-based treatments. This study aims to better characterize the clinical features and therapeutic outcomes of foster care youths with mood disorders.

Methods

A secondary analysis of data collected in the context of a French-Canadian clinical research network on pediatric mood disorders in four sites was conducted to compare three groups of patients with depressive or bipolar disorder: those without exposure to child welfare intervention (WCWI, n = 181), those who received non-placement psychosocial intervention (NPI, n = 62), and those in placement interventions (PI, n = 41).

Results

We observed a very high rate of academic problems in patients in the groups NPI/PI compared to those in the WCWI group. Patients in the PI group had more disruptive behavioral disorders (OR = 6.87, 95% CI [3.25-14.52]), trauma-related disorders (OR = 3.78, 95% CI [1.6-8.94]), and any neurodevelopmental disorders (OR = 2.73, 95% CI [1.36-5.49]) compared to the other groups (NPI/WCWI). Among inpatients, the Clinical Global Impression-Improvement scale and the change in the Children Global Assessment Scale during the hospital stay did not differ across the three groups. We observed a higher prescription rate of antipsychotics in the PI group compared to the NPI/WCWI groups, but no significant difference for antidepressants and mood stabilizers.

Discussion

These findings support the view that, when provided with dedicated support, fostered inpatient youths can improve in a range comparable to other inpatients. Undetected neurodevelopmental disorders and academic problems are likely important contributors of the burden of mood disorders in these youths.

Relation of serum BDNF to major depression and exploration of mechanistic roles of serum BDNF in a study of vitamin D3 and omega-3 supplements for late-life depression prevention

This study: 1) examined cross-sectional and longitudinal relations of serum brain-derived neurotrophic factor (BDNF) to late-life depression (LLD); 2) tested effects of vitamin D3 and omega-3s on change in BDNF; 3) explored modifying or mediating roles of BDNF on effects of vitamin D3 and omega-3s for LLD. We selected 400 adults from a completed trial of vitamin D3 and omega-3 supplements for LLD prevention. BDNF was measured using an enzyme-linked immunosorbent assay. We administered semi-structured diagnostic interviews and Patient Health Questionnaire [PHQ]-9 to ascertain outcomes at baseline (depression caseness vs. non-caseness; PHQ-9) and at 2-year follow-up among baseline non-depressed individuals (incident vs. no incident MDD; change in PHQ-9). At baseline, while there were no significant differences in mean serum BDNF comparing depression cases and non-cases, being in the lowest vs. highest serum BDNF quartile was significantly associated with worse depressive symptoms. There were no significant longitudinal associations between serum BDNF and LLD. Neither supplement significantly affected change in BDNF; serum BDNF did not appear to modify or mediate treatment effects on LLD. In conclusion, we observed significant cross-sectional but not longitudinal associations between serum BDNF levels and LLD. Vitamin D3 or omega-3s did not alter serum BDNF over 2 years.

Baseline depressive symptoms as predictors of efficacy and tolerability of the treatment with duloxetine: a network analysis approach

Introduction

Depression is considered one of the most prevalent and burdensome mental disorders. Only 50-60% of patients respond to first-line treatment. Individuals with depression might benefit from personalized treatment, tailored to the individual needs of the patient. In this study, we aimed to explore the baseline characteristics of depressive symptoms associated with a good response to duloxetine treatment using a network analysis. Additionally, the relationship between baseline psychopathological symptoms and treatment tolerability was assessed.

Methods

The sample of 88 drug-free patients with active depressive episode, who started monotherapy with increasing doses of duloxetine were evaluated. The Hamilton Depression Rating Scale (HAM-D) was used to assess depression severity and the UKU side effect rating scale to monitor adverse drug reactions (ADRs). A network analysis that explored interactions of specific baseline depression symptoms, treatment efficacy and tolerability was performed.

Results

The node representing duloxetine treatment efficacy was directly connected to the nodes representing the first HAM-D item ("depressed mood") (edge weight = 0.191) and duloxetine dose (edge weight = 0.144). The node representing ADRs was directly connected to only one node representing the baseline score of the HAM-D anxiety (psychic) item (edge weight = 0.263).

Discussion

Our findings indicate that individuals with depression presenting greater levels of depressed mood and lower levels of anxiety symptoms might better respond to the treatment with duloxetine in terms of efficacy and tolerability.

Association of Treatment-Resistant Depression With Patient Outcomes and Health Care Resource Utilization in a Population-Wide Study

Importance

The totality of the societal and individual impact of treatment-resistant depression (TRD) is unknown, as is the potential to prognosticate TRD. The generalizability of many observational studies on TRD is limited.

Objective

To estimate the burden of TRD in a large population-wide cohort in an area with universal health care by including data from both health care types (psychiatric and nonpsychiatric) and, further, to develop a prognostic model for clinical use.

Design, Setting, and Participants

This cohort study, a population-based observational study, assessed data from the Stockholm MDD Cohort for episodes of major depressive disorder (MDD) between 2010 and 2017 that fulfilled predefined criteria for TRD (≥3 consecutive antidepressant treatments). Data analysis was performed from August 2020 to May 2022.

Main Outcomes and Measures

Outcomes were psychiatric and nonpsychiatric comorbid conditions, antidepressant treatments, health care resource utilization, lost workdays, all-cause mortality, and intentional self-harm and, in the prognostic model, TRD.

Results

A total of 158 169 unipolar MDD episodes (in 145 577 patients) were identified between January 1, 2012, and December 31, 2017 (64.7% women; median [IQR] age, 42 years [30-56]). Of these, 12 793 episodes (11%) fulfilled criteria for TRD. The median (IQR) time from the start of MDD episode to TRD was 552 days (294-932). Selective serotonin reuptake inhibitor was the most common class of antidepressant treatment in all treatment steps, and 5907 patients (46.2%) received psychotherapy at some point before initiation of the third pharmacological antidepressant treatment. Compared with matched non-TRD episodes, TRD episodes had more inpatient bed-days (mean, 3.9 days; 95% CI, 3.6-4.1, vs 1.3 days; 95% CI, 1.2-1.4) and more lost workdays (mean, 132.3 days; 95% CI, 129.5-135.1, vs 58.7 days; 95% CI, 56.8-60.6) 12 months after the index date. Anxiety, stress, sleep disorder, and substance use disorder were all more common comorbid conditions in TRD episodes. Intentional self-harm was more than 4 times more common in TRD episodes. The all-cause mortality rate for patients with MDD with TRD episodes was 10.7/1000 person-years at risk, compared with 8.7/1000 person-years at risk for patients with MDD without TRD episodes (hazard ratio, 1.23; 95% CI, 1.07-1.41). Median time from start of the first antidepressant treatment to start of the second, and from start of the second antidepressant treatment to start of the third, was 165 and 197 days, respectively. The severity of MDD, defined using the self-rating Montgomery-Åsberg Depression Rating Scale (MADRS-S) at time of MDD diagnosis, was found to be the most important prognostic factor for TRD (C index = 0.69).

Conclusions and Relevance

In this cohort study, TRD was a common variant of MDD when including patients from both health care types, which is associated with a high disease burden for both patients and society. The median time between initiation of new antidepressant treatments was longer than recommended in current treatment guidelines, suggesting room for more structured and timely depression care.

Relationship of serum estradiol and progesterone with symptoms and sex difference in schizophrenia: A cross-sectional study in Iran

Background

Schizophrenia is a devastating disease characterized by frequent relapses, cognitive decline, and emotional and functional disability, with unknown causes. The phenomenology and clinical course of schizophrenic disorders are different between the two genders, which is thought to be related mainly to the effects of steroid sex hormones on the nervous system. Regarding inconsistencies in the studies, we aimed to compare the levels of estradiol and progesterone between schizophrenia patients and healthy individuals.

Methods

This cross-sectional study was conducted on 66 patients referred to the specialized clinical psychiatric ward of a teaching hospital in the north of Iran, for 5 months in 2021. Thirty-three schizophrenia patients confirmed by a psychiatrist based on DSM5 criteria were included in the case group, and 33 individuals without a psychiatric disease were included in the control group. We completed a demographic information checklist for each patient, along with the Simpson-Angus extrapyramidal side effect scale (SAS) for drug side effects and the positive and negative syndrome scale (PANSS) for the severity of the disease symptoms. Then, a 3-ml blood sample was taken from each participant to determine the serum levels of estradiol and progesterone. The data were analyzed by SPSS16 software.

Results

Thirty-four (51.5%) and 32 (48.5%) participants in this study were male and female, respectively. The mean serum level of estradiol was 22.33 ± 13.65 pm/dl in schizophrenia patients and 29.36 ± 21.32 pm/dl in the control group, showing no significant difference between the two groups (P = 0.4). However, the mean serum level of progesterone was significantly lower in schizophrenia patients (0.37 ± 1.39 pm/dl) than in control subjects (3.15 ± 5.73 pm/dl) (P < 0.001). The PANSS and SAS scores were not significantly correlated with the level of sex hormones (P > 0.05). Serum estradiol and progesterone levels based on sex significantly differed between the two groups (except for female estradiol).

Conclusion

Considering the hormonal differences between schizophrenia patients and control subjects, determining hormonal levels in these patients and using complementary hormonal therapies with estradiol or similar compounds can be beneficial as the starting point of schizophrenia treatment, where therapeutic responses can draw the future developmental framework.

Associations between depression, domain-specific physical activity, and BMI among US adults: NHANES 2011-2014 cross-sectional data

Background

Physical activity is associated with depression. However, benefits of physical activity on depression may differ for specific domains of physical activity (i.e., leisure-time, work, and travel). Moreover, the relationship between physical activity and depression could also differ for people in different Body Mass Index (BMI) categories. This study investigated the relationship between domain-specific physical activity and BMI with depression, and the moderation effects of BMI on the relationship between domain physical activity and depression.

Methods

Complex survey data from the NHANES 2011-2014 was used (N=10,047). Depression was measured using the Patient Health Questionnaire (PHQ-9). Participants reported physical activity minutes in each domain using the Global Physical Activity Questionnaire. Demographic characteristics were self-reported. Weight and height were objectively measured and used for calculating BMI. Survey procedures were used to account for complex survey design. As two survey cycles were used, sampling weights were re-calculated and used for analyses. Taylor series linearisation was chosen as a variance estimation method.

Results

Participants who engaged in ≥150 minutes/week of total moderate-vigorous physical activity (MVPA) (adjusted B = 0.83, 95% CI [0.50, 1.16]) and leisure-time MVPA (adjusted B = 0.84, 95% CI [0.57, 1.11]) experienced lower levels of depression compared to those engaging in <150 MVPA minutes/week. Work and travel-related physical activity were not associated with depression. Overweight (adjusted B = -0.40, 95% CI [-0.76, -0.04]) and underweight/normal weight participants (adjusted B = -0.60, 95%CI [-0.96, -0.25]) experienced less depressive symptoms compared to obese participants. BMI did not moderate the relationship between domain-specific physical activity and depression.

Conclusions

Interventions that focus on leisure-time physical activity appear to be best suited to improve depression, however, this needs to be confirmed in purposefully designed intervention studies. Future studies may also examine ways to improve the effectiveness of work and travel physical activity for reducing depression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14037-4.

Modular-based psychotherapy (MoBa) versus cognitive-behavioural therapy (CBT) for patients with depression, comorbidities and a history of childhood maltreatment: study protocol for a randomised controlled feasibility trial

INTRODUCTION

In depression treatment, most patients do not reach response or remission with current psychotherapeutic approaches. Major reasons for individual non-response are interindividual heterogeneity of etiological mechanisms and pathological forms, and a high rate of comorbid disorders. Personalised treatments targeting comorbidities as well as underlying transdiagnostic mechanisms and factors like early childhood maltreatment may lead to better outcomes. A modular-based psychotherapy (MoBa) approach provides a treatment model of independent and flexible therapy elements within a systematic treatment algorithm to combine and integrate existing evidence-based approaches. By optimally tailoring module selection and application to the specific needs of each patient, MoBa has great potential to improve the currently unsatisfying results of psychotherapy as a bridge between disorder-specific and personalised approaches.

METHODS AND ANALYSIS

In a randomised controlled feasibility trial, N=70 outpatients with episodic or persistent major depression, comorbidity and childhood maltreatment are treated in 20 individual sessions with MoBa or standard cognitive-behavioural therapy for depression. The three modules of MoBa focus on deficits associated with early childhood maltreatment: the systems of negative valence, social processes and arousal. According to a specific questionnaire-based treatment algorithm, elements from cognitive behavioural analysis system of psychotherapy, mentalisation-based psychotherapy and/or mindfulness-based cognitive therapy are integrated for a personalised modular procedure.As a proof of concept, this trial will provide evidence for the feasibility and efficacy (post-treatment and 6-month follow-up) of a modular add-on approach for patients with depression, comorbidities and a history of childhood maltreatment. Crucial feasibility aspects include targeted psychopathological mechanisms, selection (treatment algorithm), sequence and application of modules, as well as training and supervision of the study therapists.

ETHICS AND DISSEMINATION

This study obtained approval from the independent Ethics Committees of the University of Freiburg and the University of Heidelberg. All findings will be disseminated broadly via peer-reviewed articles in scientific journals and contributions to national and international conferences.

TRIAL REGISTRATION NUMBER

DRKS00022093.

Impact of fasting on stress systems and depressive symptoms in patients with major depressive disorder: a cross-sectional study

Major depressive disorder (MDD) is frequently associated with poor response to treatment. Common antidepressants target neurotransmission and neuronal plasticity, which require adequate energy supply. As imaging studies indicate disturbances in central energy metabolism, and caloric restriction improves neuroplasticity and impacts mood and cognition, correction of energy status might increase the effectiveness of antidepressant treatments and reduce the psychopathological symptoms of depression. Metabolic parameters, stress hormones, and brain-derived neurotrophic factor (BDNF) levels were assessed in serum of depressed inpatients (MDD, N = 21) and healthy volunteers (Ctrl, N = 28) before and after a 72 h fasting period during which only water was consumed. Depression severity was assessed by Beck's Depression Inventory (BDI)-2 sum-score and cognitive-affective and somatic sub-scores. Fasting similarly impacted metabolic parameters and stress systems in both groups. Fasting elevated BDI-2 sum-scores and somatic sub-scores in Ctrl. In MDD, fasting increased somatic-, but decreased cognitive-affective symptoms. Sub-group analyses based on BDI-2 sum-scores pre-fasting showed that cognitive-affective symptoms decreased in patients with moderate/severe but not in those with mild symptoms. This was associated with differential changes in BDNF levels. In conclusion, fasting improved cognitive-affective sub-scores in MDD patients with moderate/severe symptoms that had not responded to prior therapy. Interventions that modulate energy metabolism might directly improve cognitive-affective symptoms and/or augment therapeutic efficacy in moderate-to-severely depressed patients.

Influence and interaction of resting state functional magnetic resonance and tryptophan hydroxylase-2 methylation on short-term antidepressant drug response

BACKGROUND

Most antidepressants have been developed on the basis of the monoamine deficiency hypothesis of depression, in which neuronal serotonin (5-HT) plays a key role. 5-HT biosynthesis is regulated by the rate-limiting enzyme tryptophan hydroxylase-2 (TPH2). TPH2 methylation is correlated with antidepressant effects. Resting-state functional MRI (rs-fMRI) is applied for detecting abnormal brain functional activity in patients with different antidepressant effects. We will investigate the effect of the interaction between rs-fMRI and TPH2 DNA methylation on the early antidepressant effects.

METHODS

A total of 300 patients with major depressive disorder (MDD) and 100 healthy controls (HCs) were enrolled, of which 60 patients with MDD were subjected to rs-fMRI. Antidepressant responses was assessed by a 50% reduction in 17-item Hamilton Rating Scale for Depression (HAMD-17) scores at baseline and after two weeks of medication. The RESTPlus software in MATLAB was used to analyze the rs-fMRI data. The amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), fractional ALFF (fALFF), and functional connectivity (FC) were used, and the above results were used as regions of interest (ROIs) to extract the average value of brain ROIs regions in the RESTPlus software. Generalized linear model analysis was performed to analyze the association between abnormal activity found in rs-fMRI and the effect of TPH2 DNA methylation on antidepressant responses.

RESULTS

Two hundred ninety-one patients with MDD and 100 HCs were included in the methylation statistical analysis, of which 57 patients were included in the further rs-fMRI analysis (3 patients were excluded due to excessive head movement). 57 patients were divided into the responder group (n = 36) and the non-responder group (n = 21). Rs-fMRI results showed that the ALFF of the left inferior frontal gyrus (IFG) was significantly different between the two groups. The results showed that TPH2-1-43 methylation interacted with ALFF of left IFG to affect the antidepressant responses (p = 0.041, false discovery rate (FDR) corrected p = 0.149).

CONCLUSIONS

Our study demonstrated that the differences in the ALFF of left IFG between the two groups and its association with TPH2 methylation affect short-term antidepressant drug responses.

Venlafaxine and O-desmethylvenlafaxine serum levels are positively associated with antidepressant response in elder depressed out-patients

BACKGROUND

Therapeutic Drug Monitoring (TDM) represents one of the most promising tools in clinical practice to optimise antidepressant treatment. Nevertheless, little is still known regarding the relationship between clinical efficacy and serum concentration of venlafaxine (VEN). The aim of our study was to investigate the association between serum concentration of venlafaxine + O-desmethylvenlafaxine (SCVO) and antidepressant response (AR).

METHODS

52 depressed outpatients treated with VEN were recruited and followed in a naturalistic setting for three months. Hamilton Depression Rating Scale-21 was administered at baseline, at month 1 and at month 3 to assess AR. SCVO was measured at steady state. Linear regression analysis and nonlinear least-squares regression were used to estimate association between SCVO and AR.

RESULTS

Our results showed an association between AR and SCVO that follows a bell-shaped quadratic function with a progressive increase of AR within the therapeutic reference range of SCVO (i.e. 100-400 ng/mL) and a subsequent decrease of AR at higher serum levels.

DISCUSSION

This study strongly suggests that TDM could represent a more appropriate tool than the oral dosage to optimise the treatment with VEN. Specifically, highest efficacy might be achieved by titrating patients at SCVO levels around 400 ng/mL.

Resting-state functional magnetic resonance imaging-based identification of altered brain the fractional amplitude of low frequency fluctuation in adolescent major depressive disorder patients undergoing electroconvulsive therapy

PURPOSE

While electroconvulsive therapy (ECT) has been repeatedly been shown to effectively and efficiently treat the major depressive disorder (MDD), the mechanistic basis for such therapeutic efficacy remains to be firmly established. As such, further research exploring the ECT-based treatment of MDD in an adolescent population is warranted.

METHODS

This study included 30 treatment-naïve first-episode MDD patients and 30 healthy control (HC) individuals (aged 12-17 years). All participants were scanned using rs-fMRI, and the 30 MDD patients were scanned again after 2 weeks of the ECT treatment period. Intrinsic local activity in each voxel was assessed based on the fractional amplitude of low frequency fluctuation (fALFF) parameter, with all fALFF analyses being completed using the REST application. Correlations between ECT-related changes in fALFF and clinical parameters were additionally examined.

RESULTS

Relative to HCs, MDD patients exhibited increased fALFF values in the right inferior frontal gyrus (ORBinf), inferior occipital gyrus (IOG), and the left middle frontal gyrus (MFG) at baseline. Following ECT, these patients exhibited significant increases in fALFF values in the right medial superior frontal gyrus (SFGmed), dorsolateral superior frontal gyrus (SFGdor), anterior cingulate, and paracingulate gyrus (ACG), median cingulate and paracingulate gyrus (DCG), and left MFG. MDD patient HAMD scores were negatively correlated with fALFF values when analyzing pre-ECT vs. post-HCT ΔHAMD and fALFF values in the right SFGmed, SFGdor, and the left MFG.

CONCLUSION

These data suggest that ECT induced altered fALFF in some regions of the brain, suggesting that these alterations may serve as a neurobiological indicator of ECT effectiveness in MDD adolescents.

Validation of Machine Learning-Based Individualized Treatment for Depressive Disorder Using Target Trial Emulation

This study aims to develop and validate the use of machine learning-based prediction models to select individualized pharmacological treatment for patients with depressive disorder. This study used data from Taiwan’s National Health Insurance Research Database. Patients with incident depressive disorders were included in this study. The study outcome was treatment failure, which was defined as psychiatric hospitalization, self-harm hospitalization, emergency visits, or treatment change. Prediction models based on the Super Learner ensemble were trained separately for the initial and the next-step treatments if the previous treatments failed. An individualized treatment strategy was developed for selecting the drug with the lowest probability of treatment failure for each patient as the model-selected regimen. We emulated clinical trials to estimate the effectiveness of individualized treatments. The area under the curve of the prediction model using Super Learner was 0.627 and 0.751 for the initial treatment and the next-step treatment, respectively. Model-selected regimens were associated with reduced treatment failure rates, with a 0.84-fold (95% confidence interval (CI) 0.82–0.86) decrease for the initial treatment and a 0.82-fold (95% CI 0.80–0.83) decrease for the next-step. In emulation of clinical trials, the model-selected regimen was associated with a reduced treatment failure rate.

Moderators and predictors of treatment outcome in transdiagnostic group cognitive-behavioral therapy for primary care patients with emotional disorders

OBJECTIVE

Transdiagnostic group cognitive behavior therapy (TD-GCBT) has shown to be efficacious in the treatment of emotional disorders in primary care. However, little is known about possible moderators or predictors of treatment outcome. We aimed to explore the potential predictors and moderators of outcome in a large multicentre randomized controlled trial comparing TD-GCBT plus treatment as usual (TAU) to TAU alone.

METHOD

Putative demographic and baseline clinical variables were examined using the PROCESS macro as potential predictors/moderators of depressive and anxiety symptoms at posttreatment and 1-year follow-up.

RESULTS

Analyses were based on a study completer sample of 1061 participants randomized to TD-CBT + TAU (n = 527) or TAU alone (n = 534), with 631 participants assessed at the posttreatment evaluation and 388 at the 1-year follow-up. Individuals working or with a partner among sociodemographic variables, and higher baseline comorbidities and more severity of symptoms among clinical variables obtained more benefits from adding TDCBT to TAU. Those taking medication before treatment obtained less benefits from the TD-GCBT than those without prescribed antidepressant medications, after controlling for baseline severity of symptoms. Overall, the moderating effect of clinical (but not sociodemographic) variables remained at 1-year follow-up.

CONCLUSION

Findings support largely the generalization of the TD-GCBT for emotional disorders in primary care to a variety of sociodemographic and clinical groups. However, TD-GCBT seems to work to a greater extent for those individuals with a more severe clinical profile. Providing TD-GCBT before prescribing antidepressant medication and while people are still working may enhance the effects of adding this psychological treatment to TAU in primary care.

Assessment of a Prediction Model for Antidepressant Treatment Stability Using Supervised Topic Models

Importance

In the absence of readily assessed and clinically validated predictors of treatment response, pharmacologic management of major depressive disorder often relies on trial and error.

Objective

To assess a model using electronic health records to identify predictors of treatment response in patients with major depressive disorder.

Design, Setting, and Participants

This retrospective cohort study included data from 81 630 adults with a coded diagnosis of major depressive disorder from 2 academic medical centers in Boston, Massachusetts, including outpatient primary and specialty care clinics from December 1, 1997, to December 31, 2017. Data were analyzed from January 1, 2018, to March 15, 2020.

Exposures

Treatment with at least 1 of 11 standard antidepressants.

Main Outcomes and Measures

Stable treatment response, intended as a proxy for treatment effectiveness, defined as continued prescription of an antidepressant for 90 days. Supervised topic models were used to extract 10 interpretable covariates from coded clinical data for stability prediction. With use of data from 1 hospital system (site A), generalized linear models and ensembles of decision trees were trained to predict stability outcomes from topic features that summarize patient history. Held-out patients from site A and individuals from a second hospital system (site B) were evaluated.

Results

Among the 81 630 adults (56 340 women [69%]; mean [SD] age, 48.46 [14.75] years; range, 18.0-80.0 years), 55 303 reached a stable response to their treatment regimen during follow-up. For held-out patients from site A, the mean area under the receiver operating characteristic curve (AUC) for discrimination of the general stability outcome was 0.627 (95% CI, 0.615-0.639) for the supervised topic model with 10 covariates. In evaluation of site B, the AUC was 0.619 (95% CI, 0.610-0.627). Building models to predict stability specific to a particular drug did not improve prediction of general stability even when using a harder-to-interpret ensemble classifier and 9256 coded covariates (specific AUC, 0.647; 95% CI, 0.635-0.658; general AUC, 0.661; 95% CI, 0.648-0.672). Topics coherently captured clinical concepts associated with treatment response.

Conclusions and Relevance

The findings suggest that coded clinical data available in electronic health records may facilitate prediction of general treatment response but not response to specific medications. Although greater discrimination is likely required for clinical application, the results provide a transparent baseline for such studies.

Study protocol of the multi-centre, randomised controlled trial of the Frankfurt Early Intervention Programme A-FFIP versus early intervention as usual for toddlers and preschool children with Autism Spectrum Disorder (A-FFIP study)

BACKGROUND

Naturalistic developmental behavioural interventions (NDBI) have been shown to improve autism-specific symptoms in young children with Autism Spectrum Disorder (ASD). NDBI approaches, such as the ASD-specific Frankfurt Early Intervention Programme for ASD (A-FFIP), are based on ASD-specific developmental and learning aspects. A-FFIP is a low-intensity intervention which can easily be implemented in the local health care/social welfare system. The aim of the present study is to establish 1-year efficacy of the manualised early intervention programme A-FFIP in toddlers and preschool children with ASD. It is hypothesised that A-FFIP will result in improved ASD-specific symptoms compared to early intervention as usual (EIAU). Child- and family-specific secondary outcomes, as well as moderators and mediators of outcome, will be explored.

METHODS/DESIGN

A prospective, multi-centre, parallel-group, randomised controlled, phase-III trial comparing A-FFIP versus EIAU. A total of 134 children (A-FFIP: 67, EIAU: 67) aged 24-66 months at baseline assessment meeting the criteria for ASD (DSM-5) will be included. The primary outcome is the absolute change of the total score of the Brief Observation of Social Communication Change (BOSCC-AT) between baseline (T2) and 1-year follow-up (T6). The treatment effect will be tested, adjusted for relevant covariates applying a mixed model for repeated measures. Secondary outcomes are BOSCC social communication and repetitive-behaviour scores, single ASD symptoms, language, cognition, psychopathology, parental well-being and family quality of life. Predictors, moderators and mediating mechanisms will be explored.

DISCUSSION

If efficacy of the manualised A-FFIP early intervention is established, the current study has the potential to change clinical practice strongly towards the implementation of a low-intensity, evidence-based, natural early intervention in ASD. Early intervention in ASD requires specialist training, which subsequently needs to be developed or included into current training curricula.

TRIAL REGISTRATION

German Registry for Clinical Trials (Deutscher Register Klinischer Studien, DRKS); ID: 00016330. Retrospectively registered on 4 January 2019. URL: https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00016330.

Moderators and mediators of outcome in treatments for anorexia nervosa and bulimia nervosa in adolescents: A systematic review of randomized controlled trials

OBJECTIVE

To critically appraise papers reporting on moderators and mediators of recommended psychological treatments for anorexia nervosa (AN) and bulimia nervosa (BN) in adolescents.

METHOD

A systematic search of databases was conducted including PsycINFO, Embase, MEDLINE, AMED, CINAHL, and the Cochrane Library. Studies were included where a randomized controlled trial (RCT) compared therapies for AN or BN and reported on moderators or mediators of treatment effect. Twenty-one eligible papers were included, all based on data from eight RCTs.

RESULTS

Family therapies were dominant in the literature. Individual or separated treatment appeared superior for families with more difficult relationships, whereas conjoint family treatment appeared to be superior where good family relationships were reported. Where there was greater eating disorder psychopathology in AN, including eating disorder-related obsessions and compulsions, the response was better to a family approach than to individual therapies. There was some evidence that a family treatment was superior for those engaging in purging behaviors in BN. Measures of family relationships, parental self-efficacy, and early change emerged as possible mediators; however, the quality of evidence was mixed and the findings, in some cases, arguably circular. Moderator and mediator analyses were underpowered in all studies, with multiple, and post-hoc, analyses being run, and a broad range of outcome measures used.

DISCUSSION

This review recommends that emerging findings are explored further in adequately powered trials of the different recommended therapies, with a move toward focusing on effect sizes. A consensus on acceptable definitions of outcome, including remission and recovery, would benefit future research.

Speech-Language Pathologists' Knowledge and Consideration of Factors That May Predict, Moderate, and Mediate AAC Outcomes

The aims of this study were to examine speech-language pathologists' (SLPs) knowledge and consideration of factors found in research when making clinical decisions regarding AAC for children with Autism Spectrum Disorder (ASD), and to reveal additional factors identified based on SLPs' clinical practice. A 20-question mixed-methods survey was completed internationally by 187 certified SLPs. Overall, SLPs showed some familiarity with the research and considered factors found in research when making clinical decisions. SLPs also identified 20 factors that were not identified in the most recent systematic review that may predict, moderate, and/or mediate outcomes. This information may contribute to advancing clinical services regarding AAC as well as guide future research investigating the mechanisms by which children with ASD respond to AAC interventions.

The negative effects of social bond disruption are partially ameliorated by sertraline administration in prairie voles

Negative social experiences influence both depression and cardiovascular dysfunction. Many individuals who experience negative mood states or cardiovascular conditions have limited social support. Therefore, investigation of drug treatments that may protect against the consequences of social stress will aid in designing effective treatment strategies. The current study used an animal model to evaluate the protective effect of sertraline administration on behavioral and cardiovascular consequences of social stress. Specifically, male prairie voles (Microtus ochrogaster), which are socially monogamous rodents that share several behavioral and physiological characteristics with humans, were isolated from a socially-bonded female partner, and treated with sertraline (16 mg/kg/day, ip) or vehicle during isolation. Unexpectedly, sertraline did not protect against depression-relevant behaviors, and it was associated with increased short- and long-term heart rate responses. However, sertraline administration improved heart rate variability recovery following a behavioral stressor, including increased parasympathetic regulation, and altered long-term neuronal activity in brain regions that modulate autonomic control and stress reactivity. These results indicate that sertraline may partially protect against the consequences of social stressors, and suggest a mechanism through which sertraline may beneficially influence neurobiological control of cardiac function.

Duloxetine plasma level and antidepressant response

BACKGROUND

Major Depressive Disorder (MDD) is associated with a high rate of inadequate treatment response, which is mainly due to the large inter-individual genetic variability in pharmacokinetic and pharmacodynamic targets of antidepressant drugs. Little is still known about the exact association between plasma level of first-line antidepressants and clinical response. This is particularly true for duloxetine, a dual serotonin and norepinephrine reuptake inhibitor recommended as first-line treatment for MDD. The aim of this study was to investigate the association between serum concentration of duloxetine (SCD) and antidepressant response (AR).

METHODS

66 MDD patients treated with duloxetine 60 mg/day monotherapy were recruited in an outpatient setting and followed for three months. Hamilton Depression Rating Scale - 21 (HAMD-21) was administrated at baseline, at month 1, and at month 3 to assess AR. SCD was measured at steady state. Linear regression analysis and nonlinear least-squares regression were used to estimate association between SCD and AR.

RESULTS

SCD showed a high inter-individual variability in our sample, despite the duloxetine fixed oral dosage. We found a strong association between SCD and AR following a bell-shaped function at month 1 and at month 3. Nonetheless, within the recommended SCD range of 30-120 ng/mL a more linear correlation between SCD and AR was observed.

DISCUSSION

Our results suggest that for duloxetine the association between SCD and AR likely follows a bell-shaped quadratic function with poor AR at subtherapeutic SCD and progressive decrease of AR at higher SCD. The maximum antidepressant efficacy seems to require SCD values next to the highest recommended SCD (30-120 ng/mL), probably because of the optimal saturation of both serotonin and norepinephrine transporters. Thus, taking into account the observed high interindividual variability of SCD, our findings suggest that for MDD patients treated with duloxetine, SCD could be a useful tool to guide the treatment by optimizing the oral dosage in order to increase the AR rate.

Brain-derived neurotrophic factor as a possible predictor of electroconvulsive therapy outcome

While brain-derived neurotrophic factor (BDNF) has been shown to predict response to pharmacotherapy in depression, studies in electroconvulsive therapy (ECT) are small and report conflicting results. This study assesses the association between pre-treatment BDNF levels and ECT outcome in severe late-life unipolar depression (LLD). The potential of BDNF as a clinical predictor of ECT outcome was subsequently evaluated. Characteristics associated with low and high BDNF subgroups were determined as well. Ninety-four patients diagnosed with LDD referred for ECT were included. Fasting serum BDNF levels were determined before ECT. Remission and response, measured with the Montgomery-Åsberg Depression Rating Scale, were the outcomes. The association between BDNF and ECT outcome was analysed with logistic regression and Cox regression. The clinical usefulness of BDNF was evaluated using the receiver operating characteristic (ROC) curve. Associations between clinical characteristics and low versus high BDNF levels were examined with T tests, chi-squared tests and Mann-Whitney tests. The odds of remission decreased with 33% for every five units increase of BDNF levels (OR 0.67, 95% confidence interval 0.47-0.96; p = 0.03); however, neither the association with time to remission nor the associations with response nor the adjusted models were significant. The area under the ROC (0.66) implied a poor accuracy of BDNF as a clinical test. Clinical characteristics associated with BDNF were inclusion site, physical comorbidities and duration of the index episode. To conclude, although there is an association between pre-treatment BDNF levels and ECT outcome, BDNF cannot be considered an eligible biomarker for ECT outcome in clinical practice.

General Predictors and Moderators of Depression Remission: A VAST-D Report

OBJECTIVE

Almost two-thirds of patients with major depressive disorder do not achieve remission with initial treatments. Thus, identifying and providing effective, feasible, and safe "next-step" treatments are clinical imperatives. This study explores patient baseline features that might help clinicians select between commonly used next-step treatments.

METHODS

The authors used data from the U.S. Department of Veterans Affairs (VA) Augmentation and Switching Treatments for Improving Depression Outcomes (VAST-D) study, a multisite, randomized, single-blind trial of 1,522 Veterans Health Administration patients who did not have an adequate response to at least one course of antidepressant treatment meeting minimal standards for dosage and duration. For 12 weeks, participants received one of three possible next-step treatments: switch to another antidepressant-sustained-release bupropion; combination with another antidepressant-sustained-release bupropion; or augmentation with an antipsychotic-aripiprazole. Life table regression models were used to identify baseline characteristics associated with remission overall (general predictors) and their interaction with remission among the three treatment groups (moderators).

RESULTS

Remission was more likely for individuals who were employed, less severely and chronically depressed, less anxious, not experiencing complicated grief symptoms, did not experience childhood adversity, and had better quality of life and positive mental health. Two features suggested specific next-step treatment selections: age ≥65 years (for whom augmentation with aripiprazole was more effective than switch to bupropion) and severe mixed hypomanic symptoms (for which augmentation with aripiprazole and combination with bupropion were more effective than switch to bupropion).

CONCLUSIONS

If replicated, these preliminary findings could help clinicians determine which patients with depression requiring next-step treatment will benefit most from a specific augmentation, combination, or switching strategy.

Childhood adversities, negative life events and outcomes of non-pharmacological treatments for depression in primary care: A secondary analysis of a randomized controlled trial

Non-pharmacological treatments for depression are effective and available in primary care, but useful prognostic factors are lacking. Childhood adversities (CA) and negative recent life events (RLE) increase the risk and severity of depression, though their effect on treatment outcomes remains understudied. Using a sample of 737 adult participants of a multicenter randomized controlled trial receiving physical exercise, internet based cognitive-behavioral therapy or treatment as usual, alone or in combination with antidepressants, this prospective study aimed to determine the impact of CA, RLE and their interaction as predictors of outcomes of non-pharmacological treatments for mild-moderate depression in primary care. Outcomes were depression severity (MADRS score) and response to treatment (≥50% reduction in MADRS score) after three months. Linear regression and modified Poisson regression were used, interaction was assessed with a product term (CA*RLE) and epidemiological measures of interaction. The number of CA and RLE were associated with higher depression severity at follow-up (CA: β = 0.79, 95% CI: 0.14 to 1.44 and RLE: β = 0.52, 95% CI: 0.14 to 0.72) and showed a trend towards lower rates of response to treatment (RR = 0.94, 95% CI: 0.86 to 1.03; and RLE: RR = 0.95, 95% CI: 0.90 to 0.99). Interaction between CA and RLE was not significant for depression severity (β = 0.10, 95% CI: -2.12 to 0.41) nor for response to treatment (RERI = -0.05, 95% CI = -0.33 to 0.24). CA and RLE are associated with worse outcomes of non-pharmacological treatments in primary care. Further studies to identify predictors of outcomes of non-pharmaological treatments for depression are needed.

How to choose an antidepressant medication

OBJECTIVE

We consider how to choose an antidepressant (AD) medication for the treatment of clinical depression.

METHOD

A narrative review was undertaken addressing antidepressant 'choice' considering a range of parameters either weighted by patients and clinicians or suggested in the scientific literature. Findings were synthesised and incorporated with clinical experience into a model to assist AD choice.

RESULTS

Efficacy studies comparing ADs offer indicative guidance, while precision psychiatry prediction based on genetics, developmental trauma, neuroimaging, behavioural and cognitive biomarkers, currently has limited clinical utility. Our model offers guidance for AD choice by assessing first for the presence of a depressive subtype or symptom cluster and matching choice of AD class accordingly. Failing this, an AD can be chosen based on depression severity. Within-class choice can be determined by reference to personality style, patient preference, medical or psychiatric comorbidities and side-effect profile.

CONCLUSION

Clarification of AD choice would occur if medications are trialled in specific depressive subtypes rather than using the generic diagnosis of major depressive disorder (MDD). Such 'top-down' methods could be enhanced by 'bottom-up' studies to classify individuals according to symptom clusters and biomarkers with AD efficacy tested in these categories. Both methods could be utilised for personalised AD choice.

Prefrontal networks dynamically related to recovery from major depressive disorder: a longitudinal pharmacological fMRI study

Due to lacking predictors of depression recovery, successful treatment of major depressive disorder (MDD) is frequently only achieved after therapeutic optimization leading to a prolonged suffering of patients. This study aimed to determine neural prognostic predictors identifying non-remitters prior or early after treatment initiation. Moreover, it intended to detect time-sensitive neural mediators indicating depression recovery. This longitudinal, interventional, single-arm, open-label, phase IV, pharmacological functional magnetic resonance imaging (fMRI) study comprised four scans at important stages prior (day 0) and after escitalopram treatment initiation (day 1, 28, and 56). Totally, 22 treatment-free MDD patients (age mean ± SD: 31.5 ± 7.7; females: 50%) suffering from a concurrent major depressive episode without any comorbid DSM-IV axis I diagnosis completed the study protocol. Primary outcome were neural prognostic predictors of depression recovery. Enhanced de-activation of anterior medial prefrontal cortex (amPFC, single neural mediator) indicated depression recovery correlating with MADRS score and working memory improvements. Strong dorsolateral PFC (dlPFC) activation and weak dlPFC-amPFC, dlPFC-posterior cingulate cortex (PCC), dlPFC-parietal lobe (PL) coupling (three prognostic predictors) hinted at depression recovery at day 0 and 1. Preresponse prediction of continuous (dlPFC-PL: R²_day1 = 55.9%, 95% CI: 22.6-79%, P < 0.005) and dichotomous (specificity/sensitivity: SP/SN_day1 = 0.91/0.82) recovery definitions remained significant after leave-one-out cross-validation. Identified prefrontal neural predictors might propel the future development of fMRI markers for clinical decision making, which could lead to increased response rates and adherence during acute phase treatment periods. Moreover, this study underscores the importance of the amPFC in depression recovery.

A systematic meta-review of predictors of antidepressant treatment outcome in major depressive disorder

INTRODUCTION

The heterogeneity of symptoms and complex etiology of depression pose a significant challenge to the personalization of treatment. Meanwhile, the current application of generic treatment approaches to patients with vastly differing biological and clinical profiles is far from optimal. Here, we conduct a meta-review to identify predictors of response to antidepressant therapy in order to select robust input features for machine learning models of treatment response. These machine learning models will allow us to learn associations between patient features and treatment response which have predictive value at the individual patient level; this learning can be optimized by selecting high-quality input features for the model. While current research is difficult to directly apply to the clinic, machine learning models built using knowledge gleaned from current research may become useful clinical tools.

METHODS

The EMBASE and MEDLINE/PubMed online databases were searched from January 1996 to August 2017, using a combination of MeSH terms and keywords to identify relevant literature reviews. We identified a total of 1909 articles, wherein 199 articles met our inclusion criteria.

RESULTS

An array of genetic, immune, endocrine, neuroimaging, sociodemographic, and symptom-based predictors of treatment response were extracted, varying widely in clinical utility.

LIMITATIONS

Due to heterogeneous sample sizes, effect sizes, publication biases, and methodological disparities across reviews, we could not accurately assess the strength and directionality of every predictor.

CONCLUSION

Notwithstanding our cautious interpretation of the results, we have identified a multitude of predictors that can be used to formulate a priori hypotheses regarding the input features for a computational model. We highlight the importance of large-scale research initiatives and clinically accessible biomarkers, as well as the need for replication studies of current findings. In addition, we provide recommendations for future improvement and standardization of research efforts in this field.

Predictors of the effectiveness of an early medication change strategy in patients with major depressive disorder

BACKGROUND

Patients with Major Depressive Disorder (MDD) who are non-improvers after two weeks of antidepressant treatment have a high risk of treatment failure. Recently, we did not find differences in outcomes in non-improvers randomized to an early medication change (EMC) strategy compared to treatment as usual (TAU). This secondary analysis investigated possible predictors of higher remission rates in the EMC strategy.

METHODS

Of 192 non-improvers (i.e. decrease of ≤20% on the HAMD-17 depression scale) after a two-week treatment with escitalopram, n = 97 were randomized to EMC (immediate switch to high doses of venlafaxine XR) and n = 95 to TAU (continued escitalopram until day 28 with non-responders switched to venlafaxine XR). We first analyzed patient characteristics, psychopathological features and subtypes of MDD by logistic regression analyses as possible predictors of remission rates. In a second investigation, we analyzed the predictors, which showed a significant association in the first analysis before Bonferroni-Holm correction by chi-squared tests separated for treatment groups. All analyses were corrected by Bonferroni-Holm method.

RESULTS

The first analyses yielded no statistically significant results after correction for multiple testing. In the second analyses, however, patients with prior medication at study entry showed higher remission rates in EMC than in TAU (24.2% versus 8.6%, p = 0.017; Bonferroni-Holm corrected significance level: p = 0.025.). Furthermore, patients with a recurrent course of MDD benefited less from treatment as usual (p = 0.009; Bonferroni-Holm corrected significance level: p = 0.025). Age, sex, age of onset, psychiatric or somatic comorbidities, and other subtypes of MDD did not predict remission rates.

CONCLUSIONS

Although in our first analysis we found statistically non-significant results, the second analysis showed significant differences in remission rates between patients with or without previous medication and in patients with recurrent MDD or the first depressive episode. It would therefore be valuable to examine in larger and prospective studies whether remission rates can be increased by quick escalation of treatment in certain subgroups of patients. Promising subgroups to be tested are patients who were previously medicated, and who show a recurrent course of MDD.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT00974155 . Registered at the 10th of September 2009. Retrospectively registered.

A multicentre randomized controlled trial on trans-generational attention deficit/hyperactivity disorder (ADHD) in mothers and children (AIMAC): an exploratory analysis of predictors and moderators of treatment outcome

OBJECTIVE

We examined predictors and moderators of treatment outcome in mothers and children diagnosed with ADHD in a large multicentre RCT.

METHOD

In total, 144 mother-child dyads with ADHD were randomly assigned to either a maternal ADHD treatment (group psychotherapy and open methylphenidate medication, TG) or to a control treatment (individual counselling without psycho- or pharmacotherapy, CG). After maternal ADHD treatment, parent-child training (PCT) for all mother-child dyads was added. The final analysis set was based on 123 dyads with completed primary outcome assessments (TG: n = 67, CG: n = 56). The primary outcome was the change in each child's externalizing symptoms. Multiple linear regression analyses were performed.

RESULTS

The severity of the child's externalizing problem behaviour in the family at baseline predicted more externalizing symptoms in the child after PCT, independent of maternal treatment. When mothers had a comorbid depression, TG children showed more externalizing symptoms after PCT than CG children of depressive mothers. No differences between the treatment arms were seen in the mothers without comorbid depression.

CONCLUSIONS

Severely impaired mothers with ADHD and depressive disorder are likely to need additional disorder-specific treatment for their comorbid psychiatric disorders to effectively transfer the contents of the PCT to the home situation (CCTISRCTN73911400).

Assessing bipolar disorder in the older adult: the GERI-BD toolbox

INTRODUCTION

The evidence base regarding characteristics of older adults with bipolar disorder (BD) remains limited. The NIH-funded multicenter study Acute Pharmacotherapy of Late-Life Mania (GERI-BD) assessed various clinical domains before and during mood stabilizer treatment in older adults participating in a 9-week, double-blind randomized controlled trial. We describe the rationale for selecting these instruments.

METHODS

Domains and instruments were selected on the basis of the study design and the participants. The investigators' experience in clinical trials involving young adults with BD or older adults with major depressive disorder, along with open studies of older adults with BD, contributed to the selection process.

RESULTS

We identified domains and selected instruments that could be used to assess the participants given their diagnostic, treatment history, and medical and mood state characteristics. They were also intended to measure tolerability and efficacy and permit examination of potential moderating and mediating factors.

CONCLUSIONS

Decisions regarding the assessment domains to be included in the clinical trial highlight the challenges facing researchers studying drug treatments for older adults with BD, or more generally, mood disorders. We suggest that the domains and instruments selected by GERI-BD investigators constitute a "toolbox" that can be customized for other investigators. Copyright © 2017 John Wiley & Sons, Ltd.

Prediction of treatment outcomes to exercise in patients with nonremitted major depressive disorder

BACKGROUND

Only one-third of patients with major depressive disorder (MDD) achieve remission with initial treatment. Consequently, current clinical practice relies on a "trial-and-error" approach to identify an effective treatment for each patient. The purpose of this report was to determine whether we could identify a set of clinical and biological parameters with potential clinical utility for prescription of exercise for treatment of MDD in a secondary analysis of the Treatment with Exercise Augmentation in Depression (TREAD) trial.

METHODS

Participants with nonremitted MDD were randomized to one of two exercise doses for 12 weeks. Participants were categorized as "remitters" (≤12 on the IDS-C), nonresponders (<30% drop in IDS-C), or neither. The least absolute shrinkage and selection operator (LASSO) and random forests were used to evaluate 30 variables as predictors of both remission and nonresponse. Predictors were used to model treatment outcomes using logistic regression.

RESULTS

Of the 122 participants, 36 were categorized as remitters (29.5%), 56 as nonresponders (45.9%), and 30 as neither (24.6%). Predictors of remission were higher levels of brain-derived neurotrophic factor (BDNF) and IL-1B, greater depressive symptom severity, and higher postexercise positive affect. Predictors of treatment nonresponse were low cardiorespiratory fitness, lower levels of IL-6 and BDNF, and lower postexercise positive affect. Models including these predictors resulted in predictive values greater than 70% (true predicted remitters/all predicted remitters) with specificities greater than 25% (true predicted remitters/all remitters).

CONCLUSIONS

Results indicate feasibility in identifying patients who will either remit or not respond to exercise as a treatment for MDD utilizing a clinical decision model that incorporates multiple patient characteristics.

Escitalopram plasma levels and antidepressant response

Major Depression Disorder (MDD) has a highly variable treatment response due to the large inter-individual variation in the pharmacokinetics and pharmacodynamics of drug treatments. In detail the correlation between plasma level and efficacy has been much debated. Among first-line drugs for MDD, one of the most used is escitalopram. In the present study we investigated the association between serum concentration of escitalopram (SCE) and antidepressant response (AR). 70 MDD patients treated with escitalopram monotherapy were recruited and followed for three months. Hamilton Depression Rating Scale - 21 (HAMD-21) was administrated at baseline, month 1, and month 3 to assess AR. SCE was measured at steady state. Linear regression analysis and nonlinear least-squares regression were used to estimate association between SCE and AR. We found an association between SCE and AR both at month 1 (p<0.001) and month 3 (p=0.0003), which persists also excluding 3 patients with SCE equal to 0. Interestingly, by excluding patients with SCE < 20ng/mL, i.e. with a SCE lower than the putative therapeutic threshold, these associations disappeared. The curvilinear function AR = a + (SCE-SCE²) explained a higher proportion of variance compared to the linear other models (p<0.001). Our results suggest that for escitalopram the association between SCE and AR likely follows a nearly-asymptotic function, with poor AR at sub-therapeutic SCE and stable AR response at therapeutic SCE. Thus, when a patient reaches the therapeutic SCE range, further increase of escitalopram dosage seems to be useless, although further studies are needed to confirm our findings.

Translational Identification of Transcriptional Signatures of Major Depression and Antidepressant Response

Major depressive disorder (MDD) is a highly prevalent mental illness whose therapy management remains uncertain, with more than 20% of patients who do not achieve response to antidepressants. Therefore, identification of reliable biomarkers to predict response to treatment will greatly improve MDD patient medical care. Due to the inaccessibility and lack of brain tissues from living MDD patients to study depression, researches using animal models have been useful in improving sensitivity and specificity of identifying biomarkers. In the current study, we used the unpredictable chronic mild stress (UCMS) model and correlated stress-induced depressive-like behavior (n = 8 unstressed vs. 8 stressed mice) as well as the fluoxetine-induced recovery (n = 8 stressed and fluoxetine-treated mice vs. 8 unstressed and fluoxetine-treated mice) with transcriptional signatures obtained by genome-wide microarray profiling from whole blood, dentate gyrus (DG), and the anterior cingulate cortex (ACC). Hierarchical clustering and rank-rank hypergeometric overlap (RRHO) procedures allowed us to identify gene transcripts with variations that correlate with behavioral profiles. As a translational validation, some of those transcripts were assayed by RT-qPCR with blood samples from 10 severe major depressive episode (MDE) patients and 10 healthy controls over the course of 30 weeks and four visits. Repeated-measures ANOVAs revealed candidate trait biomarkers (ARHGEF1, CMAS, IGHMBP2, PABPN1 and TBC1D10C), whereas univariate linear regression analyses uncovered candidates state biomarkers (CENPO, FUS and NUBP1), as well as prediction biomarkers predictive of antidepressant response (CENPO, NUBP1). These data suggest that such a translational approach may offer new leads for clinically valid panels of biomarkers for MDD.

Pharmacogenetics and Imaging-Pharmacogenetics of Antidepressant Response: Towards Translational Strategies

Genetic variation underlies both the response to antidepressant treatment and the occurrence of side effects. Over the past two decades, a number of pharmacogenetic variants, among these the SCL6A4, BDNF, FKBP5, GNB3, GRIK4, and ABCB1 genes, have come to the forefront in this regard. However, small effects sizes, mixed results in independent samples, and conflicting meta-analyses results led to inherent difficulties in the field of pharmacogenetics translating these findings into clinical practice. Nearly all antidepressant pharmacogenetic variants have potentially pleiotropic effects in which they are associated with major depressive disorder, intermediate phenotypes involved in emotional processes, and brain areas affected by antidepressant treatment. The purpose of this article is to provide a comprehensive review of the advances made in the field of pharmacogenetics of antidepressant efficacy and side effects, imaging findings of antidepressant response, and the latest results in the expanding field of imaging-pharmacogenetics studies. We suggest there is mounting evidence that genetic factors exert their impact on treatment response by influencing brain structural and functional changes during antidepressant treatment, and combining neuroimaging and genetic methods may be a more powerful way to detect biological mechanisms of response than either method alone. The most promising imaging-pharmacogenetics findings exist for the SCL6A4 gene, with converging associations with antidepressant response, frontolimbic predictors of affective symptoms, and normalization of frontolimbic activity following antidepressant treatment. More research is required before imaging-pharmacogenetics informed personalized medicine can be applied to antidepressant treatment; nevertheless, inroads have been made towards assessing genetic and neuroanatomical liability and potential clinical application.

Cognitive effects of transcranial direct current stimulation in depression: Results from the SELECT-TDCS trial and insights for further clinical trials

BACKGROUND

Cognitive dysfunction treatment remains an unmet clinical need in major depressive disorder (MDD). Transcranial direct current stimulation (tDCS) may improve cognitive symptoms in MDD. Our aim was to investigate the cognitive effects of tDCS in the Sertraline vs. Electric Current Therapy for Treating Depression Clinical Study (SELECT-TDCS). We also explored whether tDCS could have mood-independent cognitive effects.

METHODS

One hundred twenty MDD patients aged from 18 to 65 years received 12 sessions of active/sham tDCS (2mA for 30min) and real/placebo 50mg/d sertraline over 6 weeks in a factorial trial. We analyzed whether changes in performance of neuropsychological tests (Trail Making, Digit Span, Stroop Task, Mini-Mental Status Exam and Montreal Cognitive Assessment) occurred over time, according to treatment group and depression improvement. Exploratory analyses were carried out to verify the influence of clinical and demographic variables on the outcomes.

RESULTS

Cognitive improvement was showed in most tests used, although they occurred regardless of intervention type and depression improvement. Further exploratory analyses revealed that clinical response and education level could have mediated pro-cognitive tDCS effects on some of the tests used.

LIMITATIONS

The neuropsychological battery used might not have been sensitive to detect tDCS-induced effects on cognition. Lack of simultaneous cognitive training during application may have also limited its cognitive effects.

CONCLUSIONS

We found no evidence of beneficial or deleterious cognitive effects of tDCS as a treatment for depression. We discussed clinical trial design considerations for further tDCS studies assessing cognitive effects, including sample and outcomes considerations.

The establishment of the objective diagnostic markers and personalized medical intervention in patients with major depressive disorder: rationale and protocol

BACKGROUND

Major depressive disorders (MDD) is a common mental disorder with high prevalence, frequent relapse and associated with heavy disease burden. Heritability, environment and their interaction play important roles in the development of MDD. MDD patients usually display a wide variation in clinical symptoms and signs, while the diagnosis of MDD is relatively subjective. The treatment response varies substantially between different subtypes of MDD patients and only half respond adequately to the first antidepressant. This study aims to define subtypes of MDD, develop multi-dimension diagnostic test and combined predictors for improving the diagnostic accuracy and promoting personalized intervention in MDD patients.

METHODS/DESIGN

This is a multi-center, multi-stage and prospective study. The first stage of this study is a case-control study, aims to explore the risk factors for developing MDD and then define the subtypes of MDD using 1200 MDD patients and 1200 healthy controls with a set of questionnaire. The second stage is a diagnostic test, aims to indentify and replicate the potential indicators to assist MDD diagnosis using 600 MDD patients and 300 healthy controls from the first stage with a set of questionnaire, neuropsychological assessment and a series of biomarkers. The third stage is a 96-week longitudinal study, including 8-week acute period treatment and 88-week stable period treatment, aims to identify overall predictors of treatment effectiveness on MDD at week 8 post treatment and to explore the predictors on MDD prognosis in the following 2 years using 600 MDD patients from the first stage with a set of questionnaire, neuropsychological assessment and a series of biomarkers. The primary outcome measure is the change of the total score of 17-Item Hamilton Rating Scale for Depression.

DISCUSSION

This study will provide strong and suitable evidence for enhancing the accuracy of MDD diagnosis and promoting personalized treatment for MDD patients in clinical practice.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT02023567 ; registration date: December 2013.

Efficacy and safety of an adjunctive mGlu2 receptor positive allosteric modulator to a SSRI/SNRI in anxious depression

This phase 2a, randomized, multicenter, double-blind, proof-of-concept study was designed to evaluate, efficacy, safety and tolerability of JNJ-40411813/ADX71149, a novel metabotropic glutamate 2 receptor positive allosteric modulator as an adjunctive treatment for major depressive disorder (MDD) with significant anxiety symptoms. Eligible patients (18-64 years) had a DSM-IV diagnosis of MDD, Hamilton Depression Rating Scale-17 (HDRS17) score of ≥ 18, HDRS17 anxiety/somatization factor score of ≥ 7, and an insufficient response to current treatment with a selective serotonin reuptake inhibitor or serotonin-norepinephrine reuptake inhibitor. The doubly-randomized, 8-week double-blind treatment phase was comprised of two 4-week periods, from which a combined test statistic was generated, with pre-determined weights assigned to each of the 2 treatment periods. Period 1: patients (n=121) were randomly assigned (1:1) to JNJ-40411813 (n=62; 50mg to 150 mg b.i.d, flexibly dosed) or placebo (n=59); Period 2: placebo-treated patients (n=22) who continued to meet entry severity criteria were re-randomized (1:1) to JNJ-40411813 or placebo, while other patients underwent sham re-randomization and continued on their same treatment. Of 121 randomized patients, 100 patients (82.6%) were completers. No efficacy signal was detected on the primary endpoint, the 6-item Hamilton Anxiety Subscale (HAM-A6, p=0.51). Efficacy signals (based on prespecified 1-sided p<0.20) were evident on several secondary outcome measures of both depression (HDRS17 total score, 6-item subscale of HDRS17 assessing core depressive symptoms [HAM-D6], and Inventory of Depressive Symptomatology [IDS-C30]) and anxiety (HDRS17 anxiety/somatization factor, IDS-C30 anxiety subscale). Although well-tolerated, the results do not suggest efficacy for JNJ-40411813 as an adjunctive treatment for patients with MDD with significant anxious symptoms in the dose range studied.

Predicting treatment outcome in psychological treatment services by identifying latent profiles of patients

BACKGROUND

The outcomes of psychological therapies for anxiety and depression vary across individuals and symptom domains. Being able to predict treatment response from readily available patient data at presentation has potentially important benefits in aiding decisions about the most suitable interventions for a patient. This paper presents a method of identifying subgroups of patients using latent profile analysis, and comparing response to psychological treatments between these profiles.

METHODS

All outpatients taken into treatment at two psychological treatment services in London, UK and who provided basic demographic information and standardized symptom measures were included in the analysis (n=16636).

RESULTS

Latent Profile Analysis was performed on intake data to identify statistically different groups of patients, which were then examined in longitudinal analyses to determine their capacity to predict treatment outcomes. Comparison between profiles showed considerable variation in recovery (74-15%), deterioration rates (5-20%), and levels of attrition (17-40%). Further variation in outcomes was found within the profiles when different intensities of psychological intervention were delivered.

LIMITATIONS

Latent profiles were identified using data from two services, so generalisability to other services should be considered. Routinely collected patient data was included, additional patient information may further enhance utility of the profiles.

CONCLUSIONS

These results suggest that intake data can be used to reliably classify patients into profiles that are predictive of outcome to different intensities of psychological treatment in routine care. Algorithms based on these kinds of data could be used to optimize decision-making and aid the appropriate matching of patients to treatment.

Moderators of response in exercise treatment for depression: A systematic review

INTRODUCTION

Exercise have antidepressant effects in people with Major Depressive Disorder (MDD). However, about to half of patients do not respond to exercise. The identification of factors that moderates the antidepressant effects of exercise in people with MDD may help researchers and health professionals to identify sub-groups of patients that would benefit more from exercise.

METHODS

A systematic review was carried out using Medline(PubMed), EMBASE and psycINFO up to April 2015. Individual and composite moderators were summarized and the strength of the evidence was assessed.

RESULTS

Eleven studies were included for review resulting in the identification of potential individual (two biological, three clinical, two psychological and two social individual) and two potential composite moderators (the interaction between BDNF and Body Mass Index (BMI) and between family history of mental illness and gender). Only the two biological features and the BDNF x BMI interaction provided confirmatory evidence.

LIMITATIONS

Due the different statistical approaches used in the studies, it was not possible to perform meta-analyses. The small number of studies and the exploratory nature of the evidence limits a wider generalization of the findings.

CONCLUSION

Potential clinical, psychological, social or biological moderators were identified. However, the small number of studies and the limited strength of the evidence requires further studies before drawn definitive results. Further trials should consider the inclusion of moderators analysis using an a-priori, theoretical/evidence based hypothesis in order to provide high quality evidence for the use of personalized medicine in exercise for depression.

Illness history: Not associated with remission during treatment of major depression in 515 mood disorder patients

BACKGROUND

There is suggestive evidence that prior illness history may have little association with response to long-term treatment in bipolar disorder (BD) or recurrent major depressive disorder (MDD), but relationships of illness-history to treatment-response in acute episodes of depression require further testing.

METHODS

We tested for associations of selected measures of illness history with remission during treatment of an acute index episode of major depression in 515 mood-disorder patients (327 MDD, 188 BD), using bivariate and multivariate methods.

RESULTS

Remission of depression was more likely with lesser initial symptom-severity and bipolar diagnosis, but not related to years since illness-onset, previous depressions or episodes (based on counts, yearly rates, or %-of months ill), or other indices of illness-severity (hospitalization, co-morbidity, suicide attempt).

CONCLUSIONS

Likelihood of response to standard treatments for acute major depressive episodes in MDD or BD appeared to be largely independent of prior illness-history.

Assessment of functional outcomes by Sheehan Disability Scale in patients with major depressive disorder treated with duloxetine versus selective serotonin reuptake inhibitors

OBJECTIVE

We compared functional impairment outcomes assessed with Sheehan Disability Scale (SDS) after treatment with duloxetine versus selective serotonin reuptake inhibitors (SSRIs) in patients with major depressive disorder.

METHODS

Data were pooled from four randomized studies comparing treatment with duloxetine and SSRIs (three double blind and one open label). Analysis of covariance, with last-observation-carried-forward approach for missing data, explored treatment differences between duloxetine and SSRIs on SDS changes during 8 to 12 weeks of acute treatment for the intent-to-treat population. Logistic regression analysis examined the predictive capacity of baseline patient characteristics for remission in functional impairment (SDS total score ≤ 6 and SDS item scores ≤ 2) at endpoint.

RESULTS

Included were 2193 patients (duloxetine n = 1029; SSRIs n = 835; placebo n = 329). Treatment with duloxetine and SSRIs resulted in significantly (p < 0.01) greater improvements in the SDS total score versus treatment with placebo. Higher SDS (p < 0.0001) or 17-item Hamilton Depression Rating Scale baseline scores (p < 0.01) predicted lower probability of functional improvement after treatment with duloxetine or SSRIs. Female gender (p ≤ 0.05) predicted higher probability of functional improvement after treatment with duloxetine or SSRIs.

CONCLUSIONS

Treatment with SSRIs and duloxetine improved functional impairment in patients with major depressive disorder. Higher SDS or 17-item Hamilton Depression Rating Scale baseline scores predicted less probability of SDS improvement; female gender predicted better improvement in functional impairment at endpoint.

Modulation of Limbic and Prefrontal Connectivity by Electroconvulsive Therapy in Treatment-resistant Depression: A Preliminary Study

BACKGROUND

Although current models of depression suggest that a sequential modulation of limbic and prefrontal connectivity is needed for illness recovery, neuroimaging studies of electroconvulsive therapy (ECT) have focused on assessing functional connectivity (FC) before and after an ECT course, without characterizing functional changes occurring at early treatment phases.

OBJECTIVE

To assess sequential changes in limbic and prefrontal FC during the course of ECT and their impact on clinical response.

METHODS

Longitudinal intralimbic and limbic-prefrontal networks connectivity study. We assessed 15 patients with treatment-resistant depression at four different time-points throughout the entire course of an ECT protocol and 10 healthy participants at two functional neuroimaging examinations. Furthermore, a path analysis to test direct and indirect predictive effects of limbic and prefrontal FC changes on clinical response measured with the Hamilton Rating Scale for Depression was also performed.

RESULTS

An early significant intralimbic FC decrease significantly predicted a later increase in limbic-prefrontal FC, which in turn significantly predicted clinical improvement at the end of an ECT course.

CONCLUSIONS

Our data support that treatment response involves sequential changes in FC within regions of the intralimbic and limbic-prefrontal networks. This approach may help in identifying potential early biomarkers of treatment response.