Trajectories of individual symptoms in remitters versus non-remitters with depression

Trajectories of suicidal ideation during rTMS for treatment-resistant depression

BACKGROUND

rTMS is a safe and effective intervention for treatment-resistant depression (TRD). However, there is limited data on its specific impact on suicidal ideation (SI), and the trajectory of SI over the treatment course.

OBJECTIVE

This open-label clinical trial investigated SI outcomes and trajectories in patients with TRD receiving low-frequency rTMS (LFR) to the right dorsolateral prefrontal cortex (DLPFC; N = 55).

METHODS

A latent class mixed-effect model was used to identify response trajectories for SI as well as core mood symptoms. Logistic regression analyses investigated risk factors associated with identified trajectories.

RESULTS

For each symptom domain, we identified two distinct trajectories during LFR, one tracking improvement (SI: n = 35, 60 %; mood: n = 29, 53 %) and the other tracking no improvement (SI: n = 20, 40 %; mood: n = 26, 47 %). Male sex, higher baseline anxiety, and higher baseline SI were risk factors for no improvement of SI; while higher baseline anxiety and benzodiazepine use were risk factors for no improvement of mood. Mediation analyses showed that anxiety was a risk factor for no improvement of SI and mood independent of benzodiazepine treatment.

CONCLUSIONS

This is the first study to investigate trajectories of response to LFR to the right DLPFC. SI and mood improved with LFR in most patients but the severity of anxiety symptoms was a factor of poor prognosis for both. Nuanced characterization of SI response to rTMS may lead to critical insights for individualized targeting strategies.

Network analysis of depression and anxiety symptoms and their associations with mobile phone addiction among Chinese medical students during the late stage of the COVID-19 pandemic

Network analysis provides a novel approach to discovering associations between mental disorders at the symptom level. This study aimed to examine the characteristics of the network of depression and anxiety symptoms and their associations with mobile phone addiction (MPA) among Chinese medical students during the late stage of the COVID-19 pandemic. A total of 553 medical students were included. Depression and anxiety symptoms and MPA were measured by the nine-item Patient Health Questionnaire (PHQ-9), the seven-item Generalized Anxiety Disorder Scale (GAD-7), and the Mobile Phone Addiction Index (MPAI), respectively. Central and bridge symptoms were identified with centrality indices and bridge centrality indices. Network stability was examined using the case-dropping procedure. "Uncontrollable worry", "restlessness" and "nervousness" were the central symptoms in the depression and anxiety network. "Restlessness" and "motor" were the most central bridge symptoms linking depression and anxiety. "Concentration", "anhedonia" and "sleep" were most strongly associated with MPA. "Uncontrollable worry", "restlessness", "nervousness," and "motor" may be the symptoms for interventions to target in medical students with comorbid depression and anxiety. From a network perspective, depressive symptoms may be more important than anxiety symptoms in medical students with MPA.

Response trajectories during escitalopram treatment of patients with major depressive disorder

Depression is a leading global cause of disability, yet about half of patients do not respond to initial antidepressant treatment. This treatment difficulty may be in part due to the heterogeneity of depression and corresponding response to treatment. Unsupervised machine learning allows underlying patterns to be uncovered, and can be used to understand this heterogeneity by finding groups of patients with similar response trajectories. Prior studies attempting this have clustered patients using a narrow range of data primarily from depression scales. In this work, we used unsupervised machine learning to cluster patients receiving escitalopram therapy using a wide variety of subjective and objective clinical features from the first eight weeks of the Canadian Biomarker Integration Network in Depression-1 trial. We investigated how these clusters responded to treatment by comparing changes in symptoms and symptom categories, and by using Principal Component Analysis (PCA). Our algorithm found three clusters, which broadly represented non-responders, responders, and remitters. Most categories of features followed this response pattern except for objective cognitive features. Using PCA with our clusters, we found that subjective mood state/anhedonia is the core feature of response with escitalopram, but there exists other distinct patterns of response around neurovegetative symptoms, activation, and cognition.

Residual insomnia in major depressive disorder: a systematic review

Introduction

The ultimate goal in major depressive disorder (MDD) treatment is recovery. A proportion of MDD patients with formal remission experience persistent difficulties, which impair their daily functioning. Residual insomnia is one of the most common residual symptoms. Patients with residual insomnia experience relapse significantly earlier and have a poor prognosis. Little is known about possible ways of treatment and what subtype of insomnia is mostly reported.

Methods

A systematic literature review was carried out in PubMed and Web of Science to synthesize the current status of knowledge about effective treatment methods and insomnia subtypes in residual insomnia in MDD.

Results

A few non-pharmacological treatment methods e.g., Cognitive Behavioral Therapy for Insomnia (CBT-I), Mindfulness-Based Cognitive Therapy (MBCT), behavioral activation (BA) and pharmacological methods (gabapentin, clonazepam) have proven to mitigate residual insomnia. Cognitive Behavioral Therapy for Depression (CBT-D) ameliorates insomnia complaints to a limited extent. Mid-nocturnal insomnia is the most common residual insomnia subtype in MDD patients.

Conclusion

Residual insomnia is a very common complaint and most often appears as mid-nocturnal insomnia. Scarce data points out the benefits from pharmacotherapy, psychotherapy, and BA. More research is needed.

The course of insomnia symptoms during the acute treatment of major depressive disorder: A CAN-BIND-1 report

Despite considerable efforts to study the relationship between insomnia and depression, there is minimal research investigating whether insomnia symptoms change over time during a course of antidepressant pharmacotherapy. This study investigated the course of insomnia symptoms during the acute treatment of major depressive disorder (MDD) using a secondary analysis of data from MDD patients (N = 180) who were treated with open-label escitalopram (10-20 mg/day) for 8-weeks. Montgomery-Asberg Depression Rating Scale without sleep item (modified-MADRS) assessed depression and Self-reported Quick Inventory Depressive Scale (QIDS-SR) measured subjective sleep-onset, mid-nocturnal, and early-morning insomnia throughout 8-weeks of treatment. Pittsburgh Sleep Quality Index (PSQI) was used to assess subjective sleep quality, duration, onset latency, and efficiency throughout 8-weeks of treatment. Remission of depression was defined as modified-MADRS ≤10 at week-8. Mixed model repeated measures (MMRMs) were conducted with remission status as an independent variable and each sleep variable as a dependent variable. MMRMs demonstrated that remitters had significantly lower QIDS-SR sleep-onset and mid-nocturnal insomnia scores as well as a significantly lower PSQI sleep quality score than non-remitters throughout 8-weeks of treatment. Monitoring subjective sleep-onset and mid-nocturnal insomnia during the course of treatment with serotonergic antidepressants may be useful for predicting acute remission of depression.

Predicting relapse from the time to remission during the acute treatment of depression: A re-analysis of the STAR*D data

BACKGROUND

Predicting relapse during maintenance treatment for depression is challenging. The objective of this analysis was to investigate the association between the time taken to achieve remission in the acute phase, and the subsequent relapse rate or time to relapse using the Sequenced Treatment Alternatives to Relieve Depression dataset.

METHOD

Data of 1296 outpatients with nonpsychotic depression who entered a 12-month naturalistic follow-up period after achieving remission with citalopram for up to 14 weeks were analyzed. One-way analysis of variance and the Jonckheere-Terpstra trend test were performed to compare the relapse rates and days to relapse during the follow-up period among those who achieved remission at weeks 2, 4, 6, 9, 12, and 14. Remission and relapse were defined as scores of ≤5 and ≥11, respectively, on the 16-Item Quick Inventory of Depressive Symptomatology and Self-Report.

RESULTS

The relapse rates were significantly different among those who achieved remission each week (F_{(5, 1087)} = 4.995, p < 0.001). The lowest and highest relapse rates were observed in those who achieved remission at weeks 4 (25.7 %) and 12 (42.4 %), respectively, with a significant difference (p = 0.006). There was also a significant negative trend between the weeks taken to achieve remission and the days to relapse (z = -6.13, p < 0.001).

CONCLUSIONS

Patients with depression who show a faster response to antidepressant treatment are more likely to maintain remission in the long term. This finding suggests that, to prevent relapse, close attention should be paid to patients who require a relatively long time to achieve remission.

Predictors of response to pharmacotherapy in children and adolescents with psychiatric disorders: A combined post hoc analysis of four clinical trial data

OBJECTIVE

The prediction of response to pharmacotherapy has not been sufficiently explored in children and adolescents with psychiatric disorders, which was addressed in this study.

METHODS

Data from four double-blind, placebo-controlled studies (sertraline and fluvoxamine for anxiety disorders, risperidone for autistic disorder, and fluoxetine for major depressive disorder) in children and adolescents funded by the National Institute of Mental Health were used. The response was defined as a score of 1 or 2 on the Clinical Global Impression-Global Improvement (CGI-I) at the endpoint. Logistic regression analysis was performed to evaluate associations between response status and the following variables: sex, diagnosis, treatment allocation, and CGI-Severity of Illness (CGI-S) score at baseline. Moreover, the presence of early improvement (a score of ≤3 in the CGI-I) at Week 1 was added to the independent variables in an additional binary logistic regression analysis, using the data from two studies.

RESULTS

A total of 599 patients were included in the analysis. In the binary logistic regression analysis, active drug use (odds ratio [OR] = 8.64, P < 0.001) and female sex (OR = 1.89, P = 0.002) were significantly associated with treatment response. In the second binary logistic regression, the presence of early improvement in the CGI-I (OR = 3.47, P = 0.009), as well as active drug use (OR = 15.05, P < 0.001) and female sex (OR = 2.87, P = 0.016), were associated with subsequent responses.

CONCLUSION

Allocation to active drugs, female sex, and early improvement may predict treatment response to pharmacotherapy among children and adolescents with psychiatric disorders.

A network analysis of anxiety and depression symptoms among Chinese nurses in the late stage of the COVID-19 pandemic

Background

Nurses are at high risk for depression and anxiety symptoms after the outbreak of the COVID-19 pandemic. We aimed to assess the network structure of anxiety and depression symptoms among Chinese nurses in the late stage of this pandemic.

Method

A total of 6,183 nurses were recruited across China from Oct 2020 to Apr 2021 through snowball sampling. We used Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder scale-7 (GAD-7) to assess depression and anxiety, respectively. We used the Ising model to estimate the network. The index "expected influence" and "bridge expected influence" were applied to determine the central symptoms and bridge symptoms of the anxiety-depression network. We tested the stability and accuracy of the network via the case-dropping procedure and non-parametric bootstrapping procedure.

Result

The network had excellent stability and accuracy. Central symptoms included "restlessness", "trouble relaxing", "sad mood", and "uncontrollable worry". "Restlessness", "nervous", and "suicidal thoughts" served as bridge symptoms.

Conclusion

Restlessness emerged as the strongest central and bridge symptom in the anxiety-depression network of nurses. Intervention on depression and anxiety symptoms in nurses should prioritize this symptom.

Evidence for machine learning guided early prediction of acute outcomes in the treatment of depressed children and adolescents with antidepressants

BACKGROUND

The treatment of depression in children and adolescents is a substantial public health challenge. This study examined artificial intelligence tools for the prediction of early outcomes in depressed children and adolescents treated with fluoxetine, duloxetine, or placebo.

METHODS

The study samples included training datasets (N = 271) from patients with major depressive disorder (MDD) treated with fluoxetine and testing datasets from patients with MDD treated with duloxetine (N = 255) or placebo (N = 265). Treatment trajectories were generated using probabilistic graphical models (PGMs). Unsupervised machine learning identified specific depressive symptom profiles and related thresholds of improvement during acute treatment.

RESULTS

Variation in six depressive symptoms (difficulty having fun, social withdrawal, excessive fatigue, irritability, low self-esteem, and depressed feelings) assessed with the Children's Depression Rating Scale-Revised at 4-6 weeks predicted treatment outcomes with fluoxetine at 10-12 weeks with an average accuracy of 73% in the training dataset. The same six symptoms predicted 10-12 week outcomes at 4-6 weeks in (a) duloxetine testing datasets with an average accuracy of 76% and (b) placebo-treated patients with accuracies of 67%. In placebo-treated patients, the accuracies of predicting response and remission were similar to antidepressants. Accuracies for predicting nonresponse to placebo treatment were significantly lower than antidepressants.

CONCLUSIONS

PGMs provided clinically meaningful predictions in samples of depressed children and adolescents treated with fluoxetine or duloxetine. Future work should augment PGMs with biological data for refined predictions to guide the selection of pharmacological and psychotherapeutic treatment in children and adolescents with depression.

Different symptomatic improvement pattern revealed by factor analysis between placebo response and response to Esketamine in treatment resistant depression

AIMS

The aim of this study is to determine whether there is difference in the change in each symptom of depression and in symptomatic improvement pattern between placebo and antidepressant responses.

METHODS

Using data from a randomized, double-blind (DB), placebo-controlled trial of esketamine (ESK) in patients with treatment-resistant depression (TRD), we conducted exploratory analyses. To determine differences in the change in each depressive symptom on the MADRS subscale between placebo and antidepressant responses, a two-way factorial analysis was conducted using the amount of change on Day 2 and 28 of treatment. In addition, exploratory and confirmatory factor analyses were conducted on the MADRS subtotal variables on Day 2 and 28 of treatment to determine symptomatic improvement pattern between placebo response and antidepressant responses.

RESULTS

We found that as well as MADRS total score, each subscale of MADRS score did not significantly differ between esketamine and placebo at Day 2 and 28. On the other hand, factor analysis revealed that the factor structure of the response was different between esketamine and placebo at the 2nd day. There was no difference in the factor structure between esketamine and placebo in response on Day 28 of treatment.

CONCLUSION

Factor analysis revealed different patterns of symptom improvement in the early phase of the intervention between esketamine and placebo. This finding suggests that a data driven approach may provide detailed efficacy information in clinical trials for antidepressants.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02918318. Registered: 28 September 2016.

Cognitive outcomes are differentially associated with depression severity trajectories during psychotherapy treatment for late life major depressive disorder

OBJECTIVES

Late Life Depression (LLD) is associated with persistent cognitive dysfunction even after depression symptoms improve. The present study was designed to examine cognitive outcomes associated with the pattern of depression severity change during psychotherapy intervention for LLD.

METHODS

96 community-dwelling adults ages 65-91 with major depressive disorder completed 12 sessions of Problem-Solving Therapy at the University of California, San Francisco. Nonlinear trajectories of depression severity ratings using the Hamilton Depression Rating Scale were computed from multiple time points collected throughout the weekly psychotherapy intervention. Performance on measures of cognition (information processing speed, executive functioning, verbal learning, memory) was assessed at baseline and post-treatment. Linear mixed-effects models examined associations between nonlinear depression severity trajectories and post-treatment change in cognitive performance.

RESULTS

Broadly, different patterns of depression change during treatment were associated with improved cognition post-treatment. Greater and more consistent interval improvements in depression ratings were differentially associated with improvements in aspects of verbal learning, memory, and executive function post-treatment, while no associations were found with information processing speed.

CONCLUSIONS

The heterogeneity of depression trajectories associated with improved cognitive outcomes suggests that the temporal pattern of depression response may impact specific cognitive processes distinctly. Results suggest that use of nonlinear depression severity trajectories may help to elucidate complex associations between the time course of depression response and cognitive outcomes of psychotherapy in LLD. These findings have important implications for identifying treatment targets to enhance clinical and cognitive outcomes of psychotherapy in LLD.

Baseline anxiety, and early anxiety/depression improvement in anxious depression predicts treatment outcomes with escitalopram: A CAN-BIND-1 study report

INTRODUCTION

Although anxiety symptoms frequently co-occur with major depressive disorder, few studies examined the prediction of treatment outcomes among participants with anxious depression receiving antidepressants. We investigated whether baseline anxiety, and early improvements in anxiety and depression symptoms predict eventual treatment outcomes.

METHODS

111 participants with anxious depression, defined using ≥ 10 on GAD-7, received escitalopram (10-20 mg) for 8 weeks. Covariate-adjusted logistic regression was conducted to examine the impact of baseline anxiety, and to assess the extent week 2 anxiety (GAD-7) and depression (QIDS-SR) percentage improvement associates with week 8 anxiety (GAD-7) and depression (MADRS) response/remission. Optimum improvement thresholds were identified using receiving-operating-curve analysis and their predictive values assessed.

RESULTS

Greater percentage improvement in anxiety and depression after the first 2 weeks of treatment significantly increased odds of achieving week 8 anxiety and depression response/remission (OR:1.01-1.04, p<0.05). Early anxiety (68.4%/87.2%) and depression (52.2%/83.0%) improvement thresholds around 30 and 40% provided moderate to high positive predictive value (PPV) for predicting week 8 anxiety response/remission, as well as moderate to high negative predictive value (NPV) for predicting week 8 depression response/remission (anxiety:70.8%/91.7%; depression:72.2%/90.1%). Baseline anxiety severity predicted anxiety outcomes at weeks 2 and 8.

LIMITATIONS

Trial lacked placebo group.

CONCLUSION

In anxious depression, early improvement in anxiety may be better than depression in predicting anxiety outcomes, with similar or higher PPVs. Both improvement types perform similarly in predicting depression outcomes, with the lack of improvement predictive of non-response and non-remission. Finally, baseline anxiety predicts eventual anxiety but not depression outcomes.

Usefulness of Hamilton rating scale for depression subset scales and full versions for electroconvulsive therapy

Objectives

We investigated the predictive value of subset scales and full versions of the Hamilton Rating Scale for Depression (HAMD) for therapeutic outcomes in ECT.

Methods

This secondary analysis of patients with major depression (N = 136; 63% female; age = 56.7 [SD = 14.8]) from the EFFECT-Dep trial (NCT01907217) examined the predictive value of Evans-6, Toronto-7, Gibbons-8 and Maier-Philip 6 HAMD subset scales and three ‘full’ versions (HAMD-17, HAMD-21 and HAMD-24) on therapeutic outcomes. We also examined early improvement on subset scales and full versions as predictors of response and remission and explored predictive abilities of individual HAMD-24 items.

Results

The subset scales and full scales lacked sufficient predictive ability for response and remission. Receiver operating characteristic curves identified a lack of discriminative capacity of HAMD subset scales and full versions at baseline to predict response and remission. Only the Maier-Philip-6 was significantly associated with percentage reduction in HAMD-24 scores from baseline to end of ECT course. Early improvement on most of the subset scales and full versions was a sensitive and specific predictor of response and remission. Four of the HAMD-24 items were significantly associated with response and one with remission.

Conclusions

Limited utility of the HAMD subset scales and full versions in this context highlight a need for more tailored depression rating scales for ECT.

Development and validation of the Maudsley Modified Patient Health Questionnaire (MM-PHQ-9)

BACKGROUND

The Patient Health Questionnaire-9 (PHQ-9) is a widely used measure of depression in primary care. It was, however, originally designed as a diagnostic screening tool, and not for measuring change in response to antidepressant treatment. Although the Quick Inventory of Depressive Symptomology (QIDS-SR-16) has been extensively validated for outcome measurement, it is poorly adopted in UK primary care, and, although free for clinicians, has licensing restrictions for healthcare organisation use.

AIMS

We aimed to develop a modified version of the PHQ-9, the Maudsley Modified PHQ-9 (MM-PHQ-9), for tracking symptom changes in primary care. We tested the measure's validity, reliability and factor structure.

METHOD

A sample of 121 participants was recruited across three studies, and comprised 78 participants with major depressive disorder and 43 controls. MM-PHQ-9 scores were compared with the QIDS-SR-16 and Clinical Global Impressions improvement scale, for concurrent validity. Internal consistency of the scale was assessed, and principal component analysis was conducted to determine the items' factor structure.

RESULTS

The MM-PHQ-9 demonstrated good concurrent validity with the QIDS-SR-16, and excellent internal consistency. Sensitivity to change over a 14-week period was d = 0.41 compared with d = 0.61 on the QIDS-SR-16. Concurrent validity between the paper and mobile app versions of the MM-PHQ-9 was r = 0.67.

CONCLUSIONS

These results indicate that the MM-PHQ-9 is a valid and reliable measure of depressive symptoms in paper and mobile app format, although further validation is required. The measure was sensitive to change, demonstrating suitability for use in routine outcome assessment.

Individual and common patterns in the order of symptom improvement during outpatient treatment for major depression

BACKGROUND

Research so far provided few clues on the order in which depressive symptoms typically remit during treatment. This study examined which depressive symptoms improve first, and whether symptoms changed before, simultaneous with, or after the core symptoms of depression (i.e., sad mood, loss of pleasure, and loss of interest).

METHODS

Participants were 176 patients with Major Depressive Disorder (MDD) receiving outpatient treatment (a combination of pharmacotherapy and psychological interventions) for depression. Participants filled out the Inventory of Depressive Symptomatology - Self Report (IDS-SR) for 16 to 20 consecutive weeks. For each symptom, the timing of onset of a persistent improvement was determined for each single-subject separately.

RESULTS

Which symptoms improved first differed markedly across patients. The core depression symptoms improved 1.5 to 2 times more often before (48% - 60%) than after (19% -28%) depressive cognitions ('view of myself' and 'view of the future'), anxiety symptoms ('feeling irritable' and 'feeling anxious / tense') and vegetative symptoms ('loss of energy', 'slowed down', and 'physical energy'). Only improvements in suicidal thoughts were more likely to occur before (46% - 48%) than after (29%) improvements in the depression core symptoms.

LIMITATIONS

Not all 'core depression-non-core symptom' combinations could be tested because some symptoms did not improve in a sufficient number of patients.

CONCLUSIONS

Which improvements mark the start of symptom remission differed between patients. Improvements in the core depression symptoms 'sad mood', 'loss of interest', and 'loss of pleasure' were more likely to occur before than after improvements in non-core symptoms.

Prediction of short-term antidepressant response using probabilistic graphical models with replication across multiple drugs and treatment settings

Heterogeneity in the clinical presentation of major depressive disorder and response to antidepressants limits clinicians' ability to accurately predict a specific patient's eventual response to therapy. Validated depressive symptom profiles may be an important tool for identifying poor outcomes early in the course of treatment. To derive these symptom profiles, we first examined data from 947 depressed subjects treated with selective serotonin reuptake inhibitors (SSRIs) to delineate the heterogeneity of antidepressant response using probabilistic graphical models (PGMs). We then used unsupervised machine learning to identify specific depressive symptoms and thresholds of improvement that were predictive of antidepressant response by 4 weeks for a patient to achieve remission, response, or nonresponse by 8 weeks. Four depressive symptoms (depressed mood, guilt feelings and delusion, work and activities and psychic anxiety) and specific thresholds of change in each at 4 weeks predicted eventual outcome at 8 weeks to SSRI therapy with an average accuracy of 77% (p = 5.5E-08). The same four symptoms and prognostic thresholds derived from patients treated with SSRIs correctly predicted outcomes in 72% (p = 1.25E-05) of 1996 patients treated with other antidepressants in both inpatient and outpatient settings in independent publicly-available datasets. These predictive accuracies were higher than the accuracy of 53% for predicting SSRI response achieved using approaches that (i) incorporated only baseline clinical and sociodemographic factors, or (ii) used 4-week nonresponse status to predict likely outcomes at 8 weeks. The present findings suggest that PGMs providing interpretable predictions have the potential to enhance clinical treatment of depression and reduce the time burden associated with trials of ineffective antidepressants. Prospective trials examining this approach are forthcoming.

Distinct Features of Cerebral Blood Flow and Spontaneous Neural Activity as Integrated Predictors of Early Response to Antidepressants

AIMS

The purpose of this study is to explore whether pre-treatment features of brain function can discriminate non-responders to antidepressant medication in the early phase.

METHODS

Forty-four treatment-responsive depressed (RD) patients, 36 non-responsive depressed (NRD) patients, and 42 healthy controls (HCs) were recruited. Regional cerebral blood flow (CBF) and amplitude of low-frequency fluctuation (ALFF) values were calculated for all subjects. Correlation analyses were used to explore the relationship between symptom improvement and CBF/ALFF. Receiver operating characteristics (ROC) and the 10-fold cross-validation support vector machine (SVM) classifier were applied for the discrimination of treatment response.

RESULTS

Compared with the HCs, the RD and NRD groups exhibited lower CBF and ALFF in the right posterior lobe of the cerebellum. Compared with the NRD group, the RD group showed distinct CBF patterns in the left frontal striatal regions and right frontal cerebellar regions, as well as distinct ALFF features in the left frontoparietal striatum and right frontotemporal striatal cerebellar regions. The ROC and SVM classifier revealed the optimal power to distinguish the RD and NRD groups based on the combined measures (i.e., CBF and ALFF).

CONCLUSION

Distinct features of CBF and ALFF in the frontal striatal network may serve as promising neuroimaging predictors for identifying patients with blunted responsiveness, which may facilitate personalized antidepressant treatment.

Symptom clusters in adolescent depression and differential response to treatment: a secondary analysis of the Treatment for Adolescents with Depression Study randomised trial

BACKGROUND

Better understanding of the heterogeneity of treatment responses could help to improve care for adolescents with depression. We analysed data from a clinical trial to assess whether specific symptom clusters responded differently to various treatments.

METHODS

For this secondary analysis, we used data from the Treatment for Adolescents with Depression Study (TADS), in which 439 US adolescents aged 12-17 with a DSM-IV diagnosis of major depressive disorder and a minimum score of 45 on the Children's Depression Rating Scale-Revised (CDRS-R) were randomly assigned (1:1:1:1) to treatment with fluoxetine, cognitive behavioural therapy (CBT), fluoxetine plus CBT, or pill placebo. Our analysis focuses on the acute phase of the trial (ie, the first 12 weeks). Groups of co-occurring symptoms were established by clustering scores for each CDRS-R item at baseline with Ward's method, with Euclidean distances for hierarchical agglomerative clustering. We then used a linear mixed-effects model to investigate the relationship between symptom clusters and treatment efficacy, with the sum of symptom scores within each cluster as the dependent measure. As fixed effects, we entered cluster, time, and treatment assignment, with all two-way and three-way interactions, into the model. The random effect providing better fit was established to be a by-subject random slope for cluster based on improvement in the Schwarz-Bayesian information criterion.

OUTCOMES

We identified two symptom clusters: cluster 1 comprised depressed mood, difficulty having fun, irritability, social withdrawal, sleep disturbance, impaired schoolwork, excessive fatigue, and low self-esteem, and cluster 2 comprised increased appetite, physical complaints, excessive weeping, decreased appetite, excessive guilt, morbid ideation, and suicidal ideation. For cluster 1 symptoms, CDRS-R scores were reduced by 5·8 points (95% CI 2·8-8·9) in adolescents treated with fluoxetine plus CBT, and by 4·1 points (1·1-7·1) in those treated with fluoxetine, compared with those given placebo. For cluster 2 symptoms, no significant differences in improvements in CDRS-R scores were detected between the active treatment and placebo groups.

INTERPRETATION

Response to fluoxetine and CBT among adolescents with depression is heterogeneous. Clinicians should consider clinical profile when selecting therapeutic modality. The contrast in response patterns between symptom clusters could provide opportunities to improve treatment efficacy by gearing the development of new therapies towards the resolution of specific symptoms.

FUNDING

Conselho Nacional de Desenvolvimento Científico e Tecnológico.

Early improvements of individual symptoms as a predictor of treatment response to asenapine in patients with schizophrenia

Aim

It is well accepted that early improvement with antipsychotics predicts subsequent response in patients with schizophrenia. However, no study has examined the contribution of individual symptoms rather than overall symptom severity as the predictors. Thus, we aimed to detect individual symptoms whose improvements could predict subsequent response in patients with schizophrenia during treatment with asenapine and examine whether a prediction model with individual symptoms would be superior to a model using overall symptom severity.

Methods

This study analyzed a dataset including 532 patients with schizophrenia enrolled in a 6‐week double‐blind, placebo‐controlled, randomized trial of asenapine. Response to asenapine was defined as a ≥30% decrease in Positive and Negative Syndrome Scale (PANSS) total score from baseline to week 6. Stepwise logistic regression analyses were performed to investigate the associations among response and PANSS total/individual item score improvements at week 1 or week 2.

Results

Response was associated with early improvement in the following PANSS items: disturbance of volition, active social avoidance, poor impulse control at week 1; and active social avoidance, poor attention, lack of judgment and insight at week 2. Prediction accuracy was almost compatible between the model with individual symptoms and the model with PANSS total score both at weeks 1 and 2 (Nagelkerke R²: .51, .42 and .55, .54, respectively).

Conclusion

Early improvement in negative symptoms, poor attention and impulse control, and lack of insight, in particular predicted subsequent treatment response in patients with schizophrenia during treatment with asenapine as accurately as prediction based on overall symptom severity.

This study found that treatment response to asenapine was predicted by early improvements of individual symptoms such as negative symptoms, poor attention and impulse control, and lack of insight in patients with schizophrenia. In addition, prediction accuracy was almost comparable between the model with individual symptoms and the model with the PANSS total score, supporting the importance to assess both individual symptoms and the whole severity in the clinical settings.

Connectivity between the anterior insula and dorsolateral prefrontal cortex links early symptom improvement to treatment response

BACKGROUND

Early improvement (EI) following treatment with antidepressants is a widely reported predictor to the treatment response. This study aimed to identify the resting-state functional connectivity (rs-FC) and its related clinical features that link the treatment response at the time of EI.

METHODS

This study included 23 first-episode treatment-naive patients with MDD. After 2 weeks of antidepressant treatment, these patients received 3.0 Tesla resting-state functional magnetic resonance imaging scanning and were subgrouped into an EI group (N = 13) and a non-EI group (N = 10). Using the anterior insula (rAI) as a seed region, this study identified the rs-FC that were associated with both EI and the treatment response at week 12, and further tested the associations of the identified rs-FC with either the clinical features or the early symptom improvement.

RESULTS

Rs-FC between rAI and the left dorsolateral prefrontal cortex (dlPFC) was associated with EI (t₂₁ = -6.091, p = 0.022 after FDR correction for multiple comparisons). This rs-FC was also associated with an interaction between EI and the treatment response at the week 12 (t₂₁ = -5.361, p = 6.37e-5). Moreover, among the clinical features, this rs-FC was associated with the early symptom improvement in the insomnia, somatic symptoms, and anxiety symptoms, and these early symptom improvements were associated with the treatment response.

CONCLUSION

Rs-FC between the rAI and the left dlPFC played a crucial role in the early antidepressant effect, which linked the treatment response. The early treatment effect relating to rAI may represent an early symptom improvement in self-perceptual anxiety, somatic symptoms and insomnia.

Predicting relapse with residual symptoms in schizophrenia: A secondary analysis of the PROACTIVE trial

INTRODUCTION

Little attention has been paid to the contribution of individual residual symptom to predict relapse in patients with schizophrenia receiving oral or long-acting injectable (LAI) antipsychotics.

METHOD

We used the data from the Preventing Relapse on Oral Antipsychotics Compared to Injectables - Evaluating Efficacy (PROACTIVE) study, in which 305 outpatients with schizophrenia were randomly allocated to either biweekly LAI-risperidone (LAI-R) or daily oral second-generation antipsychotics (SGA) and assessed for up to 30 months. Baseline individual symptoms that could predict subsequent relapse were identified, using a Cox proportional hazards model. Moreover, among those who relapsed during the study (n = 73), individual symptoms were compared between baseline and biweekly ratings 8 to 2 weeks before relapse, using the linear mixed model.

RESULTS

A greater score in grandiosity at baseline was significantly associated with subsequent relapse (adjusted HR = 1.24, p = 0.006). When the two treatment groups were separately analyzed, more severe grandiosity (adjusted HR = 1.43, p = 0.003) and less severe hallucinatory behavior (adjusted HR = 0.70, p = 0.013) at baseline were significantly associated with relapse in the oral SGA group, but none was identified in the LAI-R group. Emotional withdrawal was significantly worse 8 and 2 weeks before relapse compared to the baseline (p = 0.032 and p = 0.043, respectively).

DISCUSSION

More severe grandiosity and less hallucination may have led to more frequent relapses in patients with schizophrenia receiving oral antipsychotics, which was not a case in those receiving LAI-R. The exploratory analysis indicates an increase in emotional withdrawal before relapse may be a useful marker for earlier interventions to possibly avert relapse.

A Randomized Placebo-Controlled Trial of Omega-3 and Sertraline in Depressed Patients With or at Risk for Coronary Heart Disease

OBJECTIVE

Studies of depressed psychiatric patients have suggested that antidepressant efficacy can be increased by adding eicosapentaenoic acid (EPA), one of the omega-3 fatty acids found in fish oils. The purpose of this study was to determine whether the addition of EPA improves the response to sertraline in depressed patients with or at high risk for coronary heart disease (CHD).

METHODS

Between May 2014 and June 2018, 144 patients with DSM-5 major depressive disorder seen at the Washington University School of Medicine with or at high risk for CHD were randomized to receive either 50 mg/d of sertraline and 2 g/d of EPA or 50 mg/d of sertraline and corn oil placebo capsules for 10 weeks. The Beck Depression Inventory II (BDI-II) was the primary outcome measure.

RESULTS

After 10 weeks of treatment, there were no differences between the arms on the mean baseline-adjusted BDI-II (placebo, 10.3; EPA, 12.1; P = .22), the 17-item Hamilton Depression Rating Scale (placebo, 7.2; EPA, 8.0; P = .40), or the 10-week remission rate (BDI-II score ≤ 8: placebo, 50.6%; EPA, 46.7%; odds ratio = 0.85; 95% CI, 0.43 to 1.68; P = .63).

CONCLUSIONS

Augmentation of sertraline with 2 g/d of EPA for 10 weeks did not result in greater improvement in depressive symptoms compared to sertraline and corn oil placebo in patients with major depressive disorder and CHD or CHD risk factors. Identifying the characteristics of cardiac patients whose depression may benefit from omega-3 and clarifying the pathways linking omega-3 to improvement in depression symptoms are important directions for future research.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02021669; FDA IND registration number: 121107.

Utility of the Compensatory Tracking Task for Objective Differentiation of Hypersomnolence in Depression: A High-Density EEG Investigation

Hypersomnolence is a common and debilitating symptom in mood disorders. However, objective differentiation of excessive daytime sleepiness (EDS) from non-EDS in depression has not yet been achieved. This study compared performance on the Compensatory Tracking Task (CTT) and concurrently-recorded high-density (hd)EEG theta power in 22 patients with major depressive disorder (MDD) and co-occurring EDS against 22 age- and sex-matched patients with MDD but no EDS, as well as 22 age- and sex-matched healthy controls. Though depressed hypersomnolent participants endorsed feeling sleepier than depressed non-hypersomnolent and healthy control participants prior to starting the CTT, no group differences in CTT performance were observed. Average hdEEG theta power was higher during periods of high error on the CTT compared to periods of low error, but did not differ between the groups. Though the CTT still holds promise as an objective neurobehavioral measure, these results do not indicate a capability to differentiate EDS from non-EDS in mood disorders.

Severity, course trajectory, and within-person variability of individual symptoms in patients with major depressive disorder

BACKGROUND

Depression shows a large heterogeneity of symptoms between and within persons over time. However, most outcome studies have assessed depression as a single underlying latent construct, using the sum score on psychometric scales as an indicator for severity. This study assesses longitudinal symptom-specific trajectories and within-person variability of major depressive disorder over a 9-year period.

METHODS

Data were derived from the Netherlands Study of Depression and Anxiety (NESDA). This study included 783 participants with a current major depressive disorder at baseline. The Inventory Depressive Symptomatology-Self-Report (IDS-SR) was used to analyze 28 depressive symptoms at up to six time points during the 9-year follow-up.

RESULTS

The highest baseline severity scores were found for the items regarding energy and mood states. The core symptoms depressed mood and anhedonia had the most favorable course, whereas sleeping problems and (psycho-)somatic symptoms were more persistent over 9-year follow-up. Within-person variability was highest for symptoms related to energy and lowest for suicidal ideation.

CONCLUSIONS

The severity, course, and within-person variability differed markedly between depressive symptoms. Our findings strengthen the idea that employing a symptom-focused approach in both clinical care and research is of value.

Early symptom non-improvement and aggravation are associated with the treatment response to SSRIs in MDD: a real-world study

PURPOSE

Early improvement in major depressive disorder is defined as a reduction of ≥20% in the 17-item Hamilton Depression Rating Scale (HAM-D-17) score at the second week after initiation of treatment, predicting long-term treatment response. However, there remains no effective strategy for switching medications when a patient fails to reach early improvement at the second week. This study focused on the predictive value of early symptom changes in each item of the HAM-D-17 scale for treatment response to selective serotonin reuptake inhibitor (SSRI) monotherapy and to provide a reference for switching antidepressants to enhance early treatment efficacy.

PATIENTS AND METHODS

Our study was an observational, real-world study that enrolled 90 treatment-naïve patients experiencing their first episode of major depressive disorder in the outpatient department of Huashan Hospital. Patients who did not achieve the threshold of early improvement in the second week after starting treatment were switched to alternative SSRI monotherapy. Patient follow-up occurred at 2, 4, 8, and 12 weeks after the initiation of treatment. We analyzed the relationship between the change in each symptom on the HAM-D-17 scale and treatment efficacy.

RESULTS

Early improvement predicted the treatment response at 12 weeks (χ ²=19.249, P<0.001), whereas early non-improvement in insomnia and anxiety was associated with a poor response (OR =9.487, 95% CI: 1.312-68.588 and OR =12.947, 95% CI: 1.99-82.246, respectively). At week 2, general somatic symptom aggravation was associated with a poorer response (OR =73.337, 95% CI: 2.232->999.999); treatment-emergent headache and tremor were associated with treatment efficacy (t=-9.521, P<0.001 and t=3.660, P=0.001, respectively). In addition, the increase in suicidal thoughts, once treatment began, had no relationship with the treatment response (OR =0.821, P=0.872).

CONCLUSION

This study suggested that patients with early non-improvement in insomnia and anxiety were not suitable for switches in SSRI monotherapy. Patients with treatment-emergent symptoms, especially headaches and tremors, were not suitable for switching from monotherapy to another SSRI.

Variance of the global signal as a pretreatment predictor of antidepressant treatment response in drug-naïve major depressive disorder

Several behavioral and neuroimaging markers could be used to predict eventual antidepressant medication (ADM) outcomes in patients with major depressive disorder (MDD). However, these predictors are either subjective or complex, which has limited their clinical use. Thus, we aimed to identify an objective and easy-to-get marker to predict early therapeutic efficacy. Forty-seven drug-naïve patients with MDD and 47 age-, gender- and education-matched healthy controls underwent resting-state functional magnetic resonance imaging (fMRI) scans. We calculated the variable coefficient (VC) of the global signal for each subject. Baseline Hamilton Rating Scale for Depression (HRSD) score and that after 2 weeks of ADM were assessed for patients. Although there was no difference in VC between patients with MDD and healthy controls, we found a significant positive correlation between the VC and the decline rate of HRSD scores in the patients. Compared with the non-responding depression (NRD) group, the treatment-responsive depression (TRD) group had a higher VC. Receiver operator characteristic curve analysis revealed that the VC exhibited a good ability to differentiate TRD from NRD. In addition, the linear and logistic regression analyses showed that the VC was a significant predictor of the decline rate of HRSD scores and the antidepressant treatment response. These findings suggest that variance of the global signal may serve as a useful marker to help clinicians find an appropriate drug for individuals with MDD at the earliest opportunity and then further to facilitate personalized therapy.

Classes of depression symptom trajectories in patients with major depression receiving a collaborative care intervention

PURPOSE

Collaborative care is effective in improving symptoms of patients with depression. The aims of this study were to characterize symptom trajectories in patients with major depression during one year of collaborative care and to explore associations between baseline characteristics and symptom trajectories.

METHODS

We conducted a cluster-randomized controlled trial in primary care. The collaborative care intervention comprised case management and behavioral activation. We used the Patient Health Questionnaire-9 (PHQ-9) to assess symptom severity as the primary outcome. Statistical analyses comprised latent growth mixture modeling and a hierarchical binary logistic regression model.

RESULTS

We included 74 practices and 626 patients (310 intervention and 316 control recipients) at baseline. Based on a minimum of 12 measurement points for each intervention recipient, we identified two latent trajectories, which we labeled 'fast improvers' (60.5%) and 'slow improvers' (39.5%). At all measurements after baseline, 'fast improvers' presented higher PHQ mean values than 'slow improvers'. At baseline, 'fast improvers' presented fewer physical conditions, higher health-related quality of life, and had made fewer suicide attempts in their history.

CONCLUSIONS

A notable proportion of 39.5% of patients improved only 'slowly' and probably needed more intense treatment. The third follow-up in month two could well be a sensible time to adjust treatment to support 'slow improvers'.

Looking into the effect of multi-item symptom domains on psychometric characteristics of the Quick Inventory of Depressive Symptomatology-Self Report (QIDS-SR16)

Exploring depressive symptom severity is progressively shifting from the traditional assessment of symptom domains to detailed examination of individual symptoms. This study aimed at determining whether using an alternative scoring method (i.e., summing all scorable items instead of summing symptom domains) for the Quick Inventory of Depressive Symptomatology-Self Report (QIDS-SR₁₆) would not compromise the measurement properties. This is a secondary analysis of data collected in a psychometric study of the Spanish version of the QIDS-SR₁₆. One hundred and sixty-six patients were assessed by means of the QIDS-SR₁₆ and two interviewer-rated instruments: the Hamilton Depression Rating Scale and the Clinical Global Impression-Severity scale. Factor structure, internal consistency reliability and convergent construct validity of the QIDS-SR₁₆ scored using the alternative method were examined. Exploratory factor analysis replicated the one-factor structure of the original scoring system. Good to excellent internal consistency and convergent validity were found, which did not differ significantly from the ones of the original scoring method. Using a simplified and easier scoring method, the Spanish QIDS-SR₁₆ retained the soundness of psychometric characteristics of both the original English version and the Spanish one scored according to the original scoring system, supporting the alternative scoring method as a reliable and valid option.

Predicting antidepressant response by monitoring early improvement of individual symptoms of depression: individual patient data meta-analysis

BACKGROUND

Improvement in depression within the first 2 weeks of antidepressant treatment predicts good outcomes, but non-improvers can still respond or remit, whereas improvers often do not.AimsWe aimed to investigate whether early improvement of individual depressive symptoms better predicts response or remission.

METHOD

We obtained individual patient data of 30 trials comprising 2184 placebo-treated and 6058 antidepressant-treated participants. Primary outcome was week 6 response; secondary outcomes were week 6 remission and week 12 response and remission. We compared models that only included improvement in total score by week 2 (total improvement model) with models that also included improvement in individual symptoms.

RESULTS

For week 6 response, the area under the receiver operating characteristic curve and negative and positive predictive values of the total improvement model were 0.73, 0.67 and 0.74 compared with 0.77, 0.70 and 0.71 for the item improvement model. Model performance decreased for week 12 outcomes. Of predicted non-responders, 29% actually did respond by week 6 and 43% by week 12, which was decreased from the baseline (overall) probabilities of 51% by week 6 and 69% by week 12. In post hoc analyses with continuous rather than dichotomous early improvement, including individual items did not enhance model performance.

CONCLUSIONS

Examining individual symptoms adds little to the predictive ability of early improvement. Additionally, early non-improvement does not rule out response or remission, particularly after 12 rather than 6 weeks. Therefore, our findings suggest that routinely adapting pharmacological treatment because of limited early improvement would often be premature.Declaration of interestNone.

Predicting relapse with individual residual symptoms in major depressive disorder: a reanalysis of the STAR*D data

BACKGROUND

Residual symptoms are detrimental to prognosis in major depressive disorder (MDD); however, little is known about the contribution of each residual symptom in predicting outcomes. The objective of this analysis was to identify which individual symptoms, based on self-report and clinician interview, could predict subsequent relapse.

METHODS

The data of 1133 outpatients with nonpsychotic MDD who entered a 12-month naturalistic follow-up phase after achieving remission with level 1 treatment (i.e., citalopram for up to 14 weeks) and had at least one post-baseline contact in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial were analyzed. Specific residual symptoms in the 16-item Quick Inventory of Depressive Symptomatology, self-report (QIDS-SR₁₆) and clinician rating (QIDS-C₁₆), at the follow-up entry that predicted relapse were identified, using a Cox proportional hazards model.

RESULTS

The following three QIDS-SR₁₆ symptoms were significantly associated with subsequent relapse: restlessness (HR = 1.197, p = 0.018), hypersomnia (HR = 1.190, p = 0.009), and weight change (HR = 1.127, p = 0.041). On the other hand, the following three symptoms in the QIDS-C₁₆ at the follow-up entry were significantly associated with relapse in the follow-up phase: restlessness (HR = 1.328, p = 0.001), sleep onset insomnia (HR = 1.129, p = 0.047), and weight change (HR = 1.125, p = 0.045).

LIMITATIONS

The original trial was not designed to evaluate the issue addressed herein. Individual symptoms may be associated with each other and functional status was not addressed.

CONCLUSIONS

Some residual symptoms, including restlessness, insomnia, and weight change, may help better identify patients with MDD vulnerable to relapse. Contribution of individual residual symptoms to subsequent relapse was similar between self-report and clinician-rated symptoms.

Divergent topological architecture of the default mode network as a pretreatment predictor of early antidepressant response in major depressive disorder

Identifying a robust pretreatment neuroimaging marker would be helpful for the selection of an optimal therapy for major depressive disorder (MDD). We recruited 82 MDD patients [n = 42 treatment-responsive depression (RD) and n = 40 non-responding depression (NRD)] and 50 healthy controls (HC) for this study. Based on the thresholded partial correlation matrices of 58 specific brain regions, a graph theory approach was applied to analyse the topological properties. When compared to HC, both RD and NRD patients exhibited a lower nodal degree (D_nodal) in the left anterior cingulate gyrus; as for RD, the D_nodal of the left superior medial orbitofrontal gyrus was significantly reduced, but the right inferior orbitofrontal gyrus was increased (all P < 0.017, FDR corrected). Moreover, the nodal degree in the right dorsolateral superior frontal cortex (SFGdor) was significantly lower in RD than in NRD. Receiver operating characteristic curve analysis demonstrated that the λ and nodal degree in the right SFGdor exhibited a good ability to distinguish nonresponding patients from responsive patients, which could serve as a specific maker to predict an early response to antidepressants. The disrupted topological configurations in the present study extend the understanding of pretreatment neuroimaging predictors for antidepressant medication.

The efficacy of levomilnacipran ER across symptoms of major depressive disorder: a post hoc analysis of 5 randomized, double-blind, placebo-controlled trials

OBJECTIVE

A post hoc analysis evaluated the effects of levomilnacipran ER on individual symptoms and symptom domains in adults with major depressive disorder (MDD).

METHODS

Data were pooled from 5 Phase III trials comprising 2598 patients. Effects on depression symptoms were analyzed based on change from baseline in individual Montgomery-Åsberg Depression Rating Scale (MADRS) item scores. A1dditional evaluations included resolution of individual symptoms (defined as a MADRS item score ≤1 at end of treatment) and concurrent resolution of all 10 MADRS items, all MADRS6 subscale items, and all items included in different symptom clusters (Dysphoria, Retardation, Vegetative Symptoms, Anhedonia).

RESULTS

Significantly greater mean improvements were found on all MADRS items except Reduced Appetite with levomilnacipran ER treatment compared with placebo. Resolution of individual symptoms occurred more frequently with levomilnacipran ER than placebo for each MADRS item (all P<.05), with odds ratios (ORs) ranging from 1.26 to 1.75; resolution of all 10 items was also greater with levomilnacipran ER (OR=1.57; P=.0051). Significant results were found for the MADRS6 subscale (OR=1.73; P<.0001) and each symptom cluster (OR range, 1.39 [Vegetative Symptoms] to 1.84 [Retardation]; all clusters, P<.01).

CONCLUSION

Adult MDD patients treated with levomilnacipran ER improved across a range of depression symptoms and symptom domains.

Treatment outcome variation between depression symptom combinations in the STAR*D study

BACKGROUND

In response to recent documentation of symptom and subtype heterogeneity in major depressive disorder, we report on exploratory analyses of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) clinical-trial data to further describe heterogeneity in depression and test the hypothesis that citalopram treatment-outcome patterns differ as a function of depression symptom combinations.

METHODS

Combinatorial algorithms, latent profile analysis, and repeated-measures multivariate analysis of variance were employed to characterize heterogeneity and depression outcome-measure profile variability in the most prevalent symptom combinations with full data (26% of baseline and 13% of endpoint total sample).

RESULTS

Descriptive results suggest that substantial heterogeneity and moderate coherence characterize major depressive disorder; as in previous analyses, pairs of individuals sharing no symptoms in common were observed. Exploratory latent profile analysis indicated that different patterns of treatment outcome data exist among STAR*D participants. A small but significant interaction effect of symptom combination×outcome measure profile was observed for clinician-rated but not self-reported symptom combinations.

LIMITATIONS

Factors moderating the generalizability of these findings include binary symptom measures, a short treatment period, and a smaller number of individuals per combination.

CONCLUSIONS

These results provide evidence that citalopram treatment outcomes vary as a function of diagnostic combinations, thereby providing preliminary evidence that the substantial heterogeneity documented in depression symptom presentations may carry implications for prognosis and treatment outcome. At the level of descriptive phenomenology, these results appear to corroborate the claim that depression is not a homogenous syndrome.

Trajectories of depression symptom improvement and associated predictor analysis: An analysis of duloxetine in double-blind placebo-controlled trials

BACKGROUND

In the treatment of major depressive disorder (MDD), it is not fully understood how individual symptoms improve over time (trajectory) in remitters. This study compared symptom improvement trajectories, as measured with the 17-item Hamilton Depression Rating Scale (HAM-D17), in remitters and nonremitters.

METHODS

This analysis is based on 10 placebo-controlled, randomized, double-blind trials of duloxetine (40-60mg/day) for treatment of MDD from baseline up to week 8. Remission was defined as a HAM-D17 total score ≤7 at week 8 (last observation carried forward). Trajectories of HAM-D17 items were assessed by mixed model repeated measures analysis for treatment and remitter-nonremitter comparisons. Grouping of the trajectories was performed by factor analysis. Predictor analysis using HAM-D17 items was conducted by logistic regression.

RESULTS

There were 1555 patients in the duloxetine group (489 [31.4%] remitters) and 1206 patients in the placebo group (290 [24.0%] remitters; P<.0001). For most items, the difference in trajectories between remitters and nonremitters appeared at early time points and increased over time. Treatment response trajectories were very similar for duloxetine and placebo remitters, while duloxetine nonremitters improved more than placebo nonremitters. For duloxetine remitters, we found 3 trajectory groups of HAM-D17 items. The predictor analysis showed that improvement in 6 individual items at week 1 or 2 was significantly associated with remission at week 8.

LIMITATIONS

Generalizability of these results may be limited by the relatively short observation period used to define remission.

CONCLUSIONS

Early monitoring of some symptoms of depression may prove useful in guiding treatment decisions.

Early Improvements in Individual Symptoms to Predict Later Remission in Major Depressive Disorder Treated With Mirtazapine

Few studies, to our knowledge, have examined whether early improvements in individual, instead of overall, depressive symptoms predict remission in major depressive disorder (MDD). This post hoc analysis used data from 194 patients with MDD enrolled in a 6-week double-blind, placebo-controlled, randomized trial of mirtazapine, to identify improvements in specific individual depressive symptoms in the early phase that are associated with subsequent remission. Trajectories of individual depressive symptoms over 6 weeks were compared between remitters and nonremitters. Early improvement was defined as a ≥20% decrease in the Hamilton Rating Scale for Depression 17 items (HAM-D17) total score in weeks 1 and 2, and remission was defined as a HAM-D17 final score of ≤7. Reliability parameters were calculated for early improvements in predicting later remission. Whether improvement in each of the HAM-D17 symptoms in weeks 1 or 2 predicted remission was examined, using binary logistic regression analyses. As a result, improvements in weeks 1 and 2 were associated with sensitivity of 0.82 and 0.99 and specificity of 0.54 and 0.44, respectively, in predicting remission in week 6. Improvements in insomnia late (P = .04) and insight (P = .007) in week 1 and somatic symptoms general (P = .002) and insight (P = .04) in week 2 were associated with remission in week 6. In conclusion, early improvements in insight, insomnia late, and somatic symptoms general, as well as overall depressive symptoms, may serve as specific clinical indicators of subsequent remission in patients with MDD receiving mirtazapine.

Does early improvement in depressive symptoms predict subsequent remission in patients with depression who are treated with duloxetine?

PURPOSE

In this prospective study, we examined whether early reduction in depressive symptoms predicts later remission to duloxetine in the treatment of depression, as monitored using the Montgomery-Asberg Depression Rating Scale (MADRS).

PATIENTS AND METHODS

Among the 106 patients who were enrolled in this study, 67 were included in the statistical analysis. A clinical evaluation using the MADRS was performed at weeks 0, 4, 8, 12, and 16 after commencing treatment. For each time point, the MADRS total score was separated into three components: dysphoria, retardation, and vegetative scores.

RESULTS

Remission was defined as an MADRS total score of ≤10 at end point. From our univariate logistic regression analysis, we found that improvements in both the MADRS total score and the dysphoria score at week 4 had a significant interaction with subsequent remission. Furthermore, age and sex were significant predictors of remission. There was an increase of approximately 4% in the odds of remission for each unit increase in age, and female sex had an odds of remission of 0.318 times that of male sex (remission rate for men was 73.1% [19/26] and for women 46.3% [19/41]). However, in the multivariate model using the change from baseline in the total MADRS, dysphoria, retardation, and vegetative scores at week 4, in which age and sex were included as covariates, only sex retained significance, except for an improvement in the dysphoria score.

CONCLUSION

No significant interaction was found between early response to duloxetine and eventual remission in this study. Sex difference was found to be a predictor of subsequent remission in patients with depression who were treated with duloxetine, with the male sex having greater odds of remission.

Antidepressant Response Trajectories and Associated Clinical Prognostic Factors Among Older Adults

IMPORTANCE

More than 50% of older adults with late-life major depressive disorder fail to respond to initial treatment with first-line pharmacological therapy.

OBJECTIVES

To assess typical patterns of response to an open-label trial of extended-release venlafaxine hydrochloride (venlafaxine XR) for late-life depression and to evaluate which clinical factors are associated with the identified longitudinal response patterns.

DESIGN, SETTING, AND PARTICIPANTS

Group-based trajectory modeling was applied to data from a 12-week open-label pharmacological trial conducted in specialty care as part of the Incomplete Response in Late Life: Getting to Remission Study. Clinical prognostic factors, including domain-specific cognitive performance and individual depression symptoms, were examined in relation to response trajectories. Participants included 453 adults aged 60 years or older with current major depressive disorder. The study was conducted between August 2009 and August 2014.

INTERVENTION

Open-label venlafaxine XR (titrated up to 300 mg/d) for 12 weeks.

MAIN OUTCOMES AND MEASURES

Subgroups exhibiting similar response patterns were derived from repeated measures of overall depression severity obtained using the Montgomery-Asberg Depression Rating Scale.

RESULTS

Among the 453 study participants, 3 subgroups with differing baseline depression severity clearly responded to treatment: one group with the lowest baseline severity had a rapid response (n = 69 [15.23%]), and distinct responses were also apparent among groups starting at moderate (n = 108 [23.84%]) and higher (n = 25 [5.52%]) baseline symptom levels. Three subgroups had nonresponding trajectories: 2 with high baseline symptom levels (totaling 35.98%: high, nonresponse 1, n = 110 [24.28%]; high, nonresponse 2, n = 53 [11.70%]) and 1 with moderate baseline symptom levels (n = 88 [19.43%]). Several factors were independently associated with having a nonresponsive trajectory, including greater baseline depression severity, longer episode duration, less subjective sleep loss, more guilt, and more work/activity impairment (P < .05). Higher delayed memory (list recognition) performance was independently associated with having a rapid response (adjusted odds ratio = 2.22; 95% CI, 1.18-4.20).

CONCLUSIONS AND RELEVANCE

Based on the observed trajectory patterns, patients who have late-life depression with high baseline depression severity are unlikely to respond after 12 weeks of treatment with venlafaxine XR. However, high baseline depression severity alone may be neither a necessary nor sufficient predictor of treatment nonresponse.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT00892047.

Hypersomnia in Mood Disorders: a Rapidly Changing Landscape

Hypersomnia is commonly comorbid with depressive illness and is associated with treatment resistance, symptomatic relapse, and functional impairment. This review highlights recent changes in nosological classifications of hypersomnia. In addition, emergent findings regarding the neurobiologic underpinnings, assessment, and treatment of hypersomnia in mood disorders are reviewed, as well as the effects of hypersomnolence on illness course. Future strategies for research are proposed that may elucidate the causes of hypersomnia in mood disorders and lead to the development of improved diagnostic and therapeutic strategies.

Hamilton depression rating subscales to predict antidepressant treatment outcome in the early course of treatment

BACKGROUND

Hamilton depression rating scale (HAMD) subscales provide an economic alternative for the full scale; however, their ability to detect onset of improvement in the early course of treatment (EI) has not yet been researched. The present study investigated in patients with major depression (MD) whether the subscales are a comparable option to predict treatment remission in the early course of treatment.

METHODS

Based on data from 210 MD patients of a 6-week randomised, placebo-controlled trial comparing mirtazapine (MIR) and paroxetine (PAR), the discriminative and predictive validity of EI for (stable) remission at treatment end was evaluated for seven subscales and the HAMD17 in the total and in treatment subgroups (MIR vs. PAR). Receiver operating characteristics (ROC) curves (at week 2) and the Clinical Global Impression scales (CGI) (at study endpoint) were used to validate the 20% EI criterion for the subscales.

RESULTS

Only the Evans6 and Toronto7 subscale had almost the same predictive value as the HAMD17 (e.g., sensitivities stable remission Evans6/Toronto7: 96/95% vs. 96% HAMD17). The optimal cut-off for EI to predict remission was just below 20% for most subscales and slightly over 20% for stable remission.

LIMITATIONS

Study sample representativeness, non-independence of subscales, missing external validation criterion, lack of control group.

CONCLUSIONS

The Evans6 and Toronto7 subscales are valuable alternatives in situations, where economic aspects play a larger role. A sum score reduction of ≥20% as definition for EI seems also appropriate for the HAMD subscales, in the total as well as in the antidepressant subgroups.