Predictors and moderators of time to remission of major depression with interpersonal psychotherapy and SSRI pharmacotherapy

Longitudinal trajectories of psychosocial functioning in patients with pre-existing mental disorders after one year of COVID-19 pandemic

Aims of the present study were to prospectively assess psychosocial functioning trajectories during the COVID pandemic and the possible impact of sociodemographic variables, as well as of COVID-19 pandemic-related factors, on these trajectories, in a sample of patients with pre-existing severe mental disorders. Moreover, we aimed at identifying predictors of impairment in psychosocial functioning over a period of 9 months of COVID-19 pandemic. Patients were recruited during the 3rd wave of the COVID-19 pandemic (T0, March-April 2021) while strict containment measures were applied in Italy, and reassessed after 3 months (T1, June-July 2021), and after 6 months from T1 (T2- November-December 2021), during the 4th wave of COVID pandemic. A sample of 300 subject (out of the 527 subjects recruited at baseline) completed the T2 evaluation. Patients were assessed by: Work and Social Adjustment Scale (WSAS) for psychosocial functioning, Generalized Anxiety Disorder 7-Item (GAD-7) for anxiety symptoms, Patient Health Questionnaire-9 (PHQ-9) for depressive symptoms and the Impact of Events Scale-Revised, for post-traumatic symptoms. Cluster analyses identified 4 trajectories of functioning: the High, Stable Functioning group (N = 77), the Improvement Functioning group (N = 62), the Progressive Impairment group (N = 83) and the Persistent Severe Impairment group (N = 78) respectively. We found that predictors of higher WSAS score at T2 were higher WSAS score at T0 (B = 0.43, p < .001), PHQ scores at baseline >10 (B = 2.89, p < .05), while not living alone was found to be a protective factor (B = -2.5, p < .05). Results of the present study provides insights into the vulnerability of individuals with psychiatric disorders during times of crisis. Study findings can contribute to a better understanding of the specific needs of this population and inform interventions and support strategies.

Examining factors related to low performance of predicting remission in participants with major depressive disorder using neuroimaging data and other clinical features

Major depressive disorder (MDD), a prevalent mental health issue, affects more than 8% of the US population, and almost 17% in the young group of 18-25 years old. Since Covid-19, its prevalence has become even more significant. However, the remission (being free of depression) rates of first-line antidepressant treatments on MDD are only about 30%. To improve treatment outcomes, researchers have built various predictive models for treatment responses and yet none of them have been adopted in clinical use. One reason is that most predictive models are based on data from subjective questionnaires, which are less reliable. Neuroimaging data are promising objective prognostic factors, but they are expensive to obtain and hence predictive models using neuroimaging data are limited and such studies were usually in small scale (N<100). In this paper, we proposed an advanced machine learning (ML) pipeline for small training dataset with large number of features. We implemented multiple imputation for missing data and repeated K-fold cross validation (CV) to robustly estimate predictive performances. Different feature selection methods and stacking methods using 6 general ML models including random forest, gradient boosting decision tree, XGBoost, penalized logistic regression, support vector machine (SVM), and neural network were examined to evaluate the model performances. All predictive models were compared using model performance metrics such as accuracy, balanced accuracy, area under ROC curve (AUC), sensitivity and specificity. Our proposed ML pipeline was applied to a training dataset and obtained an accuracy and AUC above 0.80. But such high performance failed while applying our ML pipeline using an external validation dataset from the EMBARC study which is a multi-center study. We further examined the possible reasons especially the site heterogeneity issue.

Baseline depression severity as moderator on depression outcomes in psychotherapy and pharmacotherapy

BACKGROUND

Evidence-based treatments for adult depression include psychotherapy and pharmacotherapy, yet little is known about how baseline depression severity moderates treatment outcome.

OBJECTIVES

We aimed to compare the effects of psychotherapy and pharmacotherapy for adult depression and to examine the association between baseline depression severity and treatment outcome, converting multiple baseline depression measures into the scores of the Beck Depression Inventory, second edition (BDI-II).

METHODS

We conducted systematic searches in bibliographical databases up to September 2022 to identify randomized controlled trials (RCTs) in which psychotherapy was compared with pharmacotherapy in the treatment of adult depression. Various meta-regressions using the baseline depression severity as predictor of the relative effects of psychotherapy and pharmacotherapy were performed.

RESULTS

We identified 65 RCTs including 7250 participants for the meta-analyses and 56 RCTs including 5548 participants for the meta-regression. We found no significant difference between psychotherapy and pharmacotherapy (g = -0.08, 95 % CI: -0.2 to 0.04, p = 0.193) and baseline depression severity was not significantly associated with the relative effects of psychotherapy and pharmacotherapy (B = 0.0032, SE = 0.0096, p = 0.74). Results were similar in several sensitivity analyses.

LIMITATIONS

Limitations included the low quality of the included studies, and the omission of long-term effects and within-study variability.

CONCLUSIONS

We found no indication for a moderation effect of baseline depression severity on the relative effects of psychotherapy and pharmacotherapy. Thus, other factors such as availability and patients' preference must be considered when deciding for treatment options.

The relationship of separation anxiety with the age of onset of panic disorder

AIM

This study aimed to investigate whether separation anxiety (SA) constitutes a dimension related to age at onset of panic disorder (PD), in homogeneous subgroups of outpatients with PD, based on their age of onset and symptom severity.

METHODS

A sample of 232 outpatients with PD was assessed with the Panic Disorder Severity Scale (PDSS) and the Sheehan Disability Scale (SDS) for functional impairments. Separation anxiety was evaluated using structured interviews and questionnaires. We applied a K-Means Cluster Analysis based on the standardized "PD age of onset" and "the PDSS total score" to identify distinct but homogeneous groups.

RESULTS

We identified three groups of patients: group 1 ("PD early onset/severe", N = 97, 42%, onset 23.2 ± 6.7 years), group 2 ("PD early onset/not severe", N = 76, 33%, onset 23.4 ± 6.0 years) and group 3 ("PD adult onset/not severe", N = 59, 25%, onset 42.8 ± 7.0 years). Patients with early onset/severe PD had significantly higher scores on all SA measures than PD late-onset/not severe. Regression analyses showed that SA scores, but not PDSS scores, were predictive of impairment in SDS work/school, social life, and family functioning domains.

CONCLUSIONS

Our data indicate a significant relationship between SA and PD with an earlier age of onset and an impact on individual functioning. This may have important implications for implementing preventive interventions targeting early risk factors for the subsequent onset of PD.

A Novel Approach to Clustering Accelerometer Data for Application in Passive Predictions of Changes in Depression Severity

The treatment of mood disorders, which can become a lifelong process, varies widely in efficacy between individuals. Most options to monitor mood rely on subjective self-reports and clinical visits, which can be burdensome and may not portray an accurate representation of what the individual is experiencing. A passive method to monitor mood could be a useful tool for those with these disorders. Some previously proposed models utilized sensors from smartphones and wearables, such as the accelerometer. This study examined a novel approach of processing accelerometer data collected from smartphones only while participants of the open-science branch of the BiAffect study were typing. The data were modeled by von Mises-Fisher distributions and weighted networks to identify clusters relating to different typing positions unique for each participant. Longitudinal features were derived from the clustered data and used in machine learning models to predict clinically relevant changes in depression from clinical and typing measures. Model accuracy was approximately 95%, with 97% area under the ROC curve (AUC). The accelerometer features outperformed the vast majority of clinical and typing features, which suggested that this new approach to analyzing accelerometer data could contribute towards unobtrusive detection of changes in depression severity without the need for clinical input.

Worse off by waiting for treatment? The impact of waiting time on clinical course and treatment outcome for depression in routine care

BACKGROUND

Long-term untreated major depressive disorder (MDD) is associated with a less favorable clinical course. Waiting time, defined as the interval between diagnostic workup and treatment initiation, may be clinically relevant given the prolongation of the pre-existing duration of untreated MDD. However, it is currently unknown whether and to what extent waiting time affects treatment course in routine outpatient care.

METHODS

Retrospectively extracted data from 715 outpatients with MDD who received naturalistic outpatient MDD treatment were examined. Treatment outcome was defined as the difference in depression severity at the start of treatment and six months thereafter. Clinical course during waiting time was defined by the difference in severity at diagnostic workup and at treatment initiation. We analyzed the association between waiting time and treatment outcome and between waiting time and clinical course during this waiting time using multivariable regression analyses. We adjusted for severity and suicidality as potential confounders.

RESULTS

An increased duration of the waiting time was associated with a less favorable treatment outcome (B = 0.049, SE = 0.019, p = 0.01). This association persisted after adjustment for potential confounders (B = 0.053, SE = 0.02, p = 0.01). No association was found between length of waiting time and clinical course during waiting time.

LIMITATIONS

Strict definitions resulted in smaller sample sizes for the final analyses. The uncontrolled design may be questionable to definitively establish the impact of waiting time on treatment outcome.

CONCLUSIONS

A prolonged waiting time is significantly associated with less favorable treatment outcome. Reduction of waiting time deserves priority in depression treatment planning to improve clinical outcomes.

Nonpharmacologic and Pharmacologic Treatments of Adult Patients With Major Depressive Disorder: A Systematic Review and Network Meta-analysis for a Clinical Guideline by the American College of Physicians

BACKGROUND

Primary care patients and clinicians may prefer alternative options to second-generation antidepressants for major depressive disorder (MDD).

PURPOSE

To compare the benefits and harms of nonpharmacologic treatments with second-generation antidepressants as first-step interventions for acute MDD, and to compare second-step treatment strategies for patients who did not achieve remission after an initial attempt with antidepressants.

DATA SOURCES

English-language studies from several electronic databases from 1 January 1990 to 8 August 2022, trial registries, gray literature databases, and reference lists to identify unpublished research.

STUDY SELECTION

2 investigators independently selected randomized trials of at least 6 weeks' duration.

DATA EXTRACTION

Reviewers abstracted data about study design and conduct, participants, interventions, and outcomes. They dually rated the risk of bias of studies and the certainty of evidence for outcomes of interest.

DATA SYNTHESIS

65 randomized trials met the inclusion criteria; eligible data from nonrandomized studies were not found. Meta-analyses and network meta-analyses indicated similar benefits of most nonpharmacologic treatments and antidepressants as first-step treatments. Antidepressants had higher risks for discontinuation because of adverse events than most other treatments. For second-step therapies, different switching and augmentation strategies provided similar symptomatic relief. The certainty of evidence for most comparisons is low; findings should be interpreted cautiously.

LIMITATIONS

Many studies had methodological limitations or dosing inequalities; publication bias might have affected some comparisons. In some cases, conclusions could not be drawn because of insufficient evidence.

CONCLUSION

Although benefits seem to be similar among first- and second-step MDD treatments, the certainty of evidence is low for most comparisons. Clinicians and patients should focus on options with the most reliable evidence and take adverse event profiles and patient preferences into consideration.

PRIMARY FUNDING SOURCE

American College of Physicians. (PROSPERO: CRD42020204703).

Perspectives on the success rate of current antidepressant pharmacotherapy

INTRODUCTION

There has been growing debate about the effectiveness of traditional antidepressants for the treatment of depression, and whether the clinical trials literature overstates the value of existing agents. Antidepressant efficacy is limited by suboptimal remission rates, lack of robust efficacy across diverse depressed subgroups, slow onset, and challenges managing tolerability. Clinicians can better navigate uncertainties in this area by recognizing patient-specific clinical and prognostic factors that influence the likelihood of antidepressant drug response.

AREAS COVERED

The author summarizes pertinent literature regarding drug-placebo differences in antidepressant outcome as well as patient-specific factors that influence antidepressant drug responsivity across subtypes of depressive disorders.

EXPERT OPINION

Standardized effect sizes for most monoaminergic antidepressants are relatively modest. At least one-third of treatment response derives from nonspecific (yet substantial) placebo effects, limiting the ability to compare antidepressant medication effects to that of "no treatment." Patients with high baseline depressive symptom severity are less likely to respond to placebo but may be more responsive to antidepressant pharmacotherapy than is the case in mild forms of depression. Patient satisfaction with antidepressant response must take into consideration not only efficacy for reducing symptoms but also drug tolerability/acceptability and tangible improvement in functional outcome and quality of life.

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.

Inpatient psychotherapy for depression in a large routine clinical care sample: A Bayesian approach to examining clinical outcomes and predictors of change

BACKGROUND

A routinely collected dataset was analyzed (1) to determine the naturalistic effectiveness of inpatient psychotherapy for depression in routine psychotherapeutic care, and (2) to identify potential predictors of change.

METHODS

In a sample of 22,681 inpatients with depression, pre-post and pre-follow-up effect sizes were computed for various outcome variables. To build a probabilistic model of predictors of change, an independent component analysis generated components from demographic and clinical data, and Bayesian EFA extracted factors from the available pre-test, post-test and follow-up questionnaires in a subsample (N = 6377). To select the best-fitted model, the BIC of different path models were compared. A Bayesian path analysis was performed to identify the most important factors to predict changes.

RESULTS

Effect sizes were large for the primary outcome and moderate for various secondary outcomes. Almost all pretreatment factors exerted significant influences on different baseline factors. Several factors were found to be resistant to change during treatment: suicidality, agoraphobia, life dissatisfaction, physical disability and pain. The strongest cross-loadings were observed from suicidality on negative cognitions, from agoraphobia on anxiety, and from physical disability on perceived disability.

LIMITATIONS

No causal conclusions can be drawn directly from our results as we only used cross-lagged panel data without control group.

CONCLUSIONS

The results indicate large effects of inpatient psychotherapy for depression in routine clinical care. The direct influence of pretreatment factors decreased over the course of treatment. However, some factors appeared stable and difficult to treat, which might hinder treatment outcome. Findings of different predictors of change are discussed.

Does psychological process change during psychotherapy predict long-term depression outcome after successful cognitive therapy or interpersonal psychotherapy? Secondary analysis of a randomized trial

OBJECTIVE

Psychotherapies for depression are similarly effective, but the processes through which these therapies work have not been identified. We focus on psychological process changes during therapy as predictors of long-term depression outcome in treatment responders.

METHOD

Secondary analysis of a randomized trial comparing cognitive therapy (CT) and interpersonal psychotherapy (IPT) that focuses on 85 treatment responders. Using mixed-effects models, changes during therapy (0-7 months) on nine process variables were associated with depression severity (BDI-II) at follow-up (7-24 months).

RESULTS

A decrease in dysfunctional attitudes was associated with a decrease in depression scores over time. Improved self-esteem was associated with less depression at follow-up (borderline significant). More improvement in both work and social functioning and interpersonal problems was associated with better depression outcomes in IPT relative to CT, while less improvement in work and social functioning and interpersonal problems was associated with better outcomes in CT relative to IPT.

CONCLUSIONS

Less negative thinking during therapy is associated with lower depression severity in time, while changes during therapy in work and social functioning and interpersonal problems appear to predict different long-term outcomes in CT vs. IPT. If replicated, these findings can be used to guide clinical decision-making during psychotherapy.

The ADHD teen integrative data analysis longitudinal (TIDAL) dataset: background, methodology, and aims

BACKGROUND

The Attention Deficit Hyperactivity Disorder (ADHD) Teen Integrative Data Analysis Longitudinal (TIDAL) dataset integrates data from four randomized trials.

METHOD

Participants with ADHD (N = 854; 72.5% male, 92.5% racial/ethnic minority, ages 10-17) were assessed three times across 12 months. Data includes parent, self, and teacher ratings, observations, and school records. The battery was harmonized using an Integrative Data Analysis (IDA) approach to form variables that assign unique values to all participants.

RESULTS

The data will be used to investigate: (1) profiles that organize the heterogeneous population into clinically meaningful subgroups, (2) whether these profiles predict treatment response, (3) heterogeneity in treatment response and variables that predict this response, (4) how treatment characteristics and adjunctive supports predict treatment response, and (5) mediators of treatment and whether these mechanisms are moderated by treatment characteristics.

CONCLUSIONS

The ADHD TIDAL Dataset will be openly shared with the field to maximize its utility.

Psychotherapy or medication for depression? Using individual symptom meta-analyses to derive a Symptom-Oriented Therapy (SOrT) metric for a personalised psychiatry

BACKGROUND

Antidepressant medication (ADM) and psychotherapy are effective treatments for major depressive disorder (MDD). It is unclear, however, if treatments differ in their effectiveness at the symptom level and whether symptom information can be utilised to inform treatment allocation. The present study synthesises comparative effectiveness information from randomised controlled trials (RCTs) of ADM versus psychotherapy for MDD at the symptom level and develops and tests the Symptom-Oriented Therapy (SOrT) metric for precision treatment allocation.

METHODS

First, we conducted systematic review and meta-analyses of RCTs comparing ADM and psychotherapy at the individual symptom level. We searched PubMed Medline, PsycINFO, and the Cochrane Central Register of Controlled Trials databases, a database specific for psychotherapy RCTs, and looked for unpublished RCTs. Random-effects meta-analyses were applied on sum-scores and for individual symptoms for the Hamilton Rating Scale for Depression (HAM-D) and Beck Depression Inventory (BDI) measures. Second, we computed the SOrT metric, which combines meta-analytic effect sizes with patients' symptom profiles. The SOrT metric was evaluated using data from the Munich Antidepressant Response Signature (MARS) study (n = 407) and the Emory Predictors of Remission in Depression to Individual and Combined Treatments (PReDICT) study (n = 234).

RESULTS

The systematic review identified 38 RCTs for qualitative inclusion, 27 and 19 for quantitative inclusion at the sum-score level, and 9 and 4 for quantitative inclusion on individual symptom level for the HAM-D and BDI, respectively. Neither meta-analytic strategy revealed significant differences in the effectiveness of ADM and psychotherapy across the two depression measures. The SOrT metric did not show meaningful associations with other clinical variables in the MARS sample, and there was no indication of utility of the metric for better treatment allocation from PReDICT data.

CONCLUSIONS

This registered report showed no differences of ADM and psychotherapy for the treatment of MDD at sum-score and symptom levels. Symptom-based metrics such as the proposed SOrT metric do not inform allocation to these treatments, but predictive value of symptom information requires further testing for other treatment comparisons.

Interpersonal Psychotherapy: A Scoping Review and Historical Perspective (1974-2017)

BACKGROUND

Interpersonal Psychotherapy (IPT) is an affect- and relationally focused, time-limited treatment supported by research spanning >4 decades. IPT focuses on stressful interpersonal experiences of loss, life changes, disputes, and social isolation. It emphasizes the role of relationships in recovery. This scoping review describes, within a historical perspective, IPT's evolution as an evidence-supported treatment of psychiatric disorders.

METHODS

English-language publications (n = 1119) identified via EMBASE, MEDLINE, PsycINFO, and Web of Science databases (1974-2017), augmented with manual reference searches, were coded for clinical focus, population demographics, format, setting, publication type, and research type. Quantitative and qualitative analyses identified IPT publications' characteristics and trends over four epochs of psychotherapy research.

RESULTS

IPT literature primarily focused on depression (n = 772 articles; 69%), eating disorders (n = 135; 12%), anxiety disorders (n = 68; 6%), and bipolar disorder (n = 44; 4%), with rising publication rates and numbers of well-conducted randomized, controlled trials over time, justifying inclusion in consensus treatment guidelines. Research trends shifted from efficacy trials to effectiveness studies and population-based dissemination initiatives. Process research examined correlates of improvement and efficacy moderators. Innovations included global initiatives, prevention trials, and digital, web-based training and treatment.

CONCLUSION

Sparked by clinical innovations and scientific advances, IPT has evolved as an effective treatment of psychiatric disorders across the lifespan for diverse patients, including underserved clinical populations. Future research to elucidate mechanisms of change, improve access, and adapt to changing frameworks of psychopathology and treatment planning is needed. IPT addresses the universal centrality of relationships to mental health, which is as relevant today as it was over 40 years ago.

Treatment Modalities and Perceived Effectiveness of Treatment Among Adults With Depression

Patient-reported outcomes of mental health treatment, such as perceived effectiveness, are important. They indicate whether treatment is perceived to reduce symptoms and minimize psychiatric disability. Outpatient treatment for depression typically includes medication or counseling, either alone or in combination. This study examines the relationship between treatment modality and perceived effectiveness of treatment. Using a sample of adults who received outpatient treatment for depression from the 2015-2016 National Survey on Drug Use and Health (N = 4169), logistic regressions estimated the odds of rating treatment as effective among persons who received medication only, counseling only, and a combination of medication and counseling. There were no differences in perceived effectiveness between counseling only and medication only. However, receiving both was associated with greater odds of rating treatment as effective. Poor self-rated health and severe mental illness were associated with lower perceived effectiveness of medication. Those with substance use problems had lower odds of rating counseling and both counseling and medication as effective. A combined treatment for depression may be perceived as better than single-modality treatment. Therefore, there might be benefits to increasing access to both forms of treatment for persons less likely to rate either single modality as effective.

A network meta-analysis of the effects of psychotherapies, pharmacotherapies and their combination in the treatment of adult depression

No network meta-analysis has examined the relative effects of psychotherapies, pharmacotherapies and their combination in the treatment of adult depression, while this is a very important clinical issue. We conducted systematic searches in bibliographical databases to identify randomized trials in which a psychotherapy and a pharmacotherapy for the acute or long-term treatment of depression were compared with each other, or in which the combination of a psychotherapy and a pharmacotherapy was compared with either one alone. The main outcome was treatment response (50% improvement between baseline and endpoint). Remission and acceptability (defined as study drop-out for any reason) were also examined. Possible moderators that were assessed included chronic and treatment-resistant depression and baseline severity of depression. Data were pooled as relative risk (RR) using a random-effects model. A total of 101 studies with 11,910 patients were included. Depression in most studies was moderate to severe. In the network meta-analysis, combined treatment was more effective than psychotherapy alone (RR=1.27; 95% CI: 1.14-1.39) and pharmacotherapy alone (RR=1.25; 95% CI: 1.14-1.37) in achieving response at the end of treatment. No significant difference was found between psychotherapy alone and pharmacotherapy alone (RR=0.99; 95% CI: 0.92-1.08). Similar results were found for remission. Combined treatment (RR=1.23; 95% CI: 1.05-1.45) and psychotherapy alone (RR=1.17; 95% CI: 1.02-1.32) were more acceptable than pharmacotherapy. Results were similar for chronic and treatment-resistant depression. The combination of psychotherapy and pharmacotherapy seems to be the best choice for patients with moderate depression. More research is needed on long-term effects of treatments (including cost-effectiveness), on the impact of specific pharmacological and non-pharmacological approaches, and on the effects in specific populations of patients.

The Work and Social Adjustment Scale, Youth and Parent Versions: Psychometric Evaluation of a Brief Measure of Functional Impairment in Young People

The Work and Social Adjustment Scale (WSAS) is a brief global measure of functional impairment that is widely used in adult health. We have adapted the WSAS for its use in youth, the WSAS-Youth version (WSAS-Y) and WSAS-Parent version (WSAS-P). This study evaluated the psychometric properties of the scale. The internal consistency, factor structure, convergent and divergent validity, test-retest reliability and sensitivity to change of the WSAS-Y/P were studied in 525 children and adolescents with obsessive-compulsive disorder and related disorders receiving treatment. The internal consistency of the WSAS-Y/P was excellent across diagnostic groups and time-points. Exploratory factor analysis extracted a single-factor of functional impairment, explaining in excess of 85% of the variance. The test-retest reliability was adequate. The WSAS-Y/P correlated more strongly with other measures of functional impairment than with measures of symptom severity, indicating good convergent/divergent validity. Finally, the WSAS-Y/P was highly sensitive to change after treatment.

Towards personalising treatment: a systematic review and meta-analysis of face-to-face efficacy moderators of cognitive-behavioral therapy and interpersonal psychotherapy for major depressive disorder

BACKGROUND

Consistent evidence suggests that face-to-face cognitive-behavioural therapy (CBT) and interpersonal psychotherapy (IPT) may be equally effective depression treatments. Current clinical research focuses on detecting the best predictors-moderators of efficacy to guide treatment personalisation. However, individual moderator studies show inconsistent findings. This systematic review and meta-analysis aimed to compare the efficacy of CBT and IPT, including combined treatment with antidepressants for depression, and evaluate the predictive power of demographic, clinical presentation and treatment characteristics moderators for both therapies.

METHODS

PsycArticles, PsycINFO, PubMed and Cochrane Library were systematically searched through December 2017 for studies that have assessed individuals with major depression receiving either CBT or IPT in a face-to-face format both at pre- and post-treatment. Random-effects moderator meta-analyses were conducted.

RESULTS

In total 168 samples from 137 studies including 11 374 participants qualified for the meta-analytic review. CBT and IPT were equally effective across all but one prespecified moderators. For psychotherapy delivered without concomitant antidepressant treatment [antidepressant medications (ADMs)], CBT was superior to IPT (g = 1.68, Qbetweenp = 0.037). Within-CBT moderator analyses showed that increased CBT efficacy was associated with lower age, high initial depression severity, individual format of administration and no adjunctive ADMs. Within-IPT analyses showed comparable efficacy across all moderators.

CONCLUSIONS

Clinical guidance around combined treatment (psychotherapy plus ADMs) should be reconsidered. CBT alone is superior to IPT alone and to combined treatment, while IPT alone is non-inferior to combined treatment. More research is needed to assess the moderating effect of older age and number of previous episodes on IPT efficacy.

Newly diagnosed patients with advanced non-small cell lung cancer: A clinical description of those with moderate to severe depressive symptoms

OBJECTIVES

The aims of this observational study were to 1) accrue newly diagnosed patients with advanced-stage non-small cell lung cancer (NSCLC) awaiting the start of first-line treatment and identify those with moderate to severe depressive symptoms and, 2) provide a clinical description of the multiple, co-occurring psychological and behavioral difficulties and physical symptoms that potentially exacerbate and maintain depressive symptoms.

MATERIALS AND METHODS

Patients with stage IV NSCLC (N = 186) were enrolled in an observational study (ClinicalTrials.gov Identifier: NCT03199651) and completed the American Society of Clinical Oncology-recommended screening measure for depression (Patient Health Questionnaire-9 [PHQ-9]). Individuals with none/mild (n = 119; 64 %), moderate (n = 52; 28 %), and severe (n = 15; 8 %) depressive symptoms were identified. Patients also completed measures of hopelessness, generalized anxiety disorder (GAD) symptoms, stress, illness perceptions, functional status, and symptoms.

RESULTS

Patients with severe depressive symptoms reported concomitant feelings of hopelessness (elevating risk for suicidal behavior), anxiety symptoms suggestive of GAD, and traumatic, cancer-specific stress. They perceived lung cancer as consequential for their lives and not controllable with treatment. Pain and multiple severe symptoms were present along with substantial functional impairment. Patients with moderate depressive symptoms had generally lower levels of disturbance, though still substantial. The most salient differences were low GAD symptom severity and fewer functional impairments for those with moderate symptoms.

CONCLUSIONS

Depressive symptoms of moderate to severe levels co-occur in a matrix of clinical levels of anxiety symptoms, traumatic stress, impaired functional status, and pain and other physical symptoms. All of the latter factors have been shown, individually and collectively, to contribute to the maintenance or exacerbation of depressive symptoms. As life-extending targeted and immunotherapy use expands, prompt identification of patients with moderate to severe depressive symptoms, referral for evaluation, and psychological/behavioral treatment are key to maximizing treatment outcomes and quality of life for individuals with advanced NSCLC.

Inflammation Mediates Body Weight and Ageing Effects on Psychomotor Slowing

Inflammation (immune system activation) affects neuronal function and may have consequences for the efficiency and speed of functional brain processes. Indeed, unusually slow psychomotor speed, a measure predictive of behavioural performance and health outcomes, is found with obesity and ageing, two conditions also associated with chronic inflammation. Yet whether inflammation is the mediating factor remains unclear. Here, we assessed inflammation by indexing interleukin-6 level in blood and measured psychomotor speed as well as indices of selective visual attention in young (mean = 26 years) or old (mean = 71 years) adults (N = 83) who were either lean or currently significantly overweight (mean body mass index = 22.4 and 33.8, respectively). Inflammation was positively and significantly correlated with psychomotor speed, age, and body mass index but not with attention measures. Using mediation analyses we show for the first time that inflammation fully accounts for the significant psychomotor slowing found in those with high BMI. Moreover, we further show that age-related psychomotor slowing is partially mediated by inflammation. These findings support the proposal that reducing inflammation may mitigate weight- and age-related cognitive decline and thereby improve performance on daily tasks and health outcomes more generally.

A machine learning ensemble to predict treatment outcomes following an Internet intervention for depression

BACKGROUND

Some Internet interventions are regarded as effective treatments for adult depression, but less is known about who responds to this form of treatment.

METHOD

An elastic net and random forest were trained to predict depression symptoms and related disability after an 8-week course of an Internet intervention, Deprexis, involving adults (N = 283) from across the USA. Candidate predictors included psychopathology, demographics, treatment expectancies, treatment usage, and environmental context obtained from population databases. Model performance was evaluated using predictive R2$\lpar R_{{\rm pred}}^2\rpar\comma $ the expected variance explained in a new sample, estimated by 10 repetitions of 10-fold cross-validation.

RESULTS

An ensemble model was created by averaging the predictions of the elastic net and random forest. Model performance was compared with a benchmark linear autoregressive model that predicted each outcome using only its baseline. The ensemble predicted more variance in post-treatment depression (8.0% gain, 95% CI 0.8-15; total $R_{{\rm pred}}^2 \; $= 0.25), disability (5.0% gain, 95% CI -0.3 to 10; total $R_{{\rm pred}}^2 \; $= 0.25), and well-being (11.6% gain, 95% CI 4.9-19; total $R_{{\rm pred}}^2 \; $= 0.29) than the benchmark model. Important predictors included comorbid psychopathology, particularly total psychopathology and dysthymia, low symptom-related disability, treatment credibility, lower access to therapists, and time spent using certain Deprexis modules.

CONCLUSION

A number of variables predict symptom improvement following an Internet intervention, but each of these variables makes relatively small contributions. Machine learning ensembles may be a promising statistical approach for identifying the cumulative contribution of many weak predictors to psychosocial depression treatment response.

The decision tool unipolar depression (DTUD): a new measure to facilitate the early identification of patients with major depressive disorder in need of highly specialized care

BACKGROUND

Selection of the optimal initial treatment in patients with major depressive disorder (MDD) in need of highly specialized care has the potential to benefit treatment outcomes and cost-effectiveness of treatment strategies. However, to date, there is a paucity of measures that could guide the selection of the initial treatment, in particular to indicate which patients with MDD are in need of highly specialized care. Recognizing this gap, this paper reports on the development and psychometric evaluation of the Decision Tool Unipolar Depression (DTUD), aimed to facilitate the early identification of patients with MDD in need of highly specialized care.

METHODS

The DTUD was developed using a mixed-methods approach, consisting of a systematic review and a concept mapping study. To evaluate the psychometric features of the DTUD, a cross-sectional multicenter study was conducted. A total of 243 patients with MDD were evaluated with the DTUD. Feasibility was operationalized as the time required to complete the DTUD and the content clarity of the DTUD. Inter-rater reliability was evaluated using Krippendorf's alpha. The Maudsley Staging Method (MSM) and the Dutch Measure for quantification of Treatment Resistance in Depression (DM-TRD) were administered to assess the convergent validity. A receiver operator characteristic curve was generated to evaluate the criterion validity and establish the optimal cut-off value.

RESULTS

The mean administration time was 4.49 min (SD = 2.71), and the content of the total DTUD was judged as clear in 94.7% of the evaluations. Inter-rater reliability values ranged from 0.69 to 0.91. Higher scores on the DTUD were associated with higher scores on the MSM (r_s = 0.47) and DM-TRD (r_s = 0.53). Based on the maximum Youden index (0.494), maximum discrimination was reached at a cut-off score of ≥5 (sensitivity 67%, specificity 83%).

CONCLUSION

The DTUD demonstrated to be a tool with solid psychometric properties and, therefore, is a promising measure for the early identification of patients with MDD in need of highly specialized care. Use of the DTUD has the potential to facilitate the selection and initiation of the optimal initial treatment in patients with MDD, which in turn may improve the clinical effectiveness and cost-effectiveness of treatment strategies.

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.

Dismantling, personalising and optimising internet cognitive-behavioural therapy for depression: a study protocol for individual participant data component network meta-analysis

INTRODUCTION

Psychotherapy is a complex intervention, consisting of various components and being implemented flexibly in consideration of individual patient's characteristics. It is then of utmost importance to know which of the various components or combinations thereof are more efficacious, what their specific effect sizes are and which types of patients may benefit more from different components or their combinations.

METHODS AND ANALYSIS

Internet-delivered cognitive-behavioural therapy (iCBT) offers a unique opportunity to systematically review and quantitatively disentangle the efficacy of various components because, unlike face-to-face cognitive-behavioural therapy, it allows identification of constituent components that are actually delivered to patients. We will systematically identify all randomised controlled trials that compared any form of iCBT against another form or a control intervention in the acute phase treatment of adult depression. We will apply component network meta-analysis (cNMA) to dismantle efficacy of individual components. We will use individual participant data in the cNMA to identify participant-level prognostic factors and effect modifiers for different components.

ETHICS AND DISSEMINATION

The investigators of the primary trials will have obtained ethical approval for the data used in the present study and for sharing the data, if this was necessary, according to local requirements and was not covered from the initial ethic assessment. Results from this study will be published in peer-reviewed journals and presented at relevant conferences.

PROSPERO REGISTRATION NUMBER

CRD42018104683.

Temperament traits and remission of depression: A naturalistic six-month longitudinal study

BACKGROUND

The aim of this naturalistic longitudinal study was to add evidence regarding the potential of Cloninger's temperament traits (novelty seeking, harm avoidance, reward dependence and persistence) for predicting the effect of pharmacological treatment on the rates of therapeutic response and remission.

METHODS

The study was based on 200 outpatients with unipolar depressive disorders of different severity and course of illness, and extended up to 6 months of follow-up. Patients were assessed in their temperament with the Tridimensional Personality Questionnaire (TPQ) and their condition was classified (in course and severity) according to the International Classification of Diseases, Tenth revision (ICD-10) diagnostic criteria for research. Patients were blindly rated (concerning other predicting variables) on the improved Clinical Global Impression-Severity scale for depression (iCGI-S) at baseline, 6 weeks, 3 months and 6 months. Outcome measures at the last observation carried forward were therapeutic response (reduction of ≥50% in the last iCGI-S) and remission (last iCGI-S = 0), which were available for 187 patients.

RESULTS

Remission was independently and directly associated with length of follow-up, and inversely with the baseline iCGI-S score and harm avoidance (patients in the high tertile had a 2.7 likelihood of non-remission in comparison with those in the low tertile); persistence was found to have a complex, V-shape relationship with remission. Within a sub-sample of more severe cases (n = 118), having higher harm avoidance scores, a more favorable outcome was associated with higher reward dependence and the non-smoking condition.

LIMITATIONS

With a naturalistic, non-experimental design, the sample may not be representative of the general population.

CONCLUSIONS

Temperament traits may help predict outcome in patients treated for depression.

Do comorbid social and other anxiety disorders predict outcomes during and after cognitive therapy for depression?

BACKGROUND

Cognitive therapy (CT) improves symptoms in adults with major depressive disorder (MDD) plus comorbid anxiety disorder, but the specific type of anxiety may influence outcomes. This study compared CT outcomes among adults with MDD plus social, other, or no comorbid anxiety disorders.

METHODS

Outpatients with recurrent MDD (N = 523, including 87 with social and 110 with other comorbid anxiety disorders) received acute-phase CT. Higher risk responders (n = 241 with partial or unstable response) were randomized to 8 months of continuation treatment (CT or clinical management plus fluoxetine or pill placebo), followed by 24 months of assessment. Lower risk responders (n = 49) were assessed for 32 months without additional research treatment. Depression, anxiety symptoms, and social avoidance were measured repeatedly.

RESULTS

Other (non-social), but not social, anxiety disorders predicted elevated depression and anxiety symptoms throughout and after acute-phase CT. Social, but not other, anxiety disorder predicted greater reduction in depressive symptoms during acute-phase CT and elevated social avoidance during and after acute-phase CT.

LIMITATIONS

Anxiety disorders were assessed only before acute-phase treatment. The anxiety symptom measure was brief. Generalization to other patient populations and treatments is unknown.

CONCLUSIONS

Non-social comorbid anxiety disorders may reduce the efficacy of acute-phase CT for MDD by diminishing both short- and longer term outcomes relative to depressed patients without comorbid anxiety disorders. Comorbid social anxiety disorder may increase relative reductions in depressive symptoms during acute-phase CT for MDD, but patients with comorbid social anxiety disorder may require specialized focus on social avoidance during CT.

Cognitive-Behavioral Analysis System of Psychotherapy, Drug, or Their Combination for Persistent Depressive Disorder: Personalizing the Treatment Choice Using Individual Participant Data Network Metaregression

BACKGROUND

Persistent depressive disorder is prevalent, disabling, and often difficult to treat. The cognitive-behavioral analysis system of psychotherapy (CBASP) is the only psychotherapy specifically developed for its treatment. However, we do not know which of CBASP, antidepressant pharmacotherapy, or their combination is the most efficacious and for which types of patients. This study aims to present personalized prediction models to facilitate shared decision-making in treatment choices to match patients' characteristics and preferences based on individual participant data network metaregression.

METHODS

We conducted a comprehensive search for randomized controlled trials comparing any two of CBASP, pharmacotherapy, or their combination and sought individual participant data from identified trials. The primary outcomes were reduction in depressive symptom severity for efficacy and dropouts due to any reason for treatment acceptability.

RESULTS

All 3 identified studies (1,036 participants) were included in the present analyses. On average, the combination therapy showed significant superiority over both monotherapies in terms of efficacy and acceptability, while the latter 2 treatments showed essentially similar results. Baseline depression, anxiety, prior pharmacotherapy, age, and depression subtypes moderated their relative efficacy, which indicated that for certain subgroups of patients either drug therapy or CBASP alone was a recommendable treatment option that is less costly, may have fewer adverse effects and match an individual patient's preferences. An interactive web app (https://kokoro.med.kyoto-u.ac.jp/CBASP/prediction/) shows the predicted disease course for all possible combinations of patient characteristics.

CONCLUSIONS

Individual participant data network metaregression enables treatment recommendations based on individual patient characteristics.

Caffeine and Selective Adenosine Receptor Antagonists as New Therapeutic Tools for the Motivational Symptoms of Depression

Major depressive disorder is one of the most common and debilitating psychiatric disorders. Some of the motivational symptoms of depression, such anergia (lack of self-reported energy) and fatigue are relatively resistant to traditional treatments such as serotonin uptake inhibitors. Thus, new pharmacological targets are being investigated. Epidemiological data suggest that caffeine consumption can have an impact on aspects of depressive symptomatology. Caffeine is a non-selective adenosine antagonist for A1/A2A receptors, and has been demonstrated to modulate behavior in classical animal models of depression. Moreover, selective adenosine receptor antagonists are being assessed for their antidepressant effects in animal studies. This review focuses on how caffeine and selective adenosine antagonists can improve different aspects of depression in humans, as well as in animal models. The effects on motivational symptoms of depression such as anergia, fatigue, and psychomotor slowing receive particular attention. Thus, the ability of adenosine receptor antagonists to reverse the anergia induced by dopamine antagonism or depletion is of special interest. In conclusion, although further studies are needed, it appears that caffeine and selective adenosine receptor antagonists could be therapeutic agents for the treatment of motivational dysfunction in depression.

The influence of comorbid anxiety on the effectiveness of Cognitive Therapy and Interpersonal Psychotherapy for Major Depressive Disorder

BACKGROUND

Anxious depression is an important subtype of Major Depressive Disorder (MDD) defined by both syndromal (anxiety disorders) and dimensional (anxiety symptoms) criteria. A debated question is how anxiety affects MDD treatment. This study examined the impact of comorbid anxiety disorders and symptoms on the effectiveness of and dropout during Cognitive Therapy (CT) and Interpersonal Psychotherapy (IPT) for MDD.

METHODS

Depressed individuals were randomized to CT (n = 76) or IPT (n = 75). Outcome was depression severity measured with the Beck Depression Inventory-II (BDI-II) at the start of each therapy session, post treatment, and monthly up to five months follow-up. Anxiety disorders were assessed with the Structured Clinical Interview for DSM-IV Axis I disorders, (phobic) anxiety symptoms were assessed with Brief Symptom Inventory subscales.

RESULTS

Approximately one third of participants had a comorbid anxiety disorder. Comorbid anxiety disorders and anxiety symptoms were associated with less favorable depression change during IPT as compared to CT in the treatment phase, but not in the trial follow-up phase. Individuals with a comorbid anxiety disorder had significantly higher treatment dropout during both treatments.

LIMITATIONS

Not all therapists and participants were blind to the assessment of comorbid anxiety disorders and the assessments were performed by one rater.

CONCLUSIONS

A preference for CT over IPT for MDD is justifiable when comorbid anxiety is present, although long-term differences are not established and replication of this finding is needed. Clinicians should be aware of the risk of dropout for depressed individuals with an anxiety disorder.

Treatment of Depression in Patients with Breast Cancer: A Critical Review

Aims and background

To summarize current knowledge on psychopharmacological and psychotherapeutic options for patients with breast cancer and comorbid depression, starting from the psychiatric viewpoint. Issues on diagnostic boundaries of depression and outcome measures are raised.

Methods

We completed a literature review from the last 30 years (until March 2012) using PubMed by pairing the key words: ‘breast cancer and depression treatment’ (about 1431 works, including 207 reviews), ‘breast cancer and antidepressants’ (about 305 works, including 66 reviews), and in particular ‘selective serotonin reuptake inhibitors and breast cancer’ (38 works, including 10 reviews) and ‘breast cancer and psychotherapy’ (603 works, including 84 reviews). Papers in the English language were selected, including recent reviews.

Results

There is little evidence for the superiority of any one specific intervention with pharmacological options or psychotherapy. The heterogeneity of assessment criteria, the small number of subjects collected in systematic studies, the difficulty in adopting standardized outcome measures, and the limited numbers of available drugs with a favorable side effect profile are the main limitations that emerge from the literature. No conclusive findings are available on mid-term/long-term treatment strategies, or when depression is part of a bipolar disorder.

Conclusions

Further research is necessary to define the most appropriate approach to depression when it occurs in comorbidity with breast cancer. A more accurate definition of the clinical phenotypes of depression in the special population of patients with breast cancer is suggested as a key issue.

The Work and Social Adjustment Scale: Psychometric properties and validity among males and females, and outpatients with and without personality disorders

The Work and Social Adjustment Scale (WSAS) is an outcome measure assessing degree of functional impairment. Its psychometric properties, validity and sensitivity to change have been supported in several studies. However, no explicit psychometric or validity study of WSAS has been performed on data from a large sample of psychiatric outpatients, with and without personality disorders. The aim of this study was therefore to provide additional knowledge of the properties of WSAS in such a sample. The material comprised data from 1371 patients, from 15 different units participating in the Norwegian Network of Personality-Focused Treatment Programs. Psychometric properties of the scale, such as measurement invariance among males and females, longitudinal invariance, as well as associations with other clinical measures and sensitivity to change were analysed. The results confirm that WSAS constitutes a reliable, unidimensional and gender invariant measure, sensitive to change and to severity of mental distress. Although highly associated with levels of depression, WSAS measures a clinically important aspect of impairment. Copyright © 2017 John Wiley & Sons, Ltd.

Effects of Patient Preferences on Outcomes in the Predictors of Remission in Depression to Individual and Combined Treatments (PReDICT) Study

OBJECTIVE

The Predictors of Remission in Depression to Individual and Combined Treatments [PReDICT] study aimed to identify clinical and biological factors predictive of treatment outcomes in major depressive disorder among treatment-naive adults. The authors evaluated the efficacy of cognitive-behavioral therapy (CBT) and two antidepressant medications (escitalopram and duloxetine) in patients with major depression and examined the moderating effect of patients' treatment preferences on outcomes.

METHOD

Adults aged 18-65 with treatment-naive major depression were randomly assigned with equal likelihood to 12 weeks of treatment with escitalopram (10-20 mg/day), duloxetine (30-60 mg/day), or CBT (16 50-minute sessions). Prior to randomization, patients indicated whether they preferred medication or CBT or had no preference. The primary outcome was change in the 17-item Hamilton Depression Rating Scale (HAM-D), administered by raters blinded to treatment.

RESULTS

A total of 344 patients were randomly assigned, with a mean baseline HAM-D score of 19.8 (SD=3.8). The mean estimated overall decreases in HAM-D score did not significantly differ between treatments (CBT: 10.2, escitalopram: 11.1, duloxetine: 11.2). Last observation carried forward remission rates did not significantly differ between treatments (CBT: 41.9%, escitalopram: 46.7%, duloxetine: 54.7%). Patients matched to their preferred treatment were more likely to complete the trial but not more likely to achieve remission.

CONCLUSIONS

Treatment guidelines that recommend either an evidence-based psychotherapy or antidepressant medication for nonpsychotic major depression can be extended to treatment-naive patients. Treatment preferences among patients without prior treatment exposure do not significantly moderate symptomatic outcomes.

Clinical trials with nested subgroups: Analysis, sample size determination and internal pilot studies

The importance of subgroup analyses has been increasing due to a growing interest in personalized medicine and targeted therapies. Considering designs with multiple nested subgroups and a continuous endpoint, we develop methods for the analysis and sample size determination. First, we consider the joint distribution of standardized test statistics that correspond to each (sub)population. We derive multivariate exact distributions where possible, providing approximations otherwise. Based on these results, we present sample size calculation procedures. Uncertainties about nuisance parameters which are needed for sample size calculations make the study prone to misspecifications. We discuss how a sample size review can be performed in order to make the study more robust. To this end, we implement an internal pilot study design where the variances and prevalences of the subgroups are reestimated in a blinded fashion and the sample size is recalculated accordingly. Simulations show that the procedures presented here do not inflate the type I error significantly and maintain the prespecified power as long as the sample size of the smallest subgroup is not too small. We pay special attention to the case of small sample sizes and attain a lower boundary for the size of the internal pilot study.

Handling clinical comorbidity in randomized clinical trials in psychiatry

The purpose of this paper is to a) outline the importance of including patients with clinical comorbidities in Randomized Clinical Trials (RCTs) of psychiatric treatments; and b) to propose a specific approach for best handling, analyzing and interpreting the data on clinical comorbidities in terms of their impact on treatment outcomes. To do this we first define and describe clinical comorbidity and differentiate it from other forms of comorbidity. We then describe the methodological and analytical problems associated with excluding patients with clinically comorbid conditions from RCTs, including the impact on the outcomes of RCTs in psychiatry and the impact on evidence-based clinical decision-making. We then address the challenges inherent to including patients with clinical comorbidities in RCTs. Finally, we propose a methodological and analytic approach to deal with these issues in RCTs which aims to significantly improve the information yielded from RCTs in psychiatry, and thus improve clinical decision-making.

Using Psychoeducation and Role Induction to Improve Completion Rates in Cognitive Behavioural Therapy

BACKGROUND

Pre-treatment role induction interventions have been suggested to potentially enhance attendance and clinical outcomes in psychotherapy.

AIMS

This study aimed to evaluate the effects of a programme of three transdiagnostic seminars (TDS) for patients with common mental disorders accessing cognitive behavioural therapy (CBT) in primary care. TDS included CBT psychoeducation and role induction.

METHOD

A random sample of patients (n = 49) participated in TDS followed by CBT (TDS+CBT) and they were compared with matched controls (n = 49) accessing usual CBT. TDS participants rated the relevance and quality of this intervention using an acceptability questionnaire (AQ). Treatment completion (vs dropout) rates were compared across groups using chi-square tests. Post-treatment changes in depression (PHQ-9) and anxiety (GAD-7) symptoms were compared between groups using analysis of covariance controlling for potential confounders. Analyses were based on intention-to-treat principles.

RESULTS

Mean AQ ratings of the TDS intervention were comparable across diagnostic groups (p = .05). Treatment completion rates were significantly higher (p = .02) in the TDS+CBT group (87.8%) by comparison with usual CBT (68.8%). However, no significant differences in post-treatment symptom changes were found for depression (p = .34) or anxiety measures (p = .71).

CONCLUSIONS

Incorporating a psychoeducational role induction prior to CBT significantly improved treatment retention, but not overall symptom reductions.

Moderators and predictors of response to behavior therapy for tics in Tourette syndrome

OBJECTIVE

To examine moderators and predictors of response to behavior therapy for tics in children and adults with Tourette syndrome and chronic tic disorders.

METHODS

Data from 2 10-week, multisite studies (1 in children and 1 in adults; total n = 248) comparing comprehensive behavioral intervention for tics (CBIT) to psychoeducation and supportive therapy (PST) were combined for moderator analyses. Participants (177 male, 71 female) had a mean age of 21.5 ± 13.9 years (range 9-69). Demographic and clinical characteristics, baseline tic-suppressing medication, and co-occurring psychiatric disorders were tested as potential moderators for CBIT vs PST or predictors of outcome regardless of treatment assignment. Main outcomes measures were the Yale Global Tic Severity Scale Total Tic score and the Clinical Global Impression-Improvement score assessed by masked evaluators.

RESULTS

The presence of tic medication significantly moderated response to CBIT vs PST (p = 0.01). Participants showed tic reduction after CBIT regardless of tic medication status, but only participants receiving tic medication showed reduction of tics after PST. Co-occurring psychiatric disorders, age, sex, family functioning, tic characteristics, and treatment expectancy did not moderate response. Across both treatments, greater tic severity (p = 0.005) and positive participant expectancy (p = 0.01) predicted greater tic improvement. Anxiety disorders (p = 0.042) and premonitory urge severity (p = 0.005) predicted lower tic reduction.

CONCLUSIONS

Presence of co-occurring attention-deficit/hyperactivity disorder, obsessive-compulsive disorder, or anxiety disorders did not moderate response to CBIT. Although participants on tic medication showed improvement after CBIT, the difference between CBIT and PST was greater for participants who were not on tic-suppressing medication.

CLINICALTRIALSGOV IDENTIFIERS

The child and adult CBIT studies are listed on clinical trials.gov (NCT00218777 and NCT00231985, respectively).

CLASSIFICATION OF EVIDENCE

This study provides Class I evidence that CBIT is effective in reducing tic severity across subgroups of patients with chronic tic disorders, although the difference between treatments was smaller for participants on tic-suppressing medications, suggesting reduced efficacy in this subgroup.

Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder

BACKGROUNDS

Clinicians need guidance to address the heterogeneity of treatment responses of patients with major depressive disorder (MDD). While prediction schemes based on symptom clustering and biomarkers have so far not yielded results of sufficient strength to inform clinical decision-making, prediction schemes based on big data predictive analytic models might be more practically useful.

METHOD

We review evidence suggesting that prediction equations based on symptoms and other easily-assessed clinical features found in previous research to predict MDD treatment outcomes might provide a foundation for developing predictive analytic clinical decision support models that could help clinicians select optimal (personalised) MDD treatments. These methods could also be useful in targeting patient subsamples for more expensive biomarker assessments.

RESULTS

Approximately two dozen baseline variables obtained from medical records or patient reports have been found repeatedly in MDD treatment trials to predict overall treatment outcomes (i.e., intervention v. control) or differential treatment outcomes (i.e., intervention A v. intervention B). Similar evidence has been found in observational studies of MDD persistence-severity. However, no treatment studies have yet attempted to develop treatment outcome equations using the full set of these predictors. Promising preliminary empirical results coupled with recent developments in statistical methodology suggest that models could be developed to provide useful clinical decision support in personalised treatment selection. These tools could also provide a strong foundation to increase statistical power in focused studies of biomarkers and MDD heterogeneity of treatment response in subsequent controlled trials.

CONCLUSIONS

Coordinated efforts are needed to develop a protocol for systematically collecting information about established predictors of heterogeneity of MDD treatment response in large observational treatment studies, applying and refining these models in subsequent pragmatic trials, carrying out pooled secondary analyses to extract the maximum amount of information from these coordinated studies, and using this information to focus future discovery efforts in the segment of the patient population in which continued uncertainty about treatment response exists.

Sponsorship bias in the comparative efficacy of psychotherapy and pharmacotherapy for adult depression: meta-analysis

BACKGROUND

Sponsorship bias has never been investigated for non-pharmacological treatments like psychotherapy.

AIMS

We examined industry funding and author financial conflict of interest (COI) in randomised controlled trials directly comparing psychotherapy and pharmacotherapy in depression.

METHOD

We conducted a meta-analysis with subgroup comparisons for industry v. non-industry-funded trials, and respectively for trial reports with author financial COI v. those without.

RESULTS

In total, 45 studies were included. In most analyses, pharmacotherapy consistently showed significant effectiveness over psychotherapy, g = -0.11 (95% CI -0.21 to -0.02) in industry-funded trials. Differences between industry and non-industry-funded trials were significant, a result only partly confirmed in sensitivity analyses. We identified five instances where authors of the original article had not reported financial COI.

CONCLUSIONS

Industry-funded trials for depression appear to subtly favour pharmacotherapy over psychotherapy. Disclosure of all financial ties with the pharmaceutical industry should be encouraged.

The Dutch Measure for quantification of Treatment Resistance in Depression (DM-TRD): an extension of the Maudsley Staging Method

BACKGROUND

Treatment resistant depression (TRD) is common in daily practice. An empirical, widely accepted and applicable measure to quantify TRD is lacking. Previously, the Maudsley Staging Method (MSM) showed good validity. We aimed to improve the MSM by refining and extending its items resulting in the Dutch Measure for quantification of TRD (DM-TRD).

METHODS

In addition to duration, severity and failed treatments in the current depressive episode, we added items for functional impairment, comorbid anxiety, personality disorders and psychosocial stressors. We extended the augmentation section and added items for failed psychotherapy and intensified treatment. We examined psychometric properties of the DM-TRD and tested prediction of future depressive symptoms and remission after 16 weeks in 274 (DSM-IV) depressed in- and outpatients entering naturalistic treatment.

RESULTS

The DM-TRD showed excellent inter-/intra-rater reliability. Higher scores were associated with more symptoms and less remission during follow-up. The DM-TRD outperformed the MSM in prediction of future depressive symptomatology. Remission was predicted equally well by both measures. Longer duration of the current episode, larger functional impairment and larger baseline symptom severity were the strongest predictors of symptomatology at follow-up. Longer duration and larger functional impairment were negatively associated with remission.

LIMITATIONS

Longer follow-up could have increased predictive power. Addition of items for somatic co-morbidity, childhood adversity and psychotic features must be investigated further.

CONCLUSION

The DM-TRD has excellent psychometric properties and better predictive validity for clinical outcome than other sophisticated measure published to date. Its use in clinical practice and research will improve treatment planning in TRD-patients.

An approach to revealing clinically relevant subgroups across the mood spectrum

BACKGROUND

Individuals diagnosed with bipolar 1 disorder (BP1), bipolar 2 disorder (BP2), or major depressive disorder (MDD) experience varying levels of depressive and (hypo)manic symptoms. Clarifying symptom heterogeneity is meaningful, as even subthreshold symptoms may impact quality of life and treatment outcome. The MOODS Lifetime self-report instrument was designed to capture the full range of depressive and (hypo)manic characteristics.

METHODS

This study applied clustering methods to 347 currently depressed adults with MDD, BP2, or BP1 to reveal naturally occurring MOODS subgroups. Subgroups were then compared on baseline clinical and demographic characteristics and as well as depressive and (hypo)manic symptoms over twenty weeks of treatment.

RESULTS

Four subgroups were identified: (1) high depressive and (hypo)manic symptoms (N=77, 22%), (2) moderate depressive and (hypo)manic symptoms (N=115, 33%), (3) low depressive and moderate (hypo)manic symptoms (N=82, 24%), and (4) low depressive and (hypo)manic symptoms (N=73, 21%). Individuals in the low depressive/moderate (hypo)manic subgroup had poorer quality of life and greater depressive symptoms over the course of treatment. Individuals in the high and moderate severity subgroups had greater substance use, longer duration of illness, and greater (hypo)manic symptoms throughout treatment. Treatment outcomes were primarily driven by individuals diagnosed with MDD.

LIMITATIONS

The sample was drawn from three randomized clinical trials. Validation is required for this exploratory study.

CONCLUSIONS

After validation, these subgroups may inform classification and personalized treatment beyond categorical diagnosis.

Changes in depression subtypes for women during treatment with citalopram: a latent transition analysis

The aim of this study was to characterize latent subtypes of major depression and changes in these subtypes among women receiving citalopram in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial. Latent transition analysis was applied to data from 755 women who completed baseline and week 12 study visits in level 1 of STAR*D. Items from the self-report version of the Quick Inventory of Depressive Symptomatology were used as indicators of latent depression subtype. Four subtypes were identified at baseline and week 12. The baseline subtypes were Mild (21 %), Moderate (30 %), Severe with Increased Appetite (16 %), and Severe with Decreased Appetite (34 %). The subtypes at week 12 were Symptom Resolution (65 %), Mild (23 %), Moderate (9 %), and Severe with Psychomotor Disturbances (3 %). Women in the Moderate subtype at baseline had the greatest chance of moving to Symptom Resolution (87 %). Women in the Severe with Decreased Appetite subtype had the lowest chance of transitioning to Symptom Resolution (46 %). Depression severity and appetite distinguished depression subtypes for women before treatment with citalopram. Depression severity and psychomotor disturbances characterized the subtypes after treatment. This work highlights the need to consider how depression treatment changes different symptoms instead of relying exclusively on summary rating scores.

CLINICAL TRIAL REGISTRATION

www.clinicaltrials.gov , NCT00021528.

Reporting of Sex Effects by Systematic Reviews on Interventions for Depression, Diabetes, and Chronic Pain

Systematic reviews (SRs) have the potential to contribute uniquely to the evaluation of sex and gender differences (termed "sex effects"). This article describes the reporting of sex effects by SRs on interventions for depression, type 2 diabetes mellitus, and chronic pain conditions (chronic low back pain, knee osteoarthritis, and fibromyalgia). It includes SRs published since 1 October 2009 that evaluate medications, behavioral interventions, exercise, quality improvement, and some condition-specific treatments. The reporting of sex effects by primary randomized, controlled trials is also examined. Of 313 eligible SRs (86 for depression, 159 for type 2 diabetes mellitus, and 68 for chronic pain), few (n = 29) reported sex effects. Most SRs reporting sex effects used metaregression, whereas 9 SRs used subgroup analysis or individual-patient data meta-analysis. The proportion of SRs reporting the sex distribution of primary studies varied from a low of 31% (n = 8) for low back pain to a high of 68% (n = 23) for fibromyalgia. Primary randomized, controlled trials also infrequently reported sex effects, and most lacked an adequate sample size to examine them. Therefore, all SRs should report the proportion of women enrolled in primary studies and evaluate sex effects using appropriate methods whenever power is adequate.

Establishing moderators and biosignatures of antidepressant response in clinical care (EMBARC): Rationale and design

Remission rates for Major Depressive Disorder (MDD) are low and unpredictable for any given antidepressant. No biological or clinical marker has demonstrated sufficient ability to match individuals to efficacious treatment. Biosignatures developed from the systematic exploration of multiple biological markers, which optimize treatment selection for individuals (moderators) and provide early indication of ultimate treatment response (mediators) are needed. The rationale and design of a multi-site, placebo-controlled randomized clinical trial of sertraline examining moderators and mediators of treatment response is described. The target sample is 300 participants with early onset (≤30 years) recurrent MDD. Non-responders to an 8-week trial are switched double blind to either bupropion (for sertraline non-responders) or sertraline (for placebo non-responders) for an additional 8 weeks. Clinical moderators include anxious depression, early trauma, gender, melancholic and atypical depression, anger attacks, Axis II disorder, hypersomnia/fatigue, and chronicity of depression. Biological moderator and mediators include cerebral cortical thickness, task-based fMRI (reward and emotion conflict), resting connectivity, diffusion tensor imaging (DTI), arterial spin labeling (ASL), electroencephalograpy (EEG), cortical evoked potentials, and behavioral/cognitive tasks evaluated at baseline and week 1, except DTI, assessed only at baseline. The study is designed to standardize assessment of biomarkers across multiple sites as well as institute replicable quality control methods, and to use advanced data analytic methods to integrate these markers. A Differential Depression Treatment Response Index (DTRI) will be developed. The data, including biological samples (DNA, RNA, and plasma collected before and during treatment), will become available in a public scientific repository.

CLINICAL TRIAL REGISTRATION

Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC). Identifier: NCT01407094. URL: http://clinicaltrials.gov/show/NCT01407094.

Cognitive-Behavioural Analysis System of Psychotherapy (CBASP), a drug, or their combination: differential therapeutics for persistent depressive disorder: a study protocol of an individual participant data network meta-analysis

INTRODUCTION

Despite important advances in psychological and pharmacological treatments of persistent depressive disorders in the past decades, their responses remain typically slow and poor, and differential responses among different modalities of treatments or their combinations are not well understood. Cognitive-Behavioural Analysis System of Psychotherapy (CBASP) is the only psychotherapy that has been specifically designed for chronic depression and has been examined in an increasing number of trials against medications, alone or in combination. When several treatment alternatives are available for a certain condition, network meta-analysis (NMA) provides a powerful tool to examine their relative efficacy by combining all direct and indirect comparisons. Individual participant data (IPD) meta-analysis enables exploration of impacts of individual characteristics that lead to a differentiated approach matching treatments to specific subgroups of patients.

METHODS AND ANALYSIS

We will search for all randomised controlled trials that compared CBASP, pharmacotherapy or their combination, in the treatment of patients with persistent depressive disorder, in Cochrane CENTRAL, PUBMED, SCOPUS and PsycINFO, supplemented by personal contacts. Individual participant data will be sought from the principal investigators of all the identified trials. Our primary outcomes are depression severity as measured on a continuous observer-rated scale for depression, and dropouts for any reason as a proxy measure of overall treatment acceptability. We will conduct a one-step IPD-NMA to compare CBASP, medications and their combinations, and also carry out a meta-regression to identify their prognostic factors and effect moderators. The model will be fitted in OpenBUGS, using vague priors for all location parameters. For the heterogeneity we will use a half-normal prior on the SD.

ETHICS AND DISSEMINATION

This study requires no ethical approval. We will publish the findings in a peer-reviewed journal. The study results will contribute to more finely differentiated therapeutics for patients suffering from this chronically disabling disorder.

TRIAL REGISTRATION NUMBER

CRD42016035886.

Treatment-refractory anxiety; definition, risk factors, and treatment challenges

A sizable proportion of psychiatric patients will seek clinical evaluation and treatment for anxiety symptoms reportedly refractory to treatment. This apparent lack of response is either due to “pseudo-resistance” (a failure to have received and adhered to a recognized and effective treatment or treatments for their condition) or to true “treatment resistance.” Pseudo-resistance can be due to clinician errors in selecting and delivering an appropriate treatment effectively, or to patient nonadherence to a course of treatment. True treatment resistance can be due to unrecognized exogenous anxiogenic factors (eg, caffeine overuse, sleep deprivation, use of alcohol or marijuana) or an incorrect diagnosis (eg, atypical bipolar illness, occult substance abuse, attention deficit-hyperactivity disorder). Once the above factors are eliminated, treatment should focus on combining effective medications and cognitive behavioral therapy, combining several medications (augmentation), or employing novel medications or psychotherapies not typically indicated as first-line evidence-based anxiety treatments.

Changes in Depression Subtypes Among Men in STAR*D: A Latent Transition Analysis

The burden of depression in men is high. Current diagnostic criteria may not fully capture men's experience with depression. Descriptions of the heterogeneity in depression among men are lacking. The purpose of the study was to characterize latent subtypes of major depression and changes in these subtypes among men receiving citalopram in Level 1 of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial. Latent transition analysis was applied to data from 387 men who completed baseline and Week 12 study visits in Level 1 of STAR*D. Items from the self-report version of the Quick Inventory of Depressive Symptomatology were used as indicators of latent depression subtypes. Four statuses were identified at baseline and Week 12. Baseline statuses were Mild (10% of men), Moderate (53%), Severe with Psychomotor Slowing (20%), and Severe with Psychomotor Agitation (17%). At Week 12, the statuses were Symptom Resolution (41%), Mild (36%), Moderate (18%), and Severe with Psychomotor Slowing (5%). Men in the Mild status were most likely to transition to Symptom Resolution (probability = 69%). Men in the Severe with Agitation status were least likely to transition to Symptom Resolution (probability = 0%). This work highlights the need to not focus solely on summary rating scores but to also consider patterns of symptoms when treating depression.

Does Publication Bias Inflate the Apparent Efficacy of Psychological Treatment for Major Depressive Disorder? A Systematic Review and Meta-Analysis of US National Institutes of Health-Funded Trials

BACKGROUND

The efficacy of antidepressant medication has been shown empirically to be overestimated due to publication bias, but this has only been inferred statistically with regard to psychological treatment for depression. We assessed directly the extent of study publication bias in trials examining the efficacy of psychological treatment for depression.

METHODS AND FINDINGS

We identified US National Institutes of Health grants awarded to fund randomized clinical trials comparing psychological treatment to control conditions or other treatments in patients diagnosed with major depressive disorder for the period 1972-2008, and we determined whether those grants led to publications. For studies that were not published, data were requested from investigators and included in the meta-analyses. Thirteen (23.6%) of the 55 funded grants that began trials did not result in publications, and two others never started. Among comparisons to control conditions, adding unpublished studies (Hedges' g = 0.20; CI95% -0.11~0.51; k = 6) to published studies (g = 0.52; 0.37~0.68; k = 20) reduced the psychotherapy effect size point estimate (g = 0.39; 0.08~0.70) by 25%. Moreover, these findings may overestimate the "true" effect of psychological treatment for depression as outcome reporting bias could not be examined quantitatively.

CONCLUSION

The efficacy of psychological interventions for depression has been overestimated in the published literature, just as it has been for pharmacotherapy. Both are efficacious but not to the extent that the published literature would suggest. Funding agencies and journals should archive both original protocols and raw data from treatment trials to allow the detection and correction of outcome reporting bias. Clinicians, guidelines developers, and decision makers should be aware that the published literature overestimates the effects of the predominant treatments for depression.

Predictors of response to CBT and IPT for depression; the contribution of therapy process

Little is known about the factors that contribute to a positive psychotherapy outcome. There is still considerable debate as to whether specific factors (e.g. severity of symptoms, comorbidity) or nonspecific factors (e.g. alliance, therapy process) are most important in influencing outcome. This study examined the additional contribution that therapeutic process and alliance made to previously identified specific predictors of response to CBT and IPT for depression over the course of therapy. The previously identified specific factors were belief that childhood reasons caused the depression, recurrent depression, perceptions about how logical therapy was and comorbid personality disorder symptoms. One hundred and sixty five adult outpatients with major depression were treated for depression in a randomised clinical trial examining predictors of response to Cognitive Behavior Therapy and Interpersonal Psychotherapy. All therapy sessions were audiorecorded to enable objective ratings of therapeutic process and alliance. Process factors - patient psychic distress, patient participation and patient alliance had the strongest associations with outcome. The early and middle stage of therapy process did not account for any additional variance other than that previously identified by the patient predictors, however, at the end stage of therapy process contributed a further 14%.