Handling clinical comorbidity in randomized clinical trials in psychiatry

Predicting treatment response using machine learning: A registered report

OBJECTIVE

Previous research on psychotherapy treatment response has mainly focused on outpatients or clinical trial data which may have low ecological validity regarding naturalistic inpatient samples. To reduce treatment failures by proactively screening for patients at risk of low treatment response, gain more knowledge about risk factors and to evaluate treatments, accurate insights about predictors of treatment response in naturalistic inpatient samples are needed.

METHODS

We compared the performance of different machine learning algorithms in predicting treatment response, operationalized as a substantial reduction in symptom severity as expressed in the Patient Health Questionnaire Anxiety and Depression Scale. To achieve this goal, we used different sets of variables-(a) demographics, (b) physical indicators, (c) psychological indicators and (d) treatment-related variables-in a naturalistic inpatient sample (N = 723) to specify their joint and unique contribution to treatment success.

RESULTS

There was a strong link between symptom severity at baseline and post-treatment (R2 = .32). When using all available variables, both machine learning algorithms outperformed the linear regressions and led to an increment in predictive performance of R2 = .12. Treatment-related variables were the most predictive, followed psychological indicators. Physical indicators and demographics were negligible.

CONCLUSIONS

Treatment response in naturalistic inpatient settings can be predicted to a considerable degree by using baseline indicators. Regularization via machine learning algorithms leads to higher predictive performances as opposed to including nonlinear and interaction effects. Heterogenous aspects of mental health have incremental predictive value and should be considered as prognostic markers when modelling treatment processes.

The bifocal model: A two-level clinical model of psychiatric disorders integrating diagnostic and transdiagnostic approaches

Nowadays, two distinct conceptualizations are available to classify, label and guide the treatment of psychiatric disorders: the diagnostic approach and the transdiagnostic approach. There are pros and cons to both approaches. We propose here to link these two conceptualizations by creating a two-level clinical model that takes advantages of both approaches, named the bifocal model (BFM). This two-tier clinical model consists of a double level of analysis: the first step is to identify transdiagnostic mechanisms involved in multiple disorders and then to recognize specific mechanisms identified in a given disorder or cluster of symptoms. Such a process would bring the diagnostic and transdiagnostic approaches together and offer a more flexible way to understand mental disorders and ultimately to improve medical outcomes.

Expanded access to investigational drugs in psychiatry: A systematic review

Some psychiatric patients have exhausted all approved treatment options. Numerous investigational drugs are currently being developed and tested in clinical trials. However, not all patients can participate in clinical trials. Expanded access programs may provide an opportunity for patients who cannot participate in clinical trials to use investigational drugs as a therapeutic option outside of clinical trials. It is unknown to what extent expanded access occurs in psychiatry. We conducted a systematic literature search on PubMed, Embase, and PscyInfo, with additional information from ClinicalTrials.gov, the WHO International Clinical Trials Registry Platform and FDA/EMA approvals, in order to find all expanded access programs ever conducted, globally, in the field of psychiatry. This resulted in a total of fourteen expanded access programs ever conducted in psychiatry. Given the prevalence of psychiatric disorders, the activity in clinical research in psychiatry, the regulatory framework enabling expanded access, and the impact of psychiatric disorders on patients, their families, and society, we had expected a higher utilization of expanded access. We propose that the psychiatric community, with pharmaceutical industry, should consider establishing and optimizing expanded access programs.

Development of the Transdiagnostic Skills Scale (T2S)

INTRODUCTION

Psychotherapy has proved its efficacy for treating a wide range of psychological disorders. Most types of psychotherapy have been developed to treat specific disorders and validated through controlled-randomized trials. In recent years, researchers have developed a new way to conceptualize patients' difficulties, focusing on processes instead of diagnoses. However, there is no simple scale that evaluates transdiagnostic processes, and the development of such a tool is thus the aim of this study.

METHOD

We identified 12 processes that can be targeted in cognitive behavior therapy and created the Transdiagnostic Skills Scale (T2S) to evaluate them. We measured its internal consistency, factor structure and convergent validity in clinical and non-clinical samples.

RESULTS

We found a 6-factor structure composed of emotion regulation, behavioral activation/planning, emotional identification, assertiveness, problem solving and emotional confrontation. The T2S has high internal consistency (Cronbach's alpha = 0.95). We found negative associations between skills and symptoms of anxiety, depression and eating disorders. We found no association between these processes and symptoms of either alcohol or cannabis use disorder.

CONCLUSIONS

The T2S is a useful and valid tool to identify the skills that clinicians should work on with their patients. It offers a complementary way to understand patients' difficulties when categorical assessment is complicated.

Problem-solving training for Veterans in home based primary care: an evaluation of intervention effectiveness

BACKGROUND

Veterans enrolled in Veterans Health Administration (VHA) Home Based Primary Care (HBPC), a program providing in-home medical and mental health care by an interdisciplinary care team, often face substantial physical, cognitive, and mental health challenges. This program evaluation examined the impact of a brief problem-solving intervention on depressive symptoms, quality of life, and problem-solving abilities for Veterans enrolled in HBPC.

DESIGN

Pre- and post-intervention outcomes for Veterans, and qualitative feedback from Veterans and clinicians regarding program satisfaction.

PARTICIPANTS AND SETTING

A total of 230 HBPC patients (mean age in years = 72.1, SD = 11.6) within the U.S. national VHA health care system.

INTERVENTION

Six-session, individual Problem-Solving Training (PST-HBPC).

METHOD

Licensed psychologists and social workers (n = 115) completed training and administered the treatment with HBPC Veterans between 2014 and 2017.

MEASUREMENTS AND RESULTS

From baseline to post-intervention, Veterans completing five or more PST-HBPC sessions (n = 199) reported significant reductions in depressive symptoms on the Patient Health Questionnaire 9-item (PHQ-9), in difficulty functioning due to depressive symptoms (PHQ-9 item 10), and in thoughts of death (PHQ-9 item 9). They also reported more effective problem-solving on the Social Problem-Solving Inventory - Revised: Short form (total score and subscales), and improved quality of life across life domains on the World Health Organization Quality of Life-BREF (WHOQOL-BREF) scale. Both clinicians and Veterans also reported satisfaction with the program.

CONCLUSIONS

Preliminary findings support the continued dissemination and implementation of this brief PST intervention for HBPC Veterans, and its potential for use with non-VA home care populations with complex comorbidities.

The Infinity Formulation: how transdiagnostic behaviours and endeavours for behavioural change serve to maintain co-morbid mental health presentations

Treatment recommendations for mental health are often founded on diagnosis-specific models; however, there are high rates of co-morbidity of mental health presentations and growing recognition of the presence of ‘transdiagnostic processes’ (cognitive, emotional or behavioural features) seen across a range of mental health presentations. This model proposes a novel conceptualisation of how transdiagnostic behaviours may maintain co-morbid mental health presentations by acting as a trigger event for the cognitive biases specific to each presentation. Drawing on existing evidence, psychological theory and the author’s clinical experience, the model organises complex presentations in a theory-driven yet accessible manner for use in clinical practice. The model offers both theoretical and clinical implications for the treatment of mental health presentations using cognitive behavioural approaches, positing that transdiagnostic behaviours be the primary treatment target in co-morbid presentations.

Key learning aims

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Molecular and Cellular Evidence for Age by Disease Interactions: Updates and Path Forward

Characterization of age-associated gene expression changes shows that the brain engages a specific set of genes and biologic pathways along a continuous life-long trajectory and that these genes and pathways overlap with those associated with brain-related disorders. Based on this correlative observation, we have suggested a model of age-by-disease interaction by which brain ageing promotes biologic changes associated with diseases and where deviations from expected age-related trajectories, due to biologic and environmental factors, contribute to defining disease risk or resiliency. In this review, we first evaluate various biomarkers that can be used to study age-by-disease interactions and then focus on transcriptome analysis (i.e., the set of all expressed genes) as a useful tool to explore this interaction. Using the specific example of brain-derived neurotrophic factor and brain-derived neurotrophic factor-associated genes, we then describe molecular events and mechanisms potentially contributing to age-by-disease interactions. Finally, we suggest that long-term biologic adaptations within distinct cellular components of cortical microcircuits, as determined by transcriptome analysis, may integrate and mediate the effects of ageing and diseases. Moving forward, we suggest that analysis of transcriptome similarities between ageing and small molecule-induced system perturbations may lead to novel therapeutics discovery.

Study protocol: A multisite trial of Work-Related Cognitive behavioral therapy for unemployed persons with social anxiety

This paper provides a methodological description of a multi-site, randomized controlled trial (RCT) of a cognitive-behavioral intervention for enhancing employment success among unemployed persons whose employment efforts have been undermined by social anxiety disorder (SAD). SAD is a common and impairing condition, with negative impacts on occupational functioning. In response to these documented employment-related impairments, in a previous project, we produced and tested an eight-session work-related group cognitive-behavioral therapy provided alongside vocational services as usual (WCBT + VSAU). WCBT is delivered by vocational service professionals and is designed in a context and style that overcomes accessibility and stigma-related obstacles with special focus on employment-related targets. Our previous project found that WCBT + VSAU significantly improved social anxiety, depression, and a range of employment-related outcomes compared to a control group of socially anxious job-seekers who received vocational services as usual without WCBT (VSAU-alone). Participants in this study were all homeless, primarily African American job-seekers with high levels of psychiatric comorbidity and limited education and employment histories. The present, two-region study addresses whether WCBT + VSAU enhances job placement, job retention and mental health outcomes in a larger sample assessed over an extended follow-up period. In addition, this trial evaluates whether the effects of WCBT + VSAU generalize to a new population of urban-based, racially diverse job-seekers with vocational and educational histories that differ from our original sample. This study also investigates the system-effects of WCBT + VSAU in a new site that will be informative for broad implementation of WCBT + VSAU. Finally, this project involves a refined, technology-assisted form of WCBT + VSAU designed to be delivered more easily by vocational services professionals.

Multimorbidity is associated with anxiety in older adults in the Health and Retirement Study

OBJECTIVES

The present study determined whether the number of medical conditions was associated with increased occurrence of anxiety and whether triads of medical conditions were associated with anxiety in a nationally representative sample of older Americans. We determined whether multimorbidity findings were unique to anxiety as compared with depressive symptoms.

METHODS

A sample of 4219 participants (65 years or older) completed anxiety and depression measures in the Health and Retirement Study 2006 wave. The logistic regression models' outcome was elevated anxiety (≥12 on five-item Beck Anxiety Inventory) or depressive symptoms (≥12 on eight-item Center for Epidemiological Studies Depression Scale). The predictor variable was a tally of seven self-report of doctor-diagnosed conditions: arthritis, cancer, diabetes, heart conditions, high blood pressure, lung disease, and stroke. Analyses were adjusted for age, gender, and depressive or anxiety symptoms. Associations among elevated anxiety or depressive symptoms and 35 triads of medical conditions were examined using Bonferroni corrected chi-square analyses.

RESULTS

Three or more medical conditions conferred a 2.30-fold increase in elevated anxiety (95% confidence interval: 1.44-4.01). Twenty triads were associated with elevated anxiety as compared with 13 associated with depressive symptoms. Six of seven medical conditions, with the exception being stroke, were present in the majority of triads.

CONCLUSION

Number of medical conditions and specific conditions are associated with increased occurrence of elevated anxiety. Compared with elevated depressive symptoms, anxiety is associated with greater multimorbidity. As anxiety and depression cause significant morbidity, it may be beneficial to consider these mental health symptoms when evaluating older adults with multimorbidity. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.