Cost-effectiveness of genetic and clinical predictors for choosing combined psychotherapy and pharmacotherapy in major depression

Neuroregulatory Effects of Microcone Patch Stimulation on the Auricular Branch of the Vagus Nerve and the Prefrontal Cortex: A Feasibility Study

Background: The primary purpose of this study was to preliminarily examine the effects of autonomic nervous system activity on the dorsolateral prefrontal cortex. Recent studies have examined approaches to modulating autonomic activity using invasive and non-invasive methods, but the effects of changes in autonomic activity during cognitive tasks on the dorsolateral prefrontal cortex have not been fully investigated. The purpose of this preliminary investigation was to examine changes in autonomic activity and blood oxygen saturation in the dorsolateral prefrontal cortex during reading tasks induced by vagus nerve stimulation using a microcone patch. Methods: A cohort of 40 typically developing adults was enrolled in this study. We carefully examined changes in autonomic nervous system activity and blood oxygen saturation in the dorsolateral prefrontal cortex during a reading task in two conditions: with and without microcone patch stimulation. Results: Significant changes in brain activation in the dorsolateral prefrontal cortext due to microcone patch stimulation were confirmed. In addition, hierarchical multiple regression analysis revealed specific changes in reading task-related blood oxygen saturation in the dorsolateral prefrontal region during microcone patch stimulation. Conclusions: It should be recognized that this study is a preliminary investigation and does not have immediate clinical applications. However, our results suggest that changes in autonomic nervous system activity induced by external vagal stimulation may affect activity in specific reading-related regions of the dorsolateral prefrontal cortex. Further research and evaluation are needed to fully understand the implications and potential applications of these findings.

Routine treatment pathways in a cohort of patients with major depression and suicidality in Italy: the ARIANNA observational study

BACKGROUND

Major Depressive Disorder (MDD) with suicidal ideation, intent, or behavior is a psychiatric emergency with controversial care management. Our study describes the comprehensive treatment pathways of this population in Italian routine clinical practice.

METHODS

ARIANNA [NCT04463108] is an observational prospective and retrospective cohort study involving both primary data collection and secondary data extract. A total of 137 adult MDD patients with suicidality were enrolled from 24 Italian care sites and followed for 90 days. Other than the description of treatment patterns, the impact of treatment on depressive symptoms and suicidality, the burden on the patient's and caregiver's quality of life, healthcare resource utilization and costs were described.

RESULTS

Of the 133 eligible patients, 68.4% were female, and the median age was 47. Approximately half of the study population had a current severe major depressive episode. Treatment strategies at the time of active suicidal ideation with intent definition/confirmation (t0) were heterogeneous, increasing in complexity during observation. According to the MADRS, patients with remission at t0+1 day were 2.6%, with the mean total score decreasing from 37.2 at t0 to 32.3.

LIMITATIONS

The study sites were not randomly selected.

CONCLUSIONS

To the best of our knowledge, this is the first cohort study that prospectively describes the characteristics of patients with MDD and suicide risk in Italy, and how they are treated in clinical practice. The study confirms this is a difficult-to-treat population. In addition, a lack of rapid, effective treatment for reducing depressive symptoms and suicidality is observed.

Cost-effectiveness of Arg16Gly in ADRB2 pharmacogenomic-guided treatment for pediatric asthma

OBJECTIVES

To assess the cost-effectiveness of Arg16Gly ADRB2 pharmacogenomic testing compared with no Arg16Gly ADRB2 testing to guide the use of long-acting β2 receptor agonist (LABA) in asthma patients aged 1 to 5 years in China.

METHODS

This economic evaluation developed a Markov model with four health states (no exacerbation, mild exacerbation, moderate-to-severe exacerbation, and death). Transition probabilities were estimated from the rate of exacerbations, the case-fatality rate of patients hospitalized for exacerbations, and natural mortality. Costs included drug costs and exacerbation management costs. Cost inputs and utilities for each health state were gained from public databases and the literatures. Costs and quality-adjusted life years (QALYs) were estimated for ten years. Deterministic and probabilistic sensitivity analyses were performed.

RESULTS

In the base case analysis, in contrast to the group without the genotype test, the incremental total cost was -¥334.7, and the incremental QALY was 0.001 in the Arg16Gly ADRB2 genotyping group. Therefore, the Arg16Gly ADRB2 test group was the dominant strategy for children with asthma in China. The sensitivity analyses showed that the model was relatively stable.

CONCLUSION

Arg16Gly ADRB2 testing before using LABA is a cost-effective approach compared with no gene testing for pediatric asthma.

A Promising Approach to Optimizing Sequential Treatment Decisions for Depression: Markov Decision Process

The most appropriate next step in depression treatment after the initial treatment fails is unclear. This study explores the suitability of the Markov decision process for optimizing sequential treatment decisions for depression. We conducted a formal comparison of a Markov decision process approach and mainstream state-transition models as used in health economic decision analysis to clarify differences in the model structure. We performed two reviews: the first to identify existing applications of the Markov decision process in the field of healthcare and the second to identify existing health economic models for depression. We then illustrated the application of a Markov decision process by reformulating an existing health economic model. This provided input for discussing the suitability of a Markov decision process for solving sequential treatment decisions in depression. The Markov decision process and state-transition models differed in terms of flexibility in modeling actions and rewards. In all, 23 applications of a Markov decision process within the context of somatic disease were included, 16 of which concerned sequential treatment decisions. Most existing health economic models relating to depression have a state-transition structure. The example application replicated the health economic model and enabled additional capacity to make dynamic comparisons of more interventions over time than was possible with traditional state-transition models. Markov decision processes have been successfully applied to address sequential treatment-decision problems, although the results have been published mostly in economics journals that are not related to healthcare. One advantage of a Markov decision process compared with state-transition models is that it allows extended action space: the possibility of making dynamic comparisons of different treatments over time. Within the context of depression, although existing state-transition models are too basic to evaluate sequential treatment decisions, the assumptions of a Markov decision process could be satisfied. The Markov decision process could therefore serve as a powerful model for optimizing sequential treatment in depression. This would require a sufficiently elaborate state-transition model at the cohort or patient level.

Obsessive-compulsive symptoms in major depressive disorder correlate with clinical severity and mixed features

Obsessive-compulsive symptoms (OCS) are often reported in patients with bipolar disorder. The aim of this study was to investigate OCS and their related clinical features in major depressive disorder (MDD). The analysis involved 482 outpatients with MDD collected within the Combining Medications to Enhance Depression outcomes trial, who were assessed with scales for depression, suicidality, irritability, hypomanic symptomatology, and other comorbid psychiatric manifestations. OCS were reported in 27% of the sample. Patients with MDD experiencing OCS were found to differ from those not experiencing OCS by a greater severity of depression (d = 0.41, P = 0.0001), more hypomanic symptoms (d = 0.48, P < 0.0001) and mixed features (22% vs. 10%, P = 0.001), increased levels of suicidal thoughts (d = 0.40, P = 0.0001), a lower likelihood of achieving remission after antidepressant treatment (19% vs. 33%, P = 0.0109), as well as more comorbid anxiety disorders (i.e. panic disorder: d = 0.98, P < 0.0001; generalized anxiety disorder: d = 0.74, P < 0.0001; social phobia: d = 0.71, P < 0.0001), and post-traumatic stress disorder (d = 0.81, P < 0.0001). In light of these findings, clinicians should pay more attention to the occurrence of OCS in MDD, as these symptoms may reflect greater clinical severity, poorer treatment outcome, and increased risk for bipolarity.

Precision medicine in mood disorders

The choice of the most appropriate psychoactive medication for each of our patients is always a challenge. We can use more than 100 psychoactive drugs in the treatment of mood disorders, which can be prescribed either alone or in combination. Response and tolerability problems are common, and much trial and error is often needed before achieving a satisfactory outcome. Precision medicine is therefore needed for tailoring treatment to optimize outcome. Pharmacological, clinical, and demographic factors are important and informative, but biological factors may further inform and refine prediction. Twenty years after the first reports of gene variants modulating antidepressant response, we are now confronted with the prospect of routine clinical pharmacogenetic applications in the treatment of depression. The scientific community is divided into two camps: those who are enthusiastic and those who are skeptical. Although it appears clear that the benefit of existing tools is still not completely defined, at least in the case of central nervous system gene variants, this is not the case for metabolic gene variants, which is generally accepted. Cumulative scores encompassing many variants across the entire genome will soon predict psychiatric disorder liability and outcome. At present, precision medicine in mood disorders may be implemented using clinical and pharmacokinetic factors. In the near future, a genome-wide composite genetic score in conjunction with clinical factors within each patient is the most promising approach for developing a more effective way to target treatment for patients suffering from mood disorders.

Economic Impact of the Application of a Precision Medicine Model (5SPM) on Psychotic Patients

Background

Schizophrenia is a severe mental disorder that often manifests within the first three decades of life. Its prognosis is uncertain and may result in a prolonged treatment that could extend throughout the entire lifespan of the patient. Antipsychotic drugs are characterized by a high interindividual variability when considering therapeutic effect and emergence of adverse effects. Such interindividual variability is thought to be associated primarily with pharmacokinetic matters.

Objective

The objective of this study was to evaluate the economic impact of the application of the 5-Step Precision Medicine model (5SPM), an approach based on the pharmacogenetic analysis of the primary genes involved in the metabolism of the therapy for each patient, restructuring treatment as necessary.

Patients and Methods

One hundred eighty-eight psychiatry patients were analysed for single nucleotide polymorphisms on genes CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A5 and ABCB1. Information on patients' diagnosis, pharmacotherapy, and hospitalizations was collected.

Results

We achieved a cost-benefit ratio of 3.31-3.59 with a reduction of direct cost (hospitalizations plus pharmacotherapy) with a reduction of total cost in 67% of the patients who underwent the clinical intervention.

Conclusion

A rational Precision Medicine-based approach to psychiatric patients could result in a reduction on number of drugs required to control exacerbations, and the underlying pathologies, reducing the risk of adverse effects and improving adherence to treatment, leading to a potential decrease in direct costs. This methodology has been shown to be cost-dominant and, being based on a pharmacogenetic analysis, it has a lifelong nature, as the data obtained can be applied to other medical disciplines.

Symptom Cluster-Matching Antidepressant Treatment: A Case Series Pilot Study

Despite treating depression with antidepressants, their effectiveness is often insufficient. Comparative effectiveness studies and meta-analyses show the effectiveness of antidepressants; however, they do not provide clear indications as to the choice of a specific antidepressant. The rational choice of antidepressants may be based on matching their mechanisms of action to the symptomatic profiles of depression, reflecting the heterogeneity of symptoms in different patients. The authors presented a series of cases of patients diagnosed with depression in whom at least one previous antidepressant treatment was shown to be ineffective before drug targeted symptom cluster-matching treatment (SCMT). The presented pilot study shows for the first time the effectiveness of SCMT in the different clusters of depressive symptoms. All the described patients obtained recovery from depressive symptoms after introducing drug-targeted SCMT. Once validated in clinical trials, SCMT might become an effective and rational method of selecting an antidepressant according to the individual profile of depressive symptoms, the mechanism of their formation, and the mechanism of drug action. Although the study results are preliminary, SCMT can be a way to personalize treatment, increasing the likelihood of improvement even in patients who meet criteria for treatment-resistant depression.