The strategy of combining antidepressants in the treatment of major depression: clinical experience in spanish outpatients

Epidemiology of treatment resistant depression among major depressive disorder patients in Israel

INTRODUCTION

Major depressive disorder (MDD) is one of the most common mental disorders worldwide, estimated to affect 10-15% of the population per year. Treatment resistant depression (TRD) is estimated to affect a third of these patients who show difficulties in social and occupational function, decline of physical health, suicidal thoughts and increased health care utilization. We describe the prevalence of MDD, TRD and associated healthcare resource utilization in Maccabi Healthcare Services (MHS), a 2.5 million-member state-mandated health service in Israel.

METHODS

All MHS members with an MDD diagnosis were identified within the years 2017-2018 and prevalence assessed by age, sex and TRD. To assess the incidence of MDD, members aged 18-65 years at the start of any MDD episode were identified between 1^st January 2016 and 31^st May 2018 with at least one systemic first-line antidepressant treatment within three months before or after the initial episode. Treatment patterns, time on first-line treatment, and healthcare resource utilization were compared by TRD.

RESULTS

A total of 4960 eligible MDD patients were identified (median age = 51 years, 65% female), representing a period prevalence of 0.218%, and of those, a high proportion of patients received drug treatment (92%). Among incident MDD cases (n = 2553), 24.4% had TRD. Factors associated with TRD included increasing age and personality disorder. Median time on treatment was 3.7 months (longer for those without TRD than those with) and 81.9% of patients purchased more than one month's supply of therapy. In the year after index, patients with TRD had a significant increased number of visits to primary care physicians, psychiatrists, emergency room visits, general hospitalizations, and psychiatric hospitalizations.

CONCLUSION

Our study shows that prevalence of MDD in Israel is low compared to other countries, however once diagnosed, patients' are likely to receive drug treatment. Among patients diagnosed with MDD, the proportion of TRD is similar to other countries, increases with age and is associated with increased healthcare utilization, therefore should be a focus of continued research for finding effective long term treatment options.

Investigation of the Serotonergic Activity and the Serotonin Content in Serum and Platelet, and the Possible Role of the Serotonin Transporter in Patients with Depression

According to the monoamine hypothesis, the development of depression is associated with dysfunctions of the serotonergic system. Alterations in the serotonin transporter gene (5-HTTLPR), the serotonergic activity in the brain, and the content of serotonin (5-HT) have been related to depression and were examined separately by previous studies. This study investigates these parameters in 89 depressed patients and 89 healthy participants. We investigated the serotonergic activity measured by the loudness dependence of auditory evoked potentials (LDAEP). In addition to the examination of the serotonin content (serum and platelet), enzyme-linked immunosorbent assays (ELISA) were used and 5-HTTLPR genotypes were analyzed. We observed a lower serotonin content in patients compared to healthy participants. Further, we noticed a correlation between anxiety and depression-associated symptoms with serotonergic activity. Patients treated with SSRI/SNRI showed decreased contents of serum serotonin compared to patients without any psychotropic medication or other psychotropic medications. Since the serotonergic activity, peripheral serotonin content, and 5-HTTLPR were unrelated, the results suggest independent alterations of central and peripheral serotonergic systems in depression. In line with this finding, serotonergic activity was related to anxiety and depression symptoms. Furthermore, the applied medication seems to influence serum serotonin content in patients with depression.

Multi-omics driven predictions of response to acute phase combination antidepressant therapy: a machine learning approach with cross-trial replication

Combination antidepressant pharmacotherapies are frequently used to treat major depressive disorder (MDD). However, there is no evidence that machine learning approaches combining multi-omics measures (e.g., genomics and plasma metabolomics) can achieve clinically meaningful predictions of outcomes to combination pharmacotherapy. This study examined data from 264 MDD outpatients treated with citalopram or escitalopram in the Mayo Clinic Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) and 111 MDD outpatients treated with combination pharmacotherapies in the Combined Medications to Enhance Outcomes of Antidepressant Therapy (CO-MED) study to predict response to combination antidepressant therapies. To assess whether metabolomics with functionally validated single-nucleotide polymorphisms (SNPs) improves predictability over metabolomics alone, models were trained/tested with and without SNPs. Models trained with PGRN-AMPS' and CO-MED's escitalopram/citalopram patients predicted response in CO-MED's combination pharmacotherapy patients with accuracies of 76.6% (p < 0.01; AUC: 0.85) without and 77.5% (p < 0.01; AUC: 0.86) with SNPs. Then, models trained solely with PGRN-AMPS' escitalopram/citalopram patients predicted response in CO-MED's combination pharmacotherapy patients with accuracies of 75.3% (p < 0.05; AUC: 0.84) without and 77.5% (p < 0.01; AUC: 0.86) with SNPs, demonstrating cross-trial replication of predictions. Plasma hydroxylated sphingomyelins were prominent predictors of treatment outcomes. To explore the relationship between SNPs and hydroxylated sphingomyelins, we conducted multi-omics integration network analysis. Sphingomyelins clustered with SNPs and metabolites related to monoamine neurotransmission, suggesting a potential functional relationship. These results suggest that integrating specific metabolites and SNPs achieves accurate predictions of treatment response across classes of antidepressants. Finally, these results motivate functional investigation into how sphingomyelins might influence MDD pathophysiology, antidepressant response, or both.

Trazodone Addition to Paroxetine and Mirtazapine in a Patient with Treatment-Resistant Depression: The Pros and Cons of Combining Three Antidepressants

Dual antidepressant combination for treatment-resistant depression is a strategy well supported by literature and accepted in clinical practice. Rather, the usefulness of the combination of more than two antidepressants is controversial. This may be related to the possibility of higher side-effect burden and to doubts about its pharmacological effectiveness and therapeutic advantage compared to other standard treatment options. We report a relapse of moderate-to-severe depressive symptoms with insomnia that successfully remitted after the addition of trazodone to a dual combination of paroxetine and mirtazapine (in standard effective doses) in a patient with treatment-resistant depression. We also review the literature and discuss the utility of triple antidepressant combination in treatment-resistant depression. This clinical case highlights the utility of combining trazodone as a third antidepressant for the relapse of depressive symptoms after the failure of a dual antidepressant combination. Trazodone may be advantageous in patients presenting recurrence of moderate-to-severe depressive symptoms that include sleep problems and/or insomnia and may be particularly useful when benzodiazepines are not recommended. Although its use may be controversial and associated with higher risk of side-effects, more investigation is needed to determine the efficacy and safety for triple antidepressant combinations as reliable strategies for treatment-resistant depression in clinical practice.

Treatment-resistant depression: therapeutic trends, challenges, and future directions

BACKGROUND

Patients with major depression respond to antidepressant treatment, but 10%-30% of them do not improve or show a partial response coupled with functional impairment, poor quality of life, suicide ideation and attempts, self-injurious behavior, and a high relapse rate. The aim of this paper is to review the therapeutic options for treating resistant major depressive disorder, as well as evaluating further therapeutic options.

METHODS

In addition to Google Scholar and Quertle searches, a PubMed search using key words was conducted, and relevant articles published in English peer-reviewed journals (1990-2011) were retrieved. Only those papers that directly addressed treatment options for treatment-resistant depression were retained for extensive review.

RESULTS

Treatment-resistant depression, a complex clinical problem caused by multiple risk factors, is targeted by integrated therapeutic strategies, which include optimization of medications, a combination of antidepressants, switching of antidepressants, and augmentation with non-antidepressants, psychosocial and cultural therapies, and somatic therapies including electroconvulsive therapy, repetitive transcranial magnetic stimulation, magnetic seizure therapy, deep brain stimulation, transcranial direct current stimulation, and vagus nerve stimulation. As a corollary, more than a third of patients with treatment-resistant depression tend to achieve remission and the rest continue to suffer from residual symptoms. The latter group of patients needs further study to identify the most effective therapeutic modalities. Newer biomarker-based antidepressants and other drugs, together with non-drug strategies, are on the horizon to address further the multiple complex issues of treatment-resistant depression.

CONCLUSION

Treatment-resistant depression continues to challenge mental health care providers, and further relevant research involving newer drugs is warranted to improve the quality of life of patients with the disorder.