Dataset Information

Efficacy and acceptability of next step treatment strategies in adults with treatment-resistant major depressive disorder: protocol for systematic review and network meta-analysis.

ABSTRACT:

Introduction

For major depression, a one-size-fits-all treatment does not exist. Patients enter a 'trial-and-change' algorithm in which effective therapies are subsequently applied. Unfortunately, an empirically based order of treatments has not yet been determined. There is a magnitude of different treatment strategies while clinical trials only compare a small number of these. Network meta-analyses (NMA) might offer a solution, but so far have been limited in scope and did not account for possible differences in population characteristics that arise with increasing levels of treatment-resistance, potentially violating the transitivity assumption. We; therefore, present a protocol for a systematic review and NMA aiming at summarising and ranking treatments for treatment-resistant depression (TRD) while covering a broad range of therapeutic options and accounting for possible differences in population characteristics at increasing levels of treatment-resistance.

Methods and analysis

Randomised controlled trials will be included that compared next-step pharmacological, neuromodulation or psychological treatments for treatment-resistant depression (TRD; ie, failure to respond to ≥1 adequate antidepressant drug trial(s) in the current episode) to each other or to a control condition. Primary outcomes will be the proportion of patients who responded to (efficacy) and dropped out of (acceptability) the allocated treatment. A random effects NMA will be conducted, synthesising the evidence for each outcome and determining the differential efficacy of treatments. Heterogeneity in treatment nodes will be reduced by considering alternative geometries of the network structure and by conducting a meta-regression examining different levels of TRD. Local and global methods will be applied to evaluate consistency. The Cochrane Risk of Bias 2 tool, Confidence in Network Meta-Analysis and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework will be used to assess risk of bias and certainty.

Ethics and dissemination

This review does not require ethical approval.

SUBMITTER: Muit JJ

PROVIDER: S-EPMC9016400 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Publications

Efficacy and acceptability of next step treatment strategies in adults with treatment-resistant major depressive disorder: protocol for systematic review and network meta-analysis.

Muit Jan Jacobus JJ van Eijndhoven Philip F P PFP Cipriani Andrea A Dalhuisen Iris I van Bronswijk Suzanne S Furukawa Toshi A TA Ruhe Henricus G HG

BMJ open 20220418 4

<h4>Introduction</h4>For major depression, a one-size-fits-all treatment does not exist. Patients enter a 'trial-and-change' algorithm in which effective therapies are subsequently applied. Unfortunately, an empirically based order of treatments has not yet been determined. There is a magnitude of different treatment strategies while clinical trials only compare a small number of these. Network meta-analyses (NMA) might offer a solution, but so far have been limited in scope and did not account ...[more]

PMID: 35437250

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Project description:BackgroundTreatment-resistant depression (TRD) refers to patients with major depressive disorder who do not remit after 2 or more antidepressant trials. TRD is common and highly debilitating, but its neurobiological basis remains poorly understood. Recent neuroimaging studies have revealed cortical connectivity gradients that dissociate primary sensorimotor areas from higher-order associative cortices. This fundamental topography determines cortical information flow and is affected by psychiatric disorders. We examined how TRD impacts gradient-based hierarchical cortical organization.MethodsIn this secondary study, we analyzed resting-state functional magnetic resonance imaging data from a mindfulness-based intervention enrolling 56 patients with TRD and 28 healthy control subjects. Using gradient extraction tools, baseline measures of cortical gradient dispersion within and between functional brain networks were derived, compared across groups, and associated with graph theoretical measures of network topology. In patients, correlation analyses were used to associate measures of cortical gradient dispersion with clinical measures of anxiety, depression, and mindfulness at baseline and following the intervention.ResultsCortical gradient dispersion was reduced within major intrinsic brain networks in patients with TRD. Reduced cortical gradient dispersion correlated with increased network degree assessed through graph theory-based measures of network topology. Lower dispersion among default mode, control, and limbic network nodes related to baseline levels of trait anxiety, depression, and mindfulness. Patients' baseline limbic network dispersion predicted trait anxiety scores 24 weeks after the intervention.ConclusionsOur findings provide preliminary support for widespread alterations in cortical gradient architecture in TRD, implicating a significant role for transmodal and limbic networks in mediating depression, anxiety, and lower mindfulness in patients with TRD.

Project description:Background: Major Depressive Disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of non-medicated subjects (MDD patients and controls) to select genes of which expression is predictive for disease status. To reveal blood gene expression changes related to MDD disease, we applied a powerful ex vivo stimulus to the blood, i.e. incubation with lipopolysaccharide (LPS; 10 ng/ml blood). Results: Based on LPS-stimulated blood gene expression using whole-genome microarrays in 42 subjects (primary cohort; 21 MDD patients (mean age 42.3 years), 21 healthy controls (mean age 41.9 years)), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated for the primary cohort using an independent quantitative PCR method (P = 0.007). The difference between depressive patients and controls was confirmed (P = 0.019) in a replication cohort of 13 patients with MDD (mean age 42.8 years) and 14 controls (mean age 45.6 years). The MDD-signature score comprised of expression levels of 7 genes could discriminate depressive patients from controls with sensitivity of 76.9% and specificity of 71.8%. Conclusions: We show for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of MDD. In total, 33 MDD patients and 34 healthy controls were analyzed using basal gene expression in whole blood, and gene expression from whole blood that was stimulated with LPS for 5-6 h, using microarrays. Patients were arbitrarily selected from all patients to serve as primary cohort (nMDD = 21 (MDD01-MDD21); nControls = 21 (Con01-Con21)), or replication cohort (nMDD = 12 (MDD22-MDD35); nControls = 13 (Con22-Con37)) using microarrays. This submission does not include Samples CON21_LPS or CON30_LPS.

Project description:Background: With the growing importance of research about the association between neuroinflammation and major depressive disorder (MDD), anti-inflammatory agents have been used as a new antidepressant therapy in clinical practice. We conducted a network meta-analysis (NMA) with up-to-date evidence to compare different anti-inflammatory agents for improving the treatment of MDD patients. Methods: To identify eligible randomized clinical trials, four databases (i.e, the Cochrane Library, Web of Science, PubMed and Embase) were searched from inception date to May 31, 2020. Anti-inflammatory agents were defined as non-steroidal anti-inflammatory drugs (NSAIDs), corticosteroids, cytokine inhibitors, statins, pioglitazone, minocycline, N-acetylcysteine (NAC) and omega-3 fatty acid (Omega-3 FA). The main outcomes of this NMA were efficacy, acceptability and remission rate. Risk ratio (RR) was adopted for dichotomous outcomes, and the confidence interval (CI) was set at 95%. STATA 14.0 and R 3.6.3 were used to conduct the NMA. The study protocol was registered with PROSPERO (CRD42020182531). Results: A total of 39 studies, involving 2871 participants, were included in quantitative data synthesis. For efficacy, NSAIDs (RR=0.50, 95%CI: 0.26-0.73) and pioglitazone (RR=0.45, 95%CI: 0.20-0.84) were more favorable than placebo. With respect to acceptability, NSAIDs were more acceptable than placebo (RR=0.89, 95%CI: 0.77-0.99) and minocycline (RR=1.22, 95%CI: 1.03-1.49). For remission, NSAIDs were more superior than placebo (RR=0.48, 95%CI: 0.27-0.79) and Omega-3 FA (RR=2.01, 95%CI: 1.09-3.90), while NACs were more favorable than placebo (RR=0.39, 95%CI: 0.13-0.99). Based on the surface under the cumulative ranking curve (SUCRA) value, corticosteroids (0.86) were the best anti-inflammatory agent for MDD patients in terms of efficacy, but the head-to-head comparisons for the efficacy of glucocorticoids and other agents were not statistically significant. As for acceptability, NSAIDs (0.81) were much better than other anti-inflammatory agents. Besides, NAC (0.80) was the best anti-inflammatory agent in the terms of remission. Conclusions: In summary, we found that corticosteroids were more superior than other agents in terms of efficacy according to the SUCRA value. However, this result must be interpreted with caution because the head-to-head comparisons for the efficacy of glucocorticoids and other agents did not reach statistical significance. NSAIDs were recommended for acceptability and NAC for remission rate.

Dataset Information

Efficacy and acceptability of next step treatment strategies in adults with treatment-resistant major depressive disorder: protocol for systematic review and network meta-analysis.

Introduction

Methods and analysis

Ethics and dissemination

Publications

Efficacy and acceptability of next step treatment strategies in adults with treatment-resistant major depressive disorder: protocol for systematic review and network meta-analysis.

Similar Datasets

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