Currently, 30-50 % of individuals with depression and 40 % with anxiety-collectively referred to as common mental disorders (CMDs), exhibit inadequate responses to antidepressant treatments.

To assess the effectiveness and safety of drug-metabolizing enzyme pharmacogenetic variation informed treatment (PGxIT) versus usual antidepressant treatment (UT) in patients with CMDs.

A literature search was conducted in the MEDLINE, Scopus, and Cochrane Library databases from inception until January 30, 2024.

Studies were selected based on CMD diagnoses, reporting on the genetic variations of drug-metabolizing enzyme (DME) genes in relation to antidepressants, involving PGxIT and UT groups with human subjects, and published in English.

Data extraction and quality assessment were performed independently by two authors. A pooled risk ratio (RR) with 95 % CI was estimated using both random and fixed-effect models, and heterogeneity was assessed using Cochran's Q test and the I2 statistic. The publication bias of eligible studies was assessed using post hoc Doi plots and the LFK index.

This systematic review included 18 studies (n = 7021). The PGxIT demonstrated greater efficacy in the remission of symptoms of depressive disorder at 8 weeks (RR 1.523 [95 % CI: 1.255-1.843]; I2 = 48 %) and 12 weeks (RR 1.631 [95 % CI: 1.001-2.657]; I2 = 86 %; p < 0.01), and symptoms of anxiety disorder compared to UT. Additionally, the risk of adverse drug events (ADEs) was significantly lower in the PGxIT group (RR = 0.65 [95 % CI: 0.52-0.82]; I2 = 0 %) than in the UT group. The certainty of evidence for both outcomes was moderate.

This systematic review and meta-analysis suggest that pharmacogenetically guided antidepressant treatment, based on genetic variation in drug-metabolizing enzymes, is associated with superior efficacy in the remission of symptoms for patients with depressive disorders and a reduction in ADEs compared to usual treatment and the findings of the systematic review for remission in anxiety disorders indicate that, PGx guided treatment is also associated with increased remission of symptoms in anxiety disorders compared to usual treatment.

Ablative surgery is an intervention of last resort for treatment-resistant obsessive-compulsive disorder (TROCD). Our center has been using bilateral anterior capsulotomy (BAC) for the past 20 years for patients eligible for limbic surgery. This report details our experience with BAC for TROCD.

Five patients with OCD met eligibility criteria for BAC. Entry protocols were complex and took around 6 months to complete. Stereotactic radiofrequency was used to produce the capsulotomies. Lesion length varied between 5.7 and 16.9 mm in the coronal plane. Patients were followed between 4 and 20 years.

All 5 patients (100%) were responders as defined by the widely accepted criteria of a reduction of ≥35% in Yale-Brown Obsessive Compulsive Scale (YBOCS) score at 18-month follow-up. Four patients remained responders at the 48 months. One patient was lost to follow-up. Responder status when viewed from the perspective of the YBOCS was sustained over the 4- to 20-year follow-up with one relapse 19 years postsurgery when medications were discontinued. Real-world psychiatric outcomes were different as other vulnerabilities surfaced illustrating the multifactorial determinants of mental health. No patient had any significant long-term neurocognitive or physical side effects.

BAC should remain an option of last resort for patients with severe OCD who remain unresponsive to all other interventions.

Psilocybin, a naturally occurring serotonergic agonist in some mushroom species, has shown promise as a novel, fast-acting pharmacotherapy seeking to overcome the limitations of conventional first-line antidepressants. Studying psilocybin effects on cognition and emotional processing may help to clarify the mechanisms underlying the therapeutic potential of psilocybin and may also support studies with people suffering from depression. Thus, this review aims to provide a comprehensive overview of the current literature regarding the effects of psilocybin on these two key areas in both healthy and depressed populations.

A systematic search was performed on 29 January 2024, in the PubMed, EBSCOhost, Web of Science and SCOPUS databases. After duplicates removal, study selection was conducted considering pre-specified criteria. Data extraction was then performed. The quality assessment of the studies was carried out using the Cochrane Collaboration tools for randomized (RoB 2.0) and non-randomized (ROBINS-I) controlled trials.

Twenty articles were included, with 18 targeting healthy adults and two adults with depression. Results point to impairments within attentional and inhibitory processes, and improvements in the domains of creativity and social cognition in healthy individuals. In the population with depression, only cognitive flexibility and emotional recognition were affected, both being enhanced. The comparison of outcomes from both populations proved limited.

Psilocybin acutely alters several cognitive domains, with a localized rather than global focus, in a dose- and time-dependent manner. However, the significant methodological constraints call for further research, in the context of depression and with standardized protocols, with longitudinal studies also imperative.

The aim of the present study was to examine the acute and chronic effects of wild blueberry supplementation on mood, executive function, and serum biomarkers of neuroplasticity, inflammation, and oxidative stress in emerging adults with moderate-to-severe depressive symptoms.

In this double-blind trial, 60 emerging adults (Mage = 20.0 years, 32% male) with self-reported depressive symptoms were randomly assigned to receive a single blueberry drink (acute phase), followed by 6 weeks of daily blueberry supplementation (chronic phase), or a matched placebo drink. The primary outcome was Beck Depression Inventory-II (BDI-II) scores at 6-week follow-up. Further measures included momentary affect (PANAS-X) and accuracy on an executive function task. The data were analyzed using ANCOVAs adjusted for baseline values, sex, and habitual fruit and vegetable intake. Estimated marginal means were calculated to compare the treatment arms.

The blueberry drink significantly improved positive affect (p = 0.026) and executive function (p = 0.025) at 2 h post-ingestion, with change scores being positively correlated in the blueberry group (r = 0.424, p = 0.017). However, after six weeks of supplementation the reduction in BDI-II scores was greater in the placebo group by 5.8 points (95% CI: 0.8-10.7, p = 0.023). Generalized anxiety and anhedonia also decreased significantly more in the placebo group. No significant differences were found for any of the biomarkers.

Six weeks of wild blueberry supplementation were inferior to placebo in reducing depressive symptoms. Nevertheless, the correlated improvements in positive affect and executive function after a single dose of blueberries point to a beneficial, albeit transient, psychological effect. These contrasting results suggest a biphasic, hormetic-like response that warrants further investigation.

NCT04647019, dated 30 November, 2020.

Depression is a common and serious psychological condition, which seriously affects individual well-being and functional ability. Traditional treatment methods include drug therapy and psychological counseling; however, these methods have different degrees of side effects and limitations. In recent years, nonconvulsive electrotherapy (NET) has attracted increasing attention as a noninvasive treatment method. However, the clinical efficacy and potential mechanism of NET on depression are still unclear. We hypothesized that NET has a positive clinical effect in the treatment of depression, and may have a regulatory effect on serum inflammatory factors during treatment.

To assess the effects of NET on depression and analyze changes in serum inflammatory factors.

This retrospective study enrolled 140 patients undergoing treatment for depression between May 2017 and June 2022, the observation group that received a combination of mindfulness-based stress reduction (MBSR) and NET treatment (n = 70) and the control group that only received MBSR therapy (n = 70). The clinical effectiveness of the treatment was evaluated by assessing various factors, including the Hamilton Depression Scale (HAMD)-17, self-rating idea of suicide scale (SSIOS), Pittsburgh Sleep Quality Index (PSQI), and levels of serum inflammatory factors before and after 8 wk of treatment. The quality of life scores between the two groups were compared. Comparisons were made using t and χ2 tests.

After 8 wk of treatment, the observation group exhibited a 91.43% overall effectiveness rate which was higher than that of the control group which was 74.29% (64 vs 52, χ2 = 7.241; P < 0.05). The HAMD, SSIOS, and PSQI scores showed a significant decrease in both groups. Moreover, the observation group had lower scores than the control group (10.37 ± 2.04 vs 14.02 ± 2.16, t = 10.280; 1.67 ±0.28 vs 0.87 ± 0.12, t = 21.970; 5.29 ± 1.33 vs 7.94 ± 1.35, t = 11.700; P both < 0.001). Additionally, there was a notable decrease in the IL-2, IL-1β, and IL-6 in both groups after treatment. Furthermore, the observation group exhibited superior serum inflammatory factors compared to the control group (70.12 ± 10.32 vs 102.24 ± 20.21, t = 11.840; 19.35 ± 2.46 vs 22.27 ± 2.13, t = 7.508; 32.25 ± 4.6 vs 39.42 ± 4.23, t = 9.565; P both < 0.001). Moreover, the observation group exhibited significantly improved quality of life scores compared to the control group (Social function: 19.25 ± 2.76 vs 16.23 ± 2.34; Emotions: 18.54 ± 2.83 vs 12.28 ± 2.16; Environment: 18.49 ± 2.48 vs 16.56 ± 3.44; Physical health: 19.53 ± 2.39 vs 16.62 ± 3.46; P both < 0.001) after treatment.

MBSR combined with NET effectively alleviates depression, lowers inflammation (IL-2, IL-1β, and IL-6), reduces suicidal thoughts, enhances sleep, and improves the quality of life of individuals with depression.

The gut microbiome is emerging as an important factor in signaling along the gut-brain axis. The intimate physiological connection between the gut and the brain allows perturbations in the microbiome to be directly transmitted to the central nervous system and thereby contribute to psychiatric and neurological diseases. Common microbiome perturbations result from the ingestion of xenobiotic compounds including pharmaceuticals such as psychotropic drugs. In recent years, a variety of interactions between these drug classes and the gut microbiome have been reported, ranging from direct inhibitory effects on gut bacteria to microbiome-mediated drug degradation or sequestration. Consequently, the microbiome may play a critical role in influencing the intensity, duration, and onset of therapeutic effects, as well as in influencing the side effects that patients may experience. Furthermore, because the composition of the microbiome varies from person to person, the microbiome may contribute to the frequently observed interpersonal differences in the response to these drugs. In this review, we first summarize the known interactions between xenobiotics and the gut microbiome. Then, for psychopharmaceuticals, we address the question of whether these interactions with gut bacteria are irrelevant for the host (i.e., merely confounding factors in metagenomic analyses) or whether they may even have therapeutic or adverse effects.

Transcranial magnetic stimulation (TMS) is a safe, tolerable, and evidence-based intervention for major depressive disorder (MDD). However, even after decades of research, nearly half of the patients with MDD fail to respond to conventional TMS, with responding slowly and requiring daily attendance at the treatment site for 4-6 weeks. To intensify antidepressant efficacy and shorten treatment duration, accelerated TMS protocols, which involve multiple sessions per day over a few days, have been proposed and evaluated for safety and viability. We reviewed and summarized the current knowledge in accelerated TMS, including stimulation parameters, antidepressant efficacy, anti-suicidal efficacy, safety, and adverse effects. Limitations and suggestions for future directions are also addressed, along with a brief discussion on the application of accelerated TMS during the COVID-19 pandemic. This article is categorized under: Neuroscience > Clinical Neuroscience.

The substantial challenges facing high and low dose psychedelic drug development to achieve regulatory approval have been documented in the scientific literature. These limitations have not deterred drug developers and social media from repeatedly misleading patients, the public and health professionals. Developing "micro doses" of psychedelics overcomes many of the scientific and regulatory challenges of high dose psychedelics. If micro-dosing could be shown to be efficacious and safe for long term use, it could be administered in the typical model for treatment of mental disorders. Such a model would be more cost effective than the high dose/intense psychotherapy model currently described and could be readily available to all individuals who need another medication option. Outpatient psychotherapeutic agents have a clear route for approval and would be unlikely to be burdened by the extensive Risks Evaluation and Mitigation Strategy needed for high dose use. There may be a different therapeutic role for both high and low dose psychedelic agents. This article is part of the Special Issue on "National Institutes of Health Psilocybin Research Speaker Series".

Pharmacogenetics has potential for optimizing use of psychotropics. CYP2D6 and CYP2C19 are two clinically relevant pharmacogenes in the prescribing of antidepressants. Using cases recruited from the Understanding Drug Reactions Using Genomic Sequencing (UDRUGS) study, we aimed to evaluate the clinical utility of genotyping CYP2D6 and CYP2C19 in antidepressant response. Genomic and clinical data for patients who were prescribed antidepressants for mental health disorders, and experienced adverse reactions (ADRs) or ineffectiveness, were extracted for analysis. Genotype-inferred phenotyping of CYP2D6 and CYP2C19 was carried out as per Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. A total of 52 patients, predominantly New Zealand Europeans (85%) with a median age (range) of 36 years (15-73), were eligible for analysis. Thirty-one (60%) reported ADRs, 11 (21%) ineffectiveness, and 10 (19%) reported both. There were 19 CYP2C19 NMs, 15 IMs, 16 RMs, one PM and one UM. For CYP2D6, there were 22 NMs, 22 IMs, four PMs, three UMs, and one indeterminate. CPIC assigned a level to each gene-drug pair based on curated genotype-to-phenotype evidence. We analyzed a subgroup of 45 cases, inclusive of response type (ADRs/ineffectiveness). Seventy-nine (N = 37 for CYP2D6, N = 42 for CYP2C19) gene-drug/antidepressant-response pairs with CPIC evidence levels of A, A/B, or B were identified. Pairs were assigned as 'actionable' if the CYP phenotypes potentially contributed to the observed response. We observed actionability in 41% (15/37) of CYP2D6-antidepressant-response pairs and 36% (15/42) of CYP2C19-antidepressant-response pairs. In this cohort, CYP2D6 and CYP2C19 genotypes were actionable for a total of 38% pairs, consisting of 48% in relation to ADRs and 21% in relation to drug ineffectiveness.

Medicinal plants belonging to the Verbenaceae family demonstrated antidepressant effects in preclinical studies. Depression is one of the largest contributors to the global health burden of all countries. Plants from the Aloysia genus are traditionally used for affective disorders, and some of them have proven anxiolytic and antidepressant activity. The aim of this work was to evaluate the antidepressant effect of the ethanolic extract of Aloysia gratissima var. gratissima (Agg) and Aloysia virgata var. platyphylla (Avp) in mice. A tail suspension test (TST) and forced swimming test (FST) were conducted after three doses in a period of 24 h and after 7 days of treatment. Imipramine was used as an antidepressant drug. The main results demonstrated that Agg extract reduced the immobility time in mice treated orally for 7 consecutive days when compared to the control group (reduced by about 77%, imipramine 70%). Animals treated with three doses of Avp in a 24-h period had reduced immobility time in the FST (60%), and after 7 days of treatment the reduction was greater (Avp 50, 100, and 200 about 85%; Avp 400, 96.5%; p < 0.0001, imipramine, 77%). LCMS analysis showed the presence of verbascoside, hoffmaniaketone, and hoffmaniaketone acetate in both, A. virgata var. platyphylla and A. gratissima var gratissima. The flavonoids nepetin and 6-hydroxyluteolin were also found in Agg. Both tested extracts demonstrated promising antidepressant-like activity in mice.

Evidence-based medicine is the cornerstone of shared-decision making in healthcare today. The public deserves clear, transparent and trust-worthy information on drug efficacy. Yet today, many drugs are prescribed and used without solid evidence of efficacy. Clinical trials and randomised clinical trials (RCTs) are the best method to evaluate drug efficacy and side effects. In a shared medical decision-making approach, general practitioners need drug assessment based on patient-important outcomes. The aim of project rebuild the evidence base (REB) is to bridge the gap between the data needed in clinical practice and the data available from clinical research. The drugs will be assessed on clinical patient important outcomes and for a population. Using the Cochrane tools, we propose to analyse for each population and outcome: 1) a meta-analysis based on RCTs with a low risk of bias overall; 2) an evaluation of results of confirmatory RCTs; 3) a statistical analysis of heterrogeneity between RCTs and 4) an analysis of publication bias. Depending on the results of these analyses, the evidence will be categorized in 4 different levels: firm evidence, evidence (to be confirmed), signal or absence of evidence. Project REB proposes a method for reading and interpreting RCTs and their meta-analysis to produce quality data for general practitioners to focus on risk-benefit assessment in the interest of patients. If this data does not exist, it could enable clinical research to better its aim.

In the last two decades the validity of clinical trials in psychiatry has been subject to discussion. The most accepted clinical study method in the medical area, randomized controlled trial (RCT), faces significant problems when applied to the psychiatric world. One of the causes for this scenario is the strict participant inclusion and exclusion criteria that may not represent the real world. The inconsistency of the different endpoint parameters that are used in the field is another cause. We think that psychiatric RCTs' challenges, together with the underlying complexity of psychiatry, lead to a problematic clinical practice. Today, psychoactive drugs are routinely tested not in an official clinical trial setting. Off-label psychoactive drugs are commonly prescribed, and other substances, such as herbal remedies, are also regularly consumed. Learning from those real-life experiments can teach us useful lessons. Real-world data (RWD) includes information about heterogeneous patient populations, and it can be measured with standardized parameters. Collecting RWD can also address the need for systematically documenting and sharing case reports' outcomes. We suggest using digital tools to capture objective and continuous behavioral data from patients passively. New conclusions will be constantly drawn, possibly allowing more personalized treatment outcomes. The relevant next-generation decision support tools are already available.

Preliminary evidence supports the use of psychedelics for major depressive disorder (MDD). However, less attention has been given to the neural mechanisms behind their effects. We conducted a systematic review examining the neuroimaging correlates of antidepressant response following psychedelic interventions for MDD. Through MEDLINE, Embase, and APA PsycINFO, 187 records were identified and 42 articles were screened. Six published studies and one conference abstract were included. Five ongoing trials were included from subjective outcomesTrials.gov. Our search covered several psychedelics, though included studies were specific to psilocybin, ayahuasca, and lysergic acid diethylamide. Three psilocybin studies noted amygdala activity and functional connectivity (FC) alterations that correlated with treatment response. Two psilocybin studies reported that FC changes in the medial and ventromedial prefrontal cortices correlated with treatment response. Two trials from a single study reported global decreases in brain network modularity which correlated with antidepressant response. One ayahuasca study reported increased activity in the limbic regions following treatment. Preliminary evidence suggests that the default mode and limbic networks may be a target for future research on the neural mechanisms of psychedelics. More data is required to corroborate these initial findings as the evidence summarized in this review is based on four datasets.

Major depressive disorder (MDD) is complex and multifactorial, posing a major challenge of tailoring the optimal medication for each patient. Current practice for MDD treatment mainly relies on trial and error, with an estimated 42-53% response rates for antidepressant use. Here, we sought to generate an accurate predictor of response to a panel of antidepressants and optimize treatment selection using a data-driven approach analyzing combinations of genetic, clinical, and demographic factors. We analyzed the response patterns of patients to three antidepressant medications in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, and employed state-of-the-art machine learning (ML) tools to generate a predictive algorithm. To validate our results, we assessed the algorithm's capacity to predict individualized antidepressant responses on a separate set of 530 patients in STAR*D, consisting of 271 patients in a validation set and 259 patients in the final test set. This assessment yielded an average balanced accuracy rate of 72.3% (SD 8.1) and 70.1% (SD 6.8) across the different medications in the validation and test set, respectively (p < 0.01 for all models). To further validate our design scheme, we obtained data from the Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) of patients treated with citalopram, and applied the algorithm's citalopram model. This external validation yielded highly similar results for STAR*D and PGRN-AMPS test sets, with a balanced accuracy of 60.5% and 61.3%, respectively (both p's < 0.01). These findings support the feasibility of using ML algorithms applied to large datasets with genetic, clinical, and demographic features to improve accuracy in antidepressant prescription.

Emotional blunting is frequently reported by patients with major depressive disorder (MDD) and has been identified as one of the most prominent side effects of antidepressants leading to medication discontinuation. However, antidepressant-induced emotional blunting remains largely unexplored-there lacks a clinical definition of this condition, and no agreeing conclusion has been reached regarding its etiology. Current research suggests that the onset of diminished emotional response may be related to antidepressant dose, with higher doses being more likely to induce emotional blunting. Consequently, most clinicians either reduce the dose or switch to another drug when treating this symptom. Overall, more comprehensive clinical assessments or interviews specifically designed to evaluate antidepressant-induced emotional blunting in MDD patients are in need to elucidate the neuropsychological mechanisms behind this increasingly prevalent symptom.

Background/objective: To describe the design of 'DepMod,' a health-economic Markov model for assessing cost-effectiveness and budget impact of user-defined preventive interventions and treatments in depressive disorders.Methods: DepMod has an epidemiological layer describing how a cohort of people can transition between health states (sub-threshold depression, first episode of mild, moderate or severe depression (partial) remission, recurrence, death). Superimposed on the epidemiological layer, DepMod has an intervention layer consisting of a reference scenario and alternative scenario comparing the effectiveness and cost-effectiveness of a user-defined package of preventive interventions and psychological and pharmacological treatments of depression. Results are presented in terms of quality-adjusted life years (QALYs) gained and healthcare expenditure. Costs and effects can be modeled over 5 years and are subjected to probabilistic sensitivity analysis.Results: DepMod was used to assess the cost-effectiveness of scaling up preventive interventions for treating people with subclinical depression, which showed that there is an 82% probability that scaling up prevention is cost-effective given a willingness-to-pay threshold of €20,000 per QALY.Conclusion: DepMod is a Markov model that assesses the cost-utility and budget impact of different healthcare packages aimed at preventing and treating depression and is freely available for academic purposes upon request at the authors.

The observation that some patients appear to respond better to antidepressants for depression than others encourages the assumption that the effect of antidepressants differs between individuals and that treatment can be personalized.

To compare the outcome variance in patients receiving antidepressants with the outcome variance in patients receiving placebo in randomized controlled trials (RCTs) of adults with major depressive disorder (MDD) and to illustrate, using simulated data, components of variation of RCTs.

From a dataset comprising 522 RCTs of antidepressants for adult MDD, we selected the placebo-controlled RCTs reporting outcomes on the 17 or 21 item Hamilton Depression Rating Scale or the Montgomery-Asberg Depression Rating Scale and extracted the means and SDs of raw endpoint scores or baseline to endpoint changes scores on eligible depression symptom rating scales. We conducted inverse variance random-effects meta-analysis with the variability ratio (VR), the ratio between the outcome variance in the group of patients receiving antidepressants and the outcome variance in the group receiving placebo, as the primary outcome. An increased variance in the antidepressant group would indicate individual differences in response to antidepressants.

We analysed 222 RCTs that investigated 19 different antidepressants compared with placebo in 345 comparisons, comprising a total of 61144 adults with an MDD diagnosis. Across all comparisons, the VR for raw endpoint scores was 0.98 (95% CI 0.96 to 1.00, I2 = 0%) and 1.00 (95% CI 0.99 to 1.02, I2 = 0%) for baseline-to-endpoint change scores.

Based on these data, we cannot reject the null hypothesis of equal variances in the antidepressant group and the placebo group. Given that RCTs cannot provide direct evidence for individual treatment effects, it may be most reasonable to assume that the average effect of antidepressants applies also to the individual patient.

We have recently compared all second-generation as well as selected first-generation antidepressants in terms of efficacy and acceptability in the acute treatment of major depression. Here we present a protocol for a network meta-analysis aimed at extending these results, updating the evidence base and comparing all second-generation as well as selected first-generation antidepressants in terms of specific adverse events and tolerability in the acute treatment of major depression in adults.

We will include all double-blind randomised controlled trials comparing one active drug with another or with placebo in the acute treatment major depression in adults. We will compare the following active agents: agomelatine, amitriptyline, bupropion, citalopram, clomipramine, desvenlafaxine, duloxetine, escitalopram, fluoxetine, fluvoxamine, levomilnacipran, milnacipran, mirtazapine, nefazodone, paroxetine, reboxetine, sertraline, trazodone, venlafaxine, vilazodone and vortioxetine. The main outcomes will include the total number of patients experiencing specific adverse events; experiencing serious adverse events; and experiencing at least one adverse event. Published and unpublished studies will be retrieved through relevant database searches, trial registries and websites; reference selection and data extraction will be completed by at least two independent reviewers. For each outcome we will undertake a network meta-analysis to synthesise all evidence. We will use local and global methods to evaluate consistency. We will perform all analyses in R. We will assess the quality of evidence contributing to network estimates with the Confidence in Network Meta-Analysis web application.

This work will provide an in- depth analysis and an insight into the specific adverse events of individual antidepressants.

This review does not require ethical approval.

CRD42019128141.

Anxiety disorders are common in children and adolescents, and uncertainty remains regarding the optimal strategy of psychotherapies in this population.

To compare and rank the different types of psychotherapies and the different ways of delivering psychological treatments for anxiety disorders in children and adolescents.

PubMed, Cochrane Central Register of Controlled Trials, EMBASE, PsycINFO, Web of Science, CINAHL (Cumulative Index to Nursing and Allied Health Literature), ProQuest Dissertations, LILACS (Literatura Latino Americana em Ciências da Saúde), international trial registers, and US Food and Drug Administration reports were searched from inception to November 30, 2017.

Randomized clinical trials that compared any structured psychotherapy with another psychotherapy or a control condition for anxiety disorders in children and adolescents were selected.

Four researchers independently performed data extraction and quality assessment. Pairwise meta-analyses and Bayesian network meta-analysis within the random-effects model were used to synthesize data.

Efficacy (change in anxiety symptoms) posttreatment and at follow-up, acceptability (all-cause discontinuation), and quality of life and functional improvement were measured. The certainty of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation framework.

A total of 101 unique trials including 6625 unique participants compared 11 different psychotherapies with 4 specific control conditions. The certainty of evidence was rated as low or very low for most comparisons. For efficacy, most psychotherapies were significantly more effective than the wait list condition posttreatment (standardized mean difference [SMD], -1.43 to -0.61) and at the longest follow-up (SMD, -1.84 to -1.64). However, only group cognitive behavioral therapy (CBT) was significantly more effective than the other psychotherapies and all control conditions posttreatment. For acceptability, bibliotherapy CBT had significantly more all-cause discontinuations than some psychotherapies and control conditions (range of odds ratios, 2.48-9.32). In terms of quality of life and functional improvement, CBT (delivered in different ways) was significantly beneficial compared with psychological placebo and the wait list condition (SMDs, 0.73 to 1.99).

Group CBT would be the more appropriate choice of psychotherapy for anxiety disorders in children and adolescents, based on these findings. Other types of psychotherapies and different ways of delivering psychological treatment can be alternative options. Further research is needed to explore specific anxiety disorders, disorder-specific psychotherapy, and moderators of treatment effect.

PROSPERO Identifier: CRD42015016283.