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Objectives: To determine the prevalence and correlates of treatment-resistant schizophrenia (TRS) through a systematic review and meta-analysis. Methods: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria, an electronic search was performed in PubMed and Embase through May 17, 2022. All study designs that assessed a minimum of 20 schizophrenia-spectrum patients and provided data on TRS prevalence or allowed its calculation were included. Estimates were produced using a random-effects model meta-analysis. Results: The TRS prevalence across 50 studies (n = 29,390) was 36.7% (95%CI 33.1-40.5, p < 0.0001). The prevalence ranged from 22% (95%CI 18.4-25.8) in first-episode to 39.5% (95%CI 32.2-47.0) in multiple-episode samples (Q = 18.27, p < 0.0001). Primary treatment resistance, defined as no response from the first episode, was 23.6% (95%CI 20.5-26.8) vs. 9.3% (95%CI 6.8-12.2) for later-onset/secondary (≥ 6 months after initial treatment response). Longer illness duration and recruitment from long-term hospitals or clozapine clinics were associated with higher prevalence estimates. In meta-regression analyses, older age and poor functioning predicted greater TRS. When including only studies with lower bias risk, the TRS prevalence was 28.4%. Conclusion: Different study designs and recruitment strategies accounted for most of the observed heterogeneity in TRS prevalence rates. The results point to early-onset and later-onset TRS as two separate disease pathways requiring clinical attention. Registration number: PROSPERO CRD42018092033.

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OBJECTIVES: To determine the prevalence and correlates of treatment-resistant schizophrenia (TRS) through a systematic review and meta-analysis. METHODS: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria, an electronic search was performed in PubMed and Embase through May 17, 2022. All study designs that assessed a minimum of 20 schizophrenia-spectrum patients and provided data on TRS prevalence or allowed its calculation were included. Estimates were produced using a random-effects model meta-analysis. RESULTS: The TRS prevalence across 50 studies (n = 29,390) was 36.7% (95%CI 33.1-40.5, p < 0.0001). The prevalence ranged from 22% (95%CI 18.4-25.8) in first-episode to 39.5% (95%CI 32.2-47.0) in multiple-episode samples (Q = 18.27, p < 0.0001). Primary treatment resistance, defined as no response from the first episode, was 23.6% (95%CI 20.5-26.8) vs. 9.3% (95%CI 6.8-12.2) for later-onset/secondary (≥ 6 months after initial treatment response). Longer illness duration and recruitment from long-term hospitals or clozapine clinics were associated with higher prevalence estimates. In meta-regression analyses, older age and poor functioning predicted greater TRS. When including only studies with lower bias risk, the TRS prevalence was 28.4%. CONCLUSION: Different study designs and recruitment strategies accounted for most of the observed heterogeneity in TRS prevalence rates. The results point to early-onset and later-onset TRS as two separate disease pathways requiring clinical attention.

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BACKGROUND: Dimensional approaches can decompose a construct in a set of continuous variables, improving the characterization of complex phenotypes, such as schizophrenia. However, the five-factor model of the Positive and Negative Syndrome Scale (PANSS), the most used instrument in schizophrenia research, yielded poor fits in most confirmatory factor analysis (CFA) studies, raising concerns about its applications. Thus, we aimed to identify dimensional PANSS CFA models with good psychometric properties by comparing the traditional CFA with three methodological approaches: Bayesian CFA, multilevel modeling, and Multiple Indicators Multiple Causes (MIMIC) modeling. METHODS: Clinical data of 700 schizophrenia patients from four centers were analyzed. We first performed a traditional CFA. Next, we tested the three techniques: 1) a Bayesian CFA; 2) a multilevel analysis using the centers as level; and 3) a MIMIC modeling to evaluate the impact of clinical staging on PANSS factors and items. RESULTS: CFA and Bayesian CFA produced poor fit models. However, when adding a multilevel structure to the CFA model, a good fit model emerged. MIMIC modeling yielded significant differences in the factor structure between the clinical stages of schizophrenia. Sex, age, age of onset, and duration of illness did not significantly affect the model fit. CONCLUSION: Our comparison of different CFA methods highlights the need for multilevel structure to achieve a good fit model and the potential utility of staging models (rather than the duration of illness) to deal with clinical heterogeneity in schizophrenia. Large prospective samples with biological data should help to understand the interplay between psychometrics concerns and neurobiology research.

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BACKGROUND: Determining the best latent structure of negative symptoms in schizophrenia could benefit assessment tools, neurobiological research, and targeted interventions. However, no review systematically evaluated studies that assessed and validated latent models of negative symptoms. OBJECTIVE: To identify and evaluate existing latent structure models in the literature of negative symptoms and to determine the best model. METHOD: Systematic search of MEDLINE, EMBASE, and Scopus on July 19, 2020, for confirmatory factor analysis models of negative symptoms in patients with schizophrenia. The available evidence was assessed through 2 sets of criteria: (1) study design quality-based on negative symptoms assessment and modeling strategy and (2) psychometric quality and model fit-based on fit indices and factor definition quality. RESULTS: In total, 22 studies (n = 17 086) from 9 countries were included. Studies differed greatly regarding symptom scales, setting, and sample size (range = 86-6889). Dimensional models included 2-6 factors (median = 4). Twelve studies evaluated competing models and adopted appropriate instruments to assess the latent structure of negative symptoms. The 5-factor and hierarchical models outperformed unitary, 2-factor, and 3-factor models on all direct comparisons, and most of the analyses derived from the Brief Negative Symptom Scale. Considering the quality criteria proposed, 5-factor and hierarchical models achieved excellent fit in just one study. CONCLUSIONS: Our review points out that the 5-factor and hierarchical models represent the best latent structure of negative symptoms, but the immaturity of the relevant current literature may affect the robustness of this conclusion. Future studies should address current limitations regarding psychometric properties and also address biological and clinical validity to refine available models.

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Electrical and magnetic brain stimulation techniques present distinct mechanisms and efficacy in the acute treatment of depression. This was an umbrella review of meta-analyses of randomized controlled trials of brain stimulation techniques for managing acute major depressive episodes. A systematic review was performed in the PubMed/MEDLINE databases from inception until March 2020. We included the English language meta-analysis with the most randomized controlled trials on the effects of any brain stimulation technique vs. control in adults with an acute depressive episode. Continuous and dichotomous outcomes were assessed. A Measurement Tool to Assess Systematic Reviews-2 was applied and the credibility of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation framework. Seven meta-analyses were included (5,615 patients), providing evidence for different modalities of brain stimulation techniques. Three meta-analyses were evaluated as having high methodological quality, three as moderate, and one as low. The highest quality of evidence was found for high frequency-repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation, and bilateral rTMS. There is strong clinical research evidence to guide future clinical use of some techniques. Our results confirm the heterogeneity of the effects across these techniques, indicating that different mechanisms of action lead to different efficacy profiles.

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Adherence to antidepressants is crucial for optimal treatment outcomes when treating depressive disorders. However, poor adherence is common among patients prescribed antidepressants. This targeted review summarizes the main factors associated with poor adherence, interventions that promote antidepressant adherence, pharmacological aspects related to antidepressant adherence, and formulates 10 clinical recommendations to optimize antidepressant adherence. Patient-related factors associated with antidepressant non-adherence include younger age, psychiatric and medical comorbidities, cognitive impairment, and substance use disorders. Prescriber behavior-related factors include neglecting medical and family histories, selecting poorly tolerated antidepressants, or complex antidepressant regimens. Multi-disciplinary interventions targeting both patient and prescriber, aimed at improving antidepressant adherence, include psychoeducation and providing the patient with clear behavioral interventions to prevent/minimize poor adherence. Regarding antidepressant choice, agents with individually tailored tolerability profile should be chosen. Ten clinical recommendations include four points focusing on the patient (therapeutic alliance, adequate history taking, measurement of depressive symptoms, and adverse effects improved access to clinical care), three focusing on prescribing practice (psychoeducation, individually tailored antidepressant choice, simplified regimen), two focusing on mental health services (improved access to mental health care, incentivized adherence promotion and monitoring), and one relating to adherence measurement (adherence measurement with scales and/or therapeutic drug monitoring).

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Adherence to antidepressants is crucial for optimal treatment outcomes when treating depressive disorders. However, poor adherence is common among patients prescribed antidepressants. This targeted review summarizes the main factors associated with poor adherence, interventions that promote antidepressant adherence, pharmacological aspects related to antidepressant adherence, and formulates 10 clinical recommendations to optimize antidepressant adherence. Patient-related factors associated with antidepressant non-adherence include younger age, psychiatric and medical comorbidities, cognitive impairment, and substance use disorders. Prescriber behavior-related factors include neglecting medical and family histories, selecting poorly tolerated antidepressants, or complex antidepressant regimens. Multi-disciplinary interventions targeting both patient and prescriber, aimed at improving antidepressant adherence, include psychoeducation and providing the patient with clear behavioral interventions to prevent/minimize poor adherence. Regarding antidepressant choice, agents with individually tailored tolerability profile should be chosen. Ten clinical recommendations include four points focusing on the patient (therapeutic alliance, adequate history taking, measurement of depressive symptoms, and adverse effects improved access to clinical care), three focusing on prescribing practice (psychoeducation, individually tailored antidepressant choice, simplified regimen), two focusing on mental health services (improved access to mental health care, incentivized adherence promotion and monitoring), and one relating to adherence measurement (adherence measurement with scales and/or therapeutic drug monitoring).

Assuntos

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Electrical and magnetic brain stimulation techniques present distinct mechanisms and efficacy in the acute treatment of depression. This was an umbrella review of meta-analyses of randomized controlled trials of brain stimulation techniques for managing acute major depressive episodes. A systematic review was performed in the PubMed/MEDLINE databases from inception until March 2020. We included the English language meta-analysis with the most randomized controlled trials on the effects of any brain stimulation technique vs. control in adults with an acute depressive episode. Continuous and dichotomous outcomes were assessed. A Measurement Tool to Assess Systematic Reviews-2 was applied and the credibility of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation framework. Seven meta-analyses were included (5,615 patients), providing evidence for different modalities of brain stimulation techniques. Three meta-analyses were evaluated as having high methodological quality, three as moderate, and one as low. The highest quality of evidence was found for high frequency-repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation, and bilateral rTMS. There is strong clinical research evidence to guide future clinical use of some techniques. Our results confirm the heterogeneity of the effects across these techniques, indicating that different mechanisms of action lead to different efficacy profiles.

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OBJECTIVES: To describe the onset pattern, frequency, and severity of the signs and symptoms of the prodrome of the first hypomanic/manic episode and first depressive episode of bipolar disorder (BD) and to investigate the influence of a history of childhood maltreatment on the expression of prodromal symptoms. METHODS: Using a semi-structured interview, the Bipolar Prodrome Symptom Scale-Retrospective (BPSS-R), information regarding prodromal symptoms was assessed from patients with a DSM-IV diagnosis of BD. History of childhood maltreatment was evaluated using the Childhood Trauma Questionnaire (CTQ). RESULTS: Forty-three individuals with stable BD were included. On average, the prodrome of mania lasted 35.8 ± 68.7 months and was predominantly subacute or insidious, with rare acute presentations. The prodrome of depression lasted 16.6 ± 23.3 months and was also predominantly subacute or insidious, with few acute presentations. The prodromal symptoms most frequently reported prior to the first hypomanic or manic episode were mood lability, depressive mood, and impatience. A history of childhood abuse and neglect was reported by 81.4% of participants. Presence of childhood maltreatment was positively associated with prodromal symptoms, including social withdrawal, decreased functioning, and anhedonia. CONCLUSIONS: This study provides evidence of a long-lasting, symptomatic prodrome prior to first hypomanic/manic and depressive episode in BD and suggests that a history of childhood maltreatment influences the manifestations of this prodrome.

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OBJECTIVE: To characterize the early stages of bipolar disorder (BD), defined as the clinical prodrome/subsyndromal stage and first-episode phase, and strategies for their respective treatment. METHODS: A selective literature search of the PubMed, Embase, PsycINFO, and ISI databases from inception until March 2014 was performed. Included in this review were articles that a) characterized prodromal and first-episode stages of BD or b) detailed efficacy and safety/tolerability of interventions in patients considered prodromal for BD or those with only one episode of mania/hypomania. RESULTS: As research has only recently focused on characterization of the early phase of BD, there is little evidence for the effectiveness of any treatment option in the early phase of BD. Case management; individual, group, and family therapy; supportive therapy; and group psychoeducation programs have been proposed. Most evidence-based treatment guidelines for BD do not address treatment specifically in the context of the early stages of illness. Evidence for pharmacotherapy is usually presented in relation to illness polarity (i.e., manic/mixed or depressed) or treatment phase. CONCLUSIONS: Although early recognition and treatment are critical to preventing unfavorable outcomes, there is currently little evidence for interventions in these stages of BD.

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