-
The Lancet. Psychiatry Nov 2023Side-effects of psychiatric medication impair quality of life and functioning. Furthermore, they contribute to morbidity, mortality, stigma, and poor treatment...
BACKGROUND
Side-effects of psychiatric medication impair quality of life and functioning. Furthermore, they contribute to morbidity, mortality, stigma, and poor treatment concordance resulting in relapse of psychiatric illness. Guidelines recommend discussing side-effects with patients when making treatment decisions, but a synthesis of antidepressant and antipsychotic side-effects to guide this process is missing, and considering all side-effects is a complex, multidimensional process. We aimed to create comprehensive databases of antipsychotic and antidepressant side-effects, and a digital tool to support database navigation.
METHODS
To create the databases, we did an umbrella review of Embase, PsycINFO, and MEDLINE from database inception to June 26, 2023. We included meta-analyses of randomised controlled trials examining antipsychotic monotherapy in the treatment of schizophrenia or antidepressant monotherapy in the treatment of major depressive disorder. We included meta-analyses in adults (aged ≥18 years) that assessed drugs with a common comparator. The search was complemented by a review of national and international guidelines and consensus statements for the treatment of major depressive disorder and schizophrenia in adults. Effect sizes for antipsychotic and antidepressant side-effects were extracted from meta-analyses examining the largest number of drugs. In cases of incomplete meta-analytic coverage, data were imputed on the basis of guideline-derived ordinal rankings or, if imputation was not possible, ordinal scores were extracted. Both meta-analytic and ordinal outcomes were normalised to provide values between 0 and 1. We then constructed a digital tool, the Psymatik Treatment Optimizer, to combine the side-effect databases with side-effect concerns of an individual user, to enable users to select side-effects of concern and the relative degree of concern for each side-effect. Concern weightings and the side-effect databases are synthesised via a multicriteria decision analysis method (technique for order of preference by similarity to ideal situation, or TOPSIS).
FINDINGS
Of 3724 citations, 14 articles containing 68 meta-analyses of individual side-effects met inclusion criteria. After review of 19 guidelines, seven provided ordinal data. Antipsychotic data were extracted from five studies (11 meta-analyses, n=65 594 patients) and four guidelines, and antidepressant data were extracted from three guidelines. The resultant databases included data on 32 antipsychotics (14 side-effects) and 37 antidepressants (nine side-effects). The databases highlighted the clinical dilemma associated with balancing side-effects, with avoidance of one side-effect (eg, weight gain for antipsychotics) increasing the risk of others (eg, akathisia). To aid with this dilemma, the Psymatik Treatment Optimizer synthesises the side-effect databases with individual user-defined concern weights. After computing up to 5851 pairwise comparisons for antidepressants and 5142 pairwise comparisons for antipsychotics, Psymatik ranks treatments in order of preference for the individual user, with the output presented in a heatmap.
INTERPRETATION
By facilitating collaborative, personalised, and evidence-based prescribing decisions, the side-effect databases and digital application supports care delivery that is consistent with international regulatory guidance for the treatment of schizophrenia and depression, and it therefore has promise for informing psychiatric practice and improving outcomes.
FUNDING
National Institute for Health and Care Research, Maudsley Charity, Wellcome Trust, Medical Research Council.
Topics: Adult; Humans; Adolescent; Antipsychotic Agents; Depressive Disorder, Major; Quality of Life; Antidepressive Agents; Schizophrenia
PubMed: 37774723
DOI: 10.1016/S2215-0366(23)00262-6 -
Revista Brasileira de Psiquiatria (Sao... 2023To determine the prevalence and correlates of treatment-resistant schizophrenia (TRS) through a systematic review and meta-analysis. (Meta-Analysis)
Meta-Analysis
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.
Topics: Humans; Antipsychotic Agents; Clozapine; Prevalence; Schizophrenia; Drug Resistance
PubMed: 37718484
DOI: 10.47626/1516-4446-2023-3126 -
JAMA Psychiatry Dec 2023Every third to sixth patient with medical diseases receives antidepressants, but regulatory trials typically exclude comorbid medical diseases. Meta-analyses of... (Meta-Analysis)
Meta-Analysis
IMPORTANCE
Every third to sixth patient with medical diseases receives antidepressants, but regulatory trials typically exclude comorbid medical diseases. Meta-analyses of antidepressants have shown small to medium effect sizes, but generalizability to clinical settings is unclear, where medical comorbidity is highly prevalent.
OBJECTIVE
To perform an umbrella systematic review of the meta-analytic evidence and meta-analysis of the efficacy and safety of antidepressant use in populations with medical diseases and comorbid depression.
DATA SOURCES
PubMed and EMBASE were searched from inception until March 31, 2023, for systematic reviews with or without meta-analyses of randomized clinical trials (RCTs) examining the efficacy and safety of antidepressants for treatment or prevention of comorbid depression in any medical disease.
STUDY SELECTION
Meta-analyses of placebo- or active-controlled RCTs studying antidepressants for depression in individuals with medical diseases.
DATA EXTRACTION AND SYNTHESIS
Data extraction and quality assessment using A Measurement Tool for the Assessment of Multiple Systematic Reviews (AMSTAR-2 and AMSTAR-Content) were performed by pairs of independent reviewers following PRISMA guidelines. When several meta-analyses studied the same medical disease, the largest meta-analysis was included. Random-effects meta-analyses pooled data on the primary outcome (efficacy), key secondary outcomes (acceptability and tolerability), and additional secondary outcomes (response and remission).
MAIN OUTCOMES AND MEASURES
Antidepressant efficacy presented as standardized mean differences (SMDs) and tolerability (discontinuation for adverse effects) and acceptability (all-cause discontinuation) presented as risk ratios (RRs).
RESULTS
Of 6587 references, 176 systematic reviews were identified in 43 medical diseases. Altogether, 52 meta-analyses in 27 medical diseases were included in the evidence synthesis (mean [SD] AMSTAR-2 quality score, 9.3 [3.1], with a maximum possible of 16; mean [SD] AMSTAR-Content score, 2.4 [1.9], with a maximum possible of 9). Across medical diseases (23 meta-analyses), antidepressants improved depression vs placebo (SMD, 0.42 [95% CI, 0.30-0.54]; I2 = 76.5%), with the largest SMDs for myocardial infarction (SMD, 1.38 [95% CI, 0.82-1.93]), functional chest pain (SMD, 0.87 [95% CI, 0.08-1.67]), and coronary artery disease (SMD, 0.83 [95% CI, 0.32-1.33]) and the smallest for low back pain (SMD, 0.06 [95% CI, 0.17-0.39]) and traumatic brain injury (SMD, 0.08 [95% CI, -0.28 to 0.45]). Antidepressants showed worse acceptability (24 meta-analyses; RR, 1.17 [95% CI, 1.02-1.32]) and tolerability (18 meta-analyses; RR, 1.39 [95% CI, 1.13-1.64]) compared with placebo. Antidepressants led to higher rates of response (8 meta-analyses; RR, 1.54 [95% CI, 1.14-1.94]) and remission (6 meta-analyses; RR, 1.43 [95% CI, 1.25-1.61]) than placebo. Antidepressants more likely prevented depression than placebo (7 meta-analyses; RR, 0.43 [95% CI, 0.33-0.53]).
CONCLUSIONS AND RELEVANCE
The results of this umbrella systematic review of meta-analyses found that antidepressants are effective and safe in treating and preventing depression in patients with comorbid medical disease. However, few large, high-quality RCTs exist in most medical diseases.
Topics: Humans; Antidepressive Agents; Comorbidity; Depression; Meta-Analysis as Topic; Systematic Reviews as Topic
PubMed: 37672261
DOI: 10.1001/jamapsychiatry.2023.2983