Relapse in clinically stable adult patients with schizophrenia or schizoaffective disorder: evidence-based criteria derived by equipercentile linking and diagnostic test accuracy meta-analysis

Background There is no consensus on defining relapse in schizophrenia, and scale-derived criteria with unclear clinical relevance are widely used. We aimed to develop an evidence-based scale-derived set of criteria to define relapse in patients with schizophrenia or schizoaffective disorder. Methods We searched the Yale University Open Data Access (YODA) for randomised controlled trials (RCTs) in clinically stable adults with schizophrenia or schizoaffective disorder, and obtained individual participant data on Positive and Negative Syndrome Scale (PANSS), Clinical Global Impression Severity (CGI-S), Personal and Social Performance (PSP), and Social and Occupational Functioning Assessment Scale (SOFAS). Our main outcomes were PANSS-derived criteria based on worsening in PANSS total score. We examined their relevance using equipercentile linking with CGI-S and functioning scales, and their test-performance in defining relapse with diagnostic test accuracy meta-analysis against CGI-S worsening (≥1-point increase together with a score ≥4 points) and psychiatric hospitalisation. Findings Based on data from seven RCTs (2354 participants; 1348 men [57·3%] and 1006 women [42·7%], mean age of 39·5 years [SD 12·0, range 17–89]; 303 Asian [12.9%], 255 Black [10.8%], 1665 White [70.7%], and other or unspecified 131 [5.6%]), an increase of 12 points or more in PANSS total (range 30–210 points) corresponded to clinically important deterioration in global severity of illness (≥1 point increase in CGI-S, range 1–7) and functioning (≥10 points decline in PSP or SOFAS, range 1–100). The interpretation of percentage changes varied importantly across different baseline scores. An increase of 12 points or more in PANSS total had good sensitivity and specificity using CGI-S as reference standard (sensitivity 82·1% [95% CI 77·1–86·4], specificity 86·9% [82·9–90·3]), as well as good sensitivity but lower specificity compared to hospitalisation (sensitivity 81·7% [74·1–87·7], specificity 69·2% [60·5–76·9]). Requiring either an increase in PANSS total or in specific items for positive and disorganization symptoms further improved test-performance. Cutoffs for situations where high sensitivity or specificity is needed are presented. Interpretation An increase of either 12 points or more in the PANSS total score, or worsening of specific positive and disorganisation symptom items could be a reasonable evidence-based definition of relapse in schizophrenia, potentially linking symptoms used to define remission and relapse. Percentage changes should not be used to define relapse because their interpretation depends on baseline scores. Funding German Research Foundation (grant number: 428509362)

Imputing the Number of Responders from the Mean and Standard Deviation of CGI-Improvement in Clinical Trials Investigating Medications for Autism Spectrum Disorder

Introduction: Response to treatment, according to Clinical Global Impression-Improvement (CGI-I) scale, is an easily interpretable outcome in clinical trials of autism spectrum disorder (ASD). Yet, the CGI-I rating is sometimes reported as a continuous outcome, and converting it to dichotomous would allow meta-analysis to incorporate more evidence. Methods: Clinical trials investigating medications for ASD and presenting both dichotomous and continuous CGI-I data were included. The number of patients with at least much improvement (CGI-I ≤ 2) were imputed from the CGI-I scale, assuming an underlying normal distribution of a latent continuous score using a primary threshold θ = 2.5 instead of θ = 2, which is the original cut-off in the CGI-I scale. The original and imputed values were used to calculate responder rates and odds ratios. The performance of the imputation method was investigated with a concordance correlation coefficient (CCC), linear regression, Bland–Altman plots, and subgroup differences of summary estimates obtained from random-effects meta-analysis. Results: Data from 27 studies, 58 arms, and 1428 participants were used. The imputation method using the primary threshold (θ = 2.5) had good performance for the responder rates (CCC = 0.93 95% confidence intervals [0.86, 0.96]; β of linear regression = 1.04 [0.95, 1.13]; bias and limits of agreements = 4.32% [−8.1%, 16.74%]; no subgroup differences χ(2) = 1.24, p-value = 0.266) and odds ratios (CCC = 0.91 [0.86, 0.96]; β = 0.96 [0.78, 1.14]; bias = 0.09 [−0.87, 1.04]; χ(2) = 0.02, p-value = 0.894). The imputation method had poorer performance when the secondary threshold (θ = 2) was used. Discussion: Assuming a normal distribution of the CGI-I scale, the number of responders could be imputed from the mean and standard deviation and used in meta-analysis. Due to the wide limits of agreement of the imputation method, sensitivity analysis excluding studies with imputed values should be performed

Estimating and visualising the trade-off between benefits and harms on multiple clinical outcomes in network meta-analysis.

BACKGROUND The relative treatment effects estimated from network meta-analysis can be employed to rank treatments from the most preferable to the least preferable option. These treatment hierarchies are typically based on ranking metrics calculated from a single outcome. Some approaches have been proposed in the literature to account for multiple outcomes and individual preferences, such as the coverage area inside a spie chart, that, however, does not account for a trade-off between efficacy and safety outcomes. We present the net-benefit standardised area within a spie chart, [Formula: see text] to explore the changes in treatment performance with different trade-offs between benefits and harms, according to a particular set of preferences. METHODS We combine the standardised areas within spie charts for efficacy and safety/acceptability outcomes with a value λ specifying the trade-off between benefits and harms. We derive absolute probabilities and convert outcomes on a scale between 0 and 1 for inclusion in the spie chart. RESULTS We illustrate how the treatments in three published network meta-analyses perform as the trade-off λ varies. The decrease of the [Formula: see text] quantity appears more pronounced for some drugs, e.g. haloperidol. Changes in treatment performance seem more frequent when SUCRA is employed as outcome measures in the spie charts. CONCLUSIONS [Formula: see text] should not be interpreted as a ranking metric but it is a simple approach that could help identify which treatment is preferable when multiple outcomes are of interest and trading-off between benefits and harms is important

Sharing information across patient subgroups to draw conclusions from sparse treatment networks

Network meta-analysis (NMA) usually provides estimates of the relative effects with the highest possible precision. However, sparse networks with few available studies and limited direct evidence can arise, threatening the robustness and reliability of NMA estimates. In these cases, the limited amount of available information can hamper the formal evaluation of the underlying NMA assumptions of transitivity and consistency. In addition, NMA estimates from sparse networks are expected to be imprecise and possibly biased as they rely on large sample approximations which are invalid in the absence of sufficient data. We propose a Bayesian framework that allows sharing of information between two networks that pertain to different population subgroups. Specifically, we use the results from a subgroup with a lot of direct evidence (a dense network) to construct informative priors for the relative effects in the target subgroup (a sparse network). This is a two-stage approach where at the first stage we extrapolate the results of the dense network to those expected from the sparse network. This takes place by using a modified hierarchical NMA model where we add a location parameter that shifts the distribution of the relative effects to make them applicable to the target population. At the second stage, these extrapolated results are used as prior information for the sparse network. We illustrate our approach through a motivating example of psychiatric patients. Our approach results in more precise and robust estimates of the relative effects and can adequately inform clinical practice in presence of sparse networks

Are the results of open randomised controlled trials comparing antipsychotic drugs in schizophrenia biased?:Exploratory meta- and subgroup analysis

A recent meta-epidemiological study did not reveal major differences between the results of blinded and open randomised-controlled trials (RCTs). Fewer patients may consent to double-blind RCTs than to open RCTs, compromising generalisability, making this question very important. However, the issue has not been addressed in schizophrenia. We used a database of randomised, acute-phase antipsychotic drug trials. Whenever at least one open and one blinded RCT was available for a comparison of two drugs, we contrasted the results by random-effects meta-analysis with subgroup tests. The primary outcome was overall symptoms as measured by the Positive and Negative Syndrome Scale, supplemented by seven secondary efficacy and side-effect outcomes. We also examined whether open RCTs were biased in favour of more recently introduced antipsychotics, less efficacious or more prone to side-effects antipsychotics, and pharmaceutical sponsors. 183 RCTs (155 blinded and 28 open) with 34715 participants comparing two active drugs were available. The results did not suggest general differences between open and blinded RCTs, which examined two active drugs. Only 12 out of 122 subgroup tests had a p-value below 0.1, four below 0.05, and if a Bonferroni correction for multiple tests had been applied, only one would have been significant. There were some exceptions which, however, did not always confirm the originally hypothesized direction of bias. Due to the relatively small number of open RCTs, our analysis is exploratory, but this fundamental question should be given more scientific attention. Currently, open RCTs should be excluded from meta-analyses, at least in sensitivity analyses.</p

Psychological and psychosocial interventions for treatment-resistant schizophrenia:a systematic review and network meta-analysis

BACKGROUND: Many patients with schizophrenia have symptoms that do not respond to antipsychotics. This condition is called treatment-resistant schizophrenia and has not received specific attention as opposed to general schizophrenia. Psychological and psychosocial interventions as an add-on treatment to pharmacotherapy could be useful, but their role and comparative efficacy to each other and to standard care in this population are not known. We investigated the efficacy, acceptability, and tolerability of psychological and psychosocial interventions for patients with treatment-resistant schizophrenia.METHODS: In this systematic review and network meta-analysis (NMA), we searched for published and unpublished randomised controlled trials (RCTs) through a systematic database search in BIOSIS, CINAHL, Embase, LILACS, MEDLINE, PsychInfo, ClinicalTrials.gov, and the WHO International Clinical Trials Registry Platform for articles published from inception up to Jan 31, 2020. We also searched the Cochrane Schizophrenia Group registry for studies published from inception up to March 31, 2022, and PubMed and Cochrane CENTRAL for studies published from inception up to July 31, 2023. We included RCTs that included patients with treatment-resistant schizophrenia. The primary outcome was overall symptoms. We did random-effects pairwise meta-analyses and NMAs to calculate standardised mean differences (SMDs) or risk ratios with 95% CIs. No people with lived experience were involved throughout the research process. The study protocol was registered in PROSPERO, CRD42022358696.FINDINGS: We identified 30 326 records, excluding 24 526 by title and abstract screening. 5762 full-text articles were assessed for eligibility, of which 5540 were excluded for not meeting the eligibility criteria, and 222 reports corresponding to 60 studies were included in the qualitative synthesis. Of these, 52 RCTs with 5034 participants (1654 [33·2%] females and 3325 [66·8%] males with sex indicated) comparing 20 psychological and psychosocial interventions provided data for the NMA. Mean age of participants was 38·05 years (range 23·10-48·50). We aimed to collect ethnicity data, but they were scarcely reported. According to the quality of evidence, cognitive behavioural therapy for psychosis (CBTp; SMD -0·22, 95% CI -0·35 to -0·09, 35 trials), virtual reality intervention (SMD -0·41, -0·79 to -0·02, four trials), integrated intervention (SMD -0·70, -1·18 to -0·22, three trials), and music therapy (SMD -1·27, -1·83 to -0·70, one study) were more efficacious than standard care in reducing overall symptoms. No indication of publication bias was identified.INTERPRETATION: We provide robust findings that CBTp can reduce the overall symptoms of patients with treatment-resistant schizophrenia, and therefore clinicians can prioritise this intervention in their clinical practice. Other psychological and psychosocial interventions showed promising results but need further investigation.FUNDING: DAAD-ASFE.</p

Non-invasive brain stimulation for treatment-resistant schizophrenia: protocol of a systematic review and network meta-analysis.

BACKGROUND Non-invasive brain stimulation (NIBS) is a promising intervention for treatment-resistant schizophrenia. However, there are multiple available techniques and a comprehensive synthesis of evidence is lacking. Thus, we will conduct a systematic review and network meta-analysis to investigate the comparative efficacy and safety of NIBS techniques as an add-on to antipsychotics for treatment-resistant schizophrenia. METHODS We will include single- and double-blind randomized-controlled trials (RCT) comparing any NIBS technique with each other or with a control intervention as an add-on to antipsychotics in adult patients with treatment-resistant schizophrenia. We will exclude studies focusing on predominant negative symptoms, maintenance treatment, and single sessions. The primary outcome will be a change in overall symptoms, and secondary outcomes will be a change in symptom domains, cognitive performance, quality of life, functioning, response, dropouts, and side effects. We will search for eligible studies in previous reviews, multiple electronic databases and clinical trial registries from inception onwards. At least two independent reviewers will perform the study selection, data extraction, and risk of bias assessment. We will measure the treatment differences using standardized mean difference (SMD) and odds ratio (OR) for continuous and dichotomous outcomes, respectively. We will conduct pairwise and network meta-analysis within a frequentist framework using a random-effects model, except for rare event outcomes where we will use a fixed-effects Mantel-Haenszel method. We will investigate potential sources of heterogeneity in subgroup analyses. Reporting bias will be assessed with funnel plots and the Risk of Bias due to Missing Evidence in Network meta-analysis (ROB-MEN) tool. The certainty in the evidence will be evaluated using the Confidence in Network Meta-analysis (CINeMA) approach. DISCUSSION Our network meta-analysis would provide an up-to-date synthesis of the evidence from all available RCTs on the comparative efficacy and safety of NIBS for treatment-resistant schizophrenia. This information could guide evidence-based clinical practice and improve the outcomes of patients. SYSTEMATIC REVIEW REGISTRATION PROSPERO-ID CRD42023410645

Antipsychotic drugs and their effects on cognitive function: protocol for a systematic review, pairwise, and network meta-analysis.

BACKGROUND There is evidence that antipsychotic drugs differ in their effect on the cognitive symptoms of schizophrenia. So far, there is no comprehensive systematic review available that would enable providers and patients to make informed choices regarding this important aspect of treatment. With a large number of substances available, conventional pairwise meta-analyses will not be sufficient to inform this choice. To fill this gap, we will conduct a network meta-analysis (NMA), integrating direct and indirect comparisons from randomized controlled trials (RCTs) to rank antipsychotics according to their effect on cognitive functioning. METHODS In our NMA, we will include RCTs in patients with schizophrenia or schizophrenia-like psychoses comparing one antipsychotic agent with another antipsychotic agent or placebo that measures cognitive function. We will include studies on patients of every age group, in any phase of illness (e.g., acute or stable, first episode or chronic schizophrenia, in- or outpatients) with an intervention time of at least 3 weeks. The primary outcome will be the composite score of cognitive functioning, preferentially measured with the test battery developed by the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) initiative. The secondary outcomes include the seven cognitive domains that the composite score is composed of, as well as functioning and quality of life. Study selection and data extraction will be conducted by at least two independent reviewers. We will use the Cochrane Risk of Bias tool 2 to determine the risk of bias in studies, and we will evaluate the confidence in the results using Confidence in Network Meta-Analysis (CINeMA). We will perform NMA using R (package netmeta). We will conduct subgroup and sensitivity analyses to explore the heterogeneity and assess the robustness of our findings. DISCUSSION This systematic review and network meta-analysis aims to inform evidence-based antipsychotic treatment choice for cognitive deficits in schizophrenia patients by analyzing existing RCTs on this subject. The results have the potential to support patients' and physicians' decision-making processes based on the latest available evidence. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42022312483

Pro-dopaminergic pharmacological interventions for anhedonia in depression: protocol for a living systematic review of human and non-human studies.

Background: Anhedonia is a key symptom of depression, and it has been suggested as a potential target for future individualised treatments. However, much is unknown about how interventions enhancing dopaminergic pathways may affect anhedonia symptoms in the context of depression. Methods: We will perform independent searches in multiple electronic databases to identify clinical and animal experimental studies on pro-dopaminergic interventions in individuals with depression or animal models for depression. The primary outcomes will be overall anhedonia symptoms and their behavioural proxies in animals. Secondary outcomes will include side effects and neurobiological measures. At least two independent reviewers will conduct the study selection, data extraction, and risk of bias assessments using pre-defined tools according to each record's study design. We will develop ontologies to facilitate study identification and data extraction. We will synthesise data from clinical and animal studies separately. If appropriate, we will use random-effects meta-analyses, or synthesis without meta-analyses. We will investigate study characteristics as potential sources of heterogeneity. We will evaluate the confidence in the evidence for each outcome and source of evidence, considering the summary of the association, potential concerns regarding internal and external validity, and reporting biases. When multiple sources of evidence are available for an outcome, we will draw an overall conclusion in a triangulation meeting involving a multidisciplinary team of experts. We plan updates of the review every 6 months, and any future modifications to the protocol will be documented. We will co-produce this review with multiple stakeholders. PROSPERO registration: CRD42023451821