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 METHODS: In this systematic review and network meta-analysis (NMA), we searched for published and unpublished randomised controlled trials (RCTs) through a systematic database search in BIOSIS, CINAHL, Embase, LILACS, MEDLINE, PsychInfo, ClinicalTrials.gov, and the WHO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.

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 that 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.

Estimating individualized treatment effects using an individual participant data meta-analysis.

BACKGROUND: One key aspect of personalized medicine is to identify individuals who benefit from an intervention. Some approaches have been developed to estimate individualized treatment effects (ITE) with a single randomized control trial (RCT) or observational data, but they are often underpowered for the ITE estimation. Using individual participant data meta-analyses (IPD-MA) might solve this problem. Few studies have investigated how to develop risk prediction models with IPD-MA, and it remains unclear how to combine those methods with approaches used for ITE estimation. In this article, we compared different approaches using both simulated and real data with binary and time-to-event outcomes to estimate the individualized treatment effects from an IPD-MA in a one-stage approach. METHODS: We compared five one-stage models: naive model (NA), random intercept (RI), stratified intercept (SI), rank-1 (R1), and fully stratified (FS), built with two different strategies, the S-learner and the T-learner constructed with a Monte Carlo simulation study in which we explored different scenarios with a binary or a time-to-event outcome. To evaluate the performance of the models, we used the c-statistic for benefit, the calibration of predictions, and the mean squared error. The different models were also used on the INDANA IPD-MA, comparing an anti-hypertensive treatment to no treatment or placebo ( N = 40 237 , 836 events). RESULTS: Simulation results showed that using the S-learner led to better ITE estimation performances for both binary and time-to-event outcomes. None of the risk models stand out and had significantly better results. For the INDANA dataset with a binary outcome, the naive and the random intercept models had the best performances. CONCLUSIONS: For the choice of the strategy, using interactions with treatment (the S-learner) is preferable. For the choice of the method, no approach is better than the other.

Synthesis methods used to combine observational studies and randomised trials in published meta-analyses.

BACKGROUND: This study examined the synthesis methods used in meta-analyses pooling data from observational studies (OSs) and randomised controlled trials (RCTs) from various medical disciplines. METHODS: We searched Medline via PubMed to identify reports of systematic reviews of interventions, including and pooling data from RCTs and OSs published in 110 high-impact factor general and specialised journals between 2015 and 2019. Screening and data extraction were performed in duplicate. To describe the synthesis methods used in the meta-analyses, we considered the first meta-analysis presented in each article. RESULTS: Overall, 132 reports were identified with a median number of included studies of 14 [9-26]. The median number of OSs was 6.5 [3-12] and that of RCTs was 3 [1-6]. The effect estimates recorded from OSs (i.e., adjusted or unadjusted) were not specified in 82% (n = 108) of the meta-analyses. An inverse-variance common-effect model was used in 2% (n = 3) of the meta-analyses, a random-effects model was used in 55% (n = 73), and both models were used in 40% (n = 53). A Poisson regression model was used in 1 meta-analysis, and 2 meta-analyses did not report the model they used. The mean total weight of OSs in the studied meta-analyses was 57.3% (standard deviation, ± 30.3%). Only 44 (33%) meta-analyses reported results stratified by study design. Of them, the results between OSs and RCTs had a consistent direction of effect in 70% (n = 31). Study design was explored as a potential source of heterogeneity in 79% of the meta-analyses, and confounding factors were investigated in only 10% (n = 13). Publication bias was assessed in 70% (n = 92) of the meta-analyses. Tau-square was reported in 32 meta-analyses with a median of 0.07 [0-0.30]. CONCLUSION: The inclusion of OSs in a meta-analysis on interventions could provide useful information. However, considerations of several methodological and conceptual aspects of OSs, that are required to avoid misleading findings, were often absent or insufficiently reported in our sample.

Comparison of effect estimates between preprints and peer-reviewed journal articles of COVID-19 trials.

BACKGROUND: Preprints are increasingly used to disseminate research results, providing multiple sources of information for the same study. We assessed the consistency in effect estimates between preprint and subsequent journal article of COVID-19 randomized controlled trials. METHODS: The study utilized data from the COVID-NMA living systematic review of pharmacological treatments for COVID-19 (covid-nma.com) up to July 20, 2022. We identified randomized controlled trials (RCTs) evaluating pharmacological treatments vs. standard of care/placebo for patients with COVID-19 that were originally posted as preprints and subsequently published as journal articles. Trials that did not report the same analysis in both documents were excluded. Data were extracted independently by pairs of researchers with consensus to resolve disagreements. Effect estimates extracted from the first preprint were compared to effect estimates from the journal article. RESULTS: The search identified 135 RCTs originally posted as a preprint and subsequently published as a journal article. We excluded 26 RCTs that did not meet the eligibility criteria, of which 13 RCTs reported an interim analysis in the preprint and a final analysis in the journal article. Overall, 109 preprint-article RCTs were included in the analysis. The median (interquartile range) delay between preprint and journal article was 121 (73-187) days, the median sample size was 150 (71-464) participants, 76% of RCTs had been prospectively registered, 60% received industry or mixed funding, 72% were multicentric trials. The overall risk of bias was rated as 'some concern' for 80% of RCTs. We found that 81 preprint-article pairs of RCTs were consistent for all outcomes reported. There were nine RCTs with at least one outcome with a discrepancy in the number of participants with outcome events or the number of participants analyzed, which yielded a minor change in the estimate of the effect. Furthermore, six RCTs had at least one outcome missing in the journal article and 14 RCTs had at least one outcome added in the journal article compared to the preprint. There was a change in the direction of effect in one RCT. No changes in statistical significance or conclusions were found. CONCLUSIONS: Effect estimates were generally consistent between COVID-19 preprints and subsequent journal articles. The main results and interpretation did not change in any trial. Nevertheless, some outcomes were added and deleted in some journal articles.

When does the placebo effect have an impact on network meta-analysis results?

The placebo effect is the 'effect of the simulation of treatment that occurs due to a participant's belief or expectation that a treatment is effective'. Although the effect might be of little importance for some conditions, it can have a great role in others, mostly when the evaluated symptoms are subjective. Several characteristics that include informed consent, number of arms in a study, the occurrence of adverse events and quality of blinding may influence response to placebo and possibly bias the results of randomised controlled trials. Such a bias is inherited in systematic reviews of evidence and their quantitative components, pairwise meta-analysis (when two treatments are compared) and network meta-analysis (when more than two treatments are compared). In this paper, we aim to provide red flags as to when a placebo effect is likely to bias pairwise and network meta-analysis treatment effects. The classic paradigm has been that placebo-controlled randomised trials are focused on estimating the treatment effect. However, the magnitude of placebo effect itself may also in some instances be of interest and has also lately received attention. We use component network meta-analysis to estimate placebo effects. We apply these methods to a published network meta-analysis, examining the relative effectiveness of four psychotherapies and four control treatments for depression in 123 studies.

No evidence of important difference in summary treatment effects between COVID-19 preprints and peer-reviewed publications: a meta-epidemiological study.

OBJECTIVES: Preprints became a major source of research communication during the COVID-19 pandemic. We aimed to evaluate whether summary treatment effect estimates differ between preprint and peer-reviewed journal trials. STUDY DESIGN AND SETTING: A meta-epidemiological study. Data were derived from the COVID-NMA living systematic review (covid-nma.com) up to July 20, 2022. We identified all meta-analyses evaluating pharmacological treatments vs. standard of care or placebo for patients with COVID-19 that included at least one preprint and one peer-reviewed journal article. Difference in effect estimates between preprint and peer-reviewed journal trials were estimated by the ratio of odds ratio (ROR); ROR <1 indicated larger effects in preprint trials. RESULTS: Thirty-seven meta-analyses including 114 trials (44 preprints and 70 peer-reviewed publications) were selected. The median number of randomized controlled trials (RCTs) per meta-analysis was 2 (interquartile range [IQR], 2-4; maximum, 11), median sample size of RCTs was 199 (IQR, 99-478). Overall, there was no statistically significant difference in summary effect estimates between preprint and peer-reviewed journal trials (ROR, 0.88; 95% CI, 0.71-1.09; I2 = 17.8%; τ2 = 0.06). CONCLUSION: We did not find an important difference between summary treatment effects of preprints and summary treatment effects of peer-reviewed publications. Systematic reviewers and guideline developers should assess preprint inclusion individually, accounting for risk of bias and completeness of reporting.

Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.

BACKGROUND: Psoriasis is an immune-mediated disease with either skin or joints manifestations, or both, and it has a major impact on quality of life. Although there is currently no cure for psoriasis, various treatment strategies allow sustained control of disease signs and symptoms. The relative benefit of these treatments remains unclear due to the limited number of trials comparing them directly head-to-head, which is why we chose to conduct a network meta-analysis. OBJECTIVES: To compare the benefits and harms of non-biological systemic agents, small molecules, and biologics for people with moderate-to-severe psoriasis using a network meta-analysis, and to provide a ranking of these treatments according to their benefits and harms. SEARCH METHODS: For this update of the living systematic review, we updated our searches of the following databases monthly to October 2022: the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, and Embase. SELECTION CRITERIA: Randomised controlled trials (RCTs) of systemic treatments in adults over 18 years with moderate-to-severe plaque psoriasis, at any stage of treatment, compared to placebo or another active agent. The primary outcomes were: proportion of participants who achieved clear or almost clear skin, that is, at least Psoriasis Area and Severity Index (PASI) 90; proportion of participants with serious adverse events (SAEs) at induction phase (8 to 24 weeks after randomisation). DATA COLLECTION AND ANALYSIS: We conducted duplicate study selection, data extraction, risk of bias assessment, and analyses. We synthesised data using pairwise and network meta-analysis (NMA) to compare treatments and rank them according to effectiveness (PASI 90 score) and acceptability (inverse of SAEs). We assessed the certainty of NMA evidence for the two primary outcomes and all comparisons using CINeMA, as very low, low, moderate, or high. We contacted study authors when data were unclear or missing. We used the surface under the cumulative ranking curve (SUCRA) to infer treatment hierarchy, from 0% (worst for effectiveness or safety) to 100% (best for effectiveness or safety). MAIN RESULTS: This update includes an additional 12 studies, taking the total number of included studies to 179, and randomised participants to 62,339, 67.1% men, mainly recruited from hospitals. Average age was 44.6 years, mean PASI score at baseline was 20.4 (range: 9.5 to 39). Most studies were placebo-controlled (56%). We assessed a total of 20 treatments. Most (152) trials were multicentric (two to 231 centres). One-third of the studies (65/179) had high risk of bias, 24 unclear risk, and most (90) low risk. Most studies (138/179) declared funding by a pharmaceutical company, and 24 studies did not report a funding source. Network meta-analysis at class level showed that all interventions (non-biological systemic agents, small molecules, and biological treatments) showed a higher proportion of patients reaching PASI 90 than placebo. Anti-IL17 treatment showed a higher proportion of patients reaching PASI 90 compared to all the interventions. Biologic treatments anti-IL17, anti-IL12/23, anti-IL23, and anti-TNF alpha showed a higher proportion of patients reaching PASI 90 than the non-biological systemic agents. For reaching PASI 90, the most effective drugs when compared to placebo were (SUCRA rank order, all high-certainty evidence): infliximab (risk ratio (RR) 49.16, 95% CI 20.49 to 117.95), bimekizumab (RR 27.86, 95% CI 23.56 to 32.94), ixekizumab (RR 27.35, 95% CI 23.15 to 32.29), risankizumab (RR 26.16, 95% CI 22.03 to 31.07). Clinical effectiveness of these drugs was similar when compared against each other. Bimekizumab and ixekizumab were significantly more likely to reach PASI 90 than secukinumab. Bimekizumab, ixekizumab, and risankizumab were significantly more likely to reach PASI 90 than brodalumab and guselkumab. Infliximab, anti-IL17 drugs (bimekizumab, ixekizumab, secukinumab, and brodalumab), and anti-IL23 drugs except tildrakizumab were significantly more likely to reach PASI 90 than ustekinumab, three anti-TNF alpha agents, and deucravacitinib. Ustekinumab was superior to certolizumab. Adalimumab, tildrakizumab, and ustekinumab were superior to etanercept. No significant difference was shown between apremilast and two non-biological drugs: ciclosporin and methotrexate. We found no significant difference between any of the interventions and the placebo for the risk of SAEs. The risk of SAEs was significantly lower for participants on methotrexate compared with most of the interventions. Nevertheless, the SAE analyses were based on a very low number of events with very low- to moderate-certainty evidence for all the comparisons. The findings therefore have to be viewed with caution. For other efficacy outcomes (PASI 75 and Physician Global Assessment (PGA) 0/1), the results were similar to the results for PASI 90. Information on quality of life was often poorly reported and was absent for several of the interventions. AUTHORS' CONCLUSIONS: Our review shows that, compared to placebo, the biologics infliximab, bimekizumab, ixekizumab, and risankizumab were the most effective treatments for achieving PASI 90 in people with moderate-to-severe psoriasis on the basis of high-certainty evidence. This NMA evidence is limited to induction therapy (outcomes measured from 8 to 24 weeks after randomisation), and is not sufficient for evaluating longer-term outcomes in this chronic disease. Moreover, we found low numbers of studies for some of the interventions, and the young age (mean 44.6 years) and high level of disease severity (PASI 20.4 at baseline) may not be typical of patients seen in daily clinical practice. We found no significant difference in the assessed interventions and placebo in terms of SAEs, and the safety evidence for most interventions was very low to moderate quality. More randomised trials directly comparing active agents are needed, and these should include systematic subgroup analyses (sex, age, ethnicity, comorbidities, psoriatic arthritis). To provide long-term information on the safety of treatments included in this review, an evaluation of non-randomised studies is needed. Editorial note: This is a living systematic review. Living systematic reviews offer a new approach to review updating, in which the review is continually updated, incorporating relevant new evidence as it becomes available. Please refer to the Cochrane Database of Systematic Reviews for the current status of this review.

Interleukin-6 blocking agents for treating COVID-19: a living systematic review.

BACKGROUND: It has been reported that people with COVID-19 and pre-existing autoantibodies against type I interferons are likely to develop an inflammatory cytokine storm responsible for severe respiratory symptoms. Since interleukin 6 (IL-6) is one of the cytokines released during this inflammatory process, IL-6 blocking agents have been used for treating people with severe COVID-19. OBJECTIVES: To update the evidence on the effectiveness and safety of IL-6 blocking agents compared to standard care alone or to a placebo for people with COVID-19. SEARCH METHODS: We searched the World Health Organization (WHO) International Clinical Trials Registry Platform, the Living OVerview of Evidence (L·OVE) platform, and the Cochrane COVID-19 Study Register to identify studies on 7 June 2022. SELECTION CRITERIA: We included randomized controlled trials (RCTs) evaluating IL-6 blocking agents compared to standard care alone or to placebo for people with COVID-19, regardless of disease severity. DATA COLLECTION AND ANALYSIS: Pairs of researchers independently conducted study selection, extracted data and assessed risk of bias. We assessed the certainty of evidence using the GRADE approach for all critical and important outcomes. In this update we amended our protocol to update the methods used for grading evidence by establishing minimal important differences for the critical outcomes. MAIN RESULTS: This update includes 22 additional trials, for a total of 32 trials including 12,160 randomized participants all hospitalized for COVID-19 disease. We identified a further 17 registered RCTs evaluating IL-6 blocking agents without results available as of 7 June 2022.  The mean age range varied from 56 to 75 years; 66.2% (8051/12,160) of enrolled participants were men. One-third (11/32) of included trials were placebo-controlled. Twenty-two were published in peer-reviewed journals, three were reported as preprints, two trials had results posted only on registries, and results from five trials were retrieved from another meta-analysis. Eight were funded by pharmaceutical companies.  Twenty-six included studies were multicenter trials; four were multinational and 22 took place in single countries. Recruitment of participants occurred between February 2020 and June 2021, with a mean enrollment duration of 21 weeks (range 1 to 54 weeks). Nineteen trials (60%) had a follow-up of 60 days or more. Disease severity ranged from mild to critical disease. The proportion of participants who were intubated at study inclusion also varied from 5% to 95%. Only six trials reported vaccination status; there were no vaccinated participants included in these trials, and 17 trials were conducted before vaccination was rolled out. We assessed a total of six treatments, each compared to placebo or standard care. Twenty trials assessed tocilizumab, nine assessed sarilumab, and two assessed clazakizumab. Only one trial was included for each of the other IL-6 blocking agents (siltuximab, olokizumab, and levilimab). Two trials assessed more than one treatment. Efficacy and safety of tocilizumab and sarilumab compared to standard care or placebo for treating COVID-19 At day (D) 28, tocilizumab and sarilumab probably result in little or no increase in clinical improvement (tocilizumab: risk ratio (RR) 1.05, 95% confidence interval (CI) 1.00 to 1.11; 15 RCTs, 6116 participants; moderate-certainty evidence; sarilumab: RR 0.99, 95% CI 0.94 to 1.05; 7 RCTs, 2425 participants; moderate-certainty evidence). For clinical improvement at ≥ D60, the certainty of evidence is very low for both tocilizumab (RR 1.10, 95% CI 0.81 to 1.48; 1 RCT, 97 participants; very low-certainty evidence) and sarilumab (RR 1.22, 95% CI 0.91 to 1.63; 2 RCTs, 239 participants; very low-certainty evidence). The effect of tocilizumab on the proportion of participants with a WHO Clinical Progression Score (WHO-CPS) of level 7 or above remains uncertain at D28 (RR 0.90, 95% CI 0.72 to 1.12; 13 RCTs, 2117 participants; low-certainty evidence) and that for sarilumab very uncertain (RR 1.10, 95% CI 0.90 to 1.33; 5 RCTs, 886 participants; very low-certainty evidence). Tocilizumab reduces all cause-mortality at D28 compared to standard care/placebo (RR 0.88, 95% CI 0.81 to 0.94; 18 RCTs, 7428 participants; high-certainty evidence). The evidence about the effect of sarilumab on this outcome is very uncertain (RR 1.06, 95% CI 0.86 to 1.30; 9 RCTs, 3305 participants; very low-certainty evidence). The evidence is uncertain for all cause-mortality at ≥ D60 for tocilizumab (RR 0.91, 95% CI 0.80 to 1.04; 9 RCTs, 2775 participants; low-certainty evidence) and very uncertain for sarilumab (RR 0.95, 95% CI 0.84 to 1.07; 6 RCTs, 3379 participants; very low-certainty evidence). Tocilizumab probably results in little to no difference in the risk of adverse events (RR 1.03, 95% CI 0.95 to 1.12; 9 RCTs, 1811 participants; moderate-certainty evidence). The evidence about adverse events for sarilumab is uncertain (RR 1.12, 95% CI 0.97 to 1.28; 4 RCT, 860 participants; low-certainty evidence).  The evidence about serious adverse events is very uncertain for tocilizumab (RR 0.93, 95% CI 0.81 to 1.07; 16 RCTs; 2974 participants; very low-certainty evidence) and uncertain for sarilumab (RR 1.09, 95% CI 0.97 to 1.21; 6 RCTs; 2936 participants; low-certainty evidence). Efficacy and safety of clazakizumab, olokizumab, siltuximab and levilimab compared to standard care or placebo for treating COVID-19 The evidence about the effects of clazakizumab, olokizumab, siltuximab, and levilimab comes from only one or two studies for each blocking agent, and is uncertain or very uncertain. AUTHORS' CONCLUSIONS: In hospitalized people with COVID-19, results show a beneficial effect of tocilizumab on all-cause mortality in the short term and probably little or no difference in the risk of adverse events compared to standard care alone or placebo. Nevertheless, both tocilizumab and sarilumab probably result in little or no increase in clinical improvement at D28. Evidence for an effect of sarilumab and the other IL-6 blocking agents on critical outcomes is uncertain or very uncertain. Most of the trials included in our review were done before the waves of different variants of concern and before vaccination was rolled out on a large scale. An additional 17 RCTs of IL-6 blocking agents are currently registered with no results yet reported. The number of pending studies and the number of participants planned is low. Consequently, we will not publish further updates of this review.

Heterogeneity of design features in studies included in systematic reviews with meta-analysis of cognitive outcomes in children born very preterm.

BACKGROUND: Meta-analyses of the voluminous scientific literature on the impact of very preterm (VPT, <32 weeks' gestation) birth on cognition find a marked deficit in intelligence quotient (IQ) among children born VPT relative to term-born peers, but with unexplained between-study heterogeneity in effect size. OBJECTIVES: To conduct an umbrella review to describe the design and methodology of primary studies and to assess whether methodological heterogeneity affects the results of meta-analyses. DATA SOURCES: Primary studies from five systematic reviews with meta-analysis on VPT birth and childhood IQ. STUDY SELECTION AND DATA EXTRACTION: Information on study design, sample characteristics and results was extracted from studies. Study features covered study type, sample size, follow-up rates, adjustment for social context, management of severe impairments and test type. SYNTHESIS: We used random-effects subgroup meta-analyses and meta-regressions to investigate the contribution of study features to between-study variance in standardised mean differences (SMD) in IQ between groups. RESULTS: In 58 cohorts (56%), children with severe impairments were excluded, while 23 (22%) cohorts accounted for social factors. The least reported feature was the follow-up rate (missing in 38 cohorts). The largest difference in SMDs was between studies using full scale IQ tests (61 cohorts, SMD -0.89, 95% CI -0.96, -0.82) versus short-form tests (27 cohorts, SMD -0.68, 95% CI -0.79, -0.57). The proportion of between-study variance explained by the type of test was 14%; the other features explained less than 1% of the variance. CONCLUSIONS: Study design and methodology varied across studies, but most of them did not affect the variance in effect size, except the type of cognitive test. Key features, such as the follow-up rate, were not consistently reported limiting the evaluation of their potential contribution. Incomplete reporting limited the evaluation of the full impact of this methodological diversity.

Empirical evaluation of the methods used in systematic reviews including observational studies and randomized trials.

OBJECTIVES: To examine the methodological characteristics of systematic reviews and meta-analyses including observational studies (OSs) and randomized controlled trials (RCTs), in various medical disciplines. STUDY DESIGN AND SETTING: We searched Medline via PubMed to identify systematic reviews of interventions including RCTs and OSs published in 110 journals from 2015 to 2019. We extracted in duplicate general and methodological characteristics of the systematic review. RESULTS: We identified 402 systematic reviews. Only 39% (n = 160) of them reported the availability of a pre-established protocol. A rationale for including observational data in the systematic review was clearly reported in 25% (n = 102) of the systematic reviews. Thirty two percent (n = 130) of the reviews reported a search strategy intending to identify published and unpublished data for RCTs and OSs. The risk of bias of the individual studies was assessed in 89% (n = 359) of the systematic reviews. In 74% (n = 266) it was assessed for both RCTs and OSs; 180 (50%) used different tools. Information about confounding factors was reported in only 11% of systematic reviews and the type of effect estimates (crude or adjusted) used was specified in only 22% of the systematic reviews. Among the 385 systematic reviews that performed data synthesis, only 132 (33%) pooled OSs and RCTs in the same meta-analysis. CONCLUSION: Including OSs in systematic reviews of interventions could provide useful information but such an approach could also be misleading; thus, several methodological details are needed to ensure appropriate handling of OS and valid results. Our study revealed, although, that substantial methodological information is missing in reports published in high-impact factor general and specialty journals.

metaCOVID: A web-application for living meta-analyses of COVID-19 trials.

Outputs from living evidence syntheses projects have been used widely during the pandemic by guideline developers to form evidence-based recommendations. However, the needs of different stakeholders cannot be accommodated by solely providing pre-defined non amendable numerical summaries. Stakeholders also need to understand the data and perform their own exploratory analyses. This requires resources, time, statistical expertise, software knowledge as well as relevant clinical expertise to avoid spurious conclusions. To assist them, we created the metaCOVID application which, based on automation processes, facilitates the fast exploration of the data and the conduct of sub-analyses tailored to end-users needs. metaCOVID has been created in R and is freely available as an R-Shiny application. Based on the COVID-NMA platform (https://covid-nma.com/) the application conducts living meta-analyses of randomized controlled trials related to COVID-19 treatments and vaccines for several outcomes. Several options are available for subgroup and sensitivity analyses. The results are presented in downloadable forest plots. We illustrate metaCOVID through three examples involving well-known treatments and vaccines for COVID-19. The application is freely available from https://covid-nma.com/metacovid/.

Considering multiple outcomes with different weights informed the hierarchy of interventions in network meta-analysis.

OBJECTIVES: Ranking metrics in network meta-analysis (NMA) are computed separately for each outcome. Our aim is to 1) present graphical ways to group competing interventions considering multiple outcomes and 2) use conjoint analysis for placing weights on the various outcomes based on the stakeholders' preferences. STUDY DESIGN AND SETTING: We used multidimensional scaling (MDS) and hierarchical tree clustering to visualize the extent of similarity of interventions in terms of the relative effects they produce through a random effect NMA. We reanalyzed a published network of 212 psychosis trials taking three outcomes into account as follows: reduction in symptoms of schizophrenia, all-cause treatment discontinuation, and weight gain. RESULTS: Conjoint analysis provides a mathematical method to transform judgements into weights that can be subsequently used to visually represent interventions on a two-dimensional plane or through a dendrogram. These plots provide insightful information about the clustering of interventions. CONCLUSION: Grouping interventions can help decision makers not only to identify the optimal ones in terms of benefit-risk balance but also choose one from the best cluster based on other grounds, such as cost, implementation etc. Placing weights on outcomes allows considering patient profile or preferences.

Efficacy and safety of COVID-19 vaccines.

BACKGROUND: Different forms of vaccines have been developed to prevent the SARS-CoV-2 virus and subsequent COVID-19 disease. Several are in widespread use globally.  OBJECTIVES: To assess the efficacy and safety of COVID-19 vaccines (as a full primary vaccination series or a booster dose) against SARS-CoV-2. SEARCH METHODS: We searched the Cochrane COVID-19 Study Register and the COVID-19 L·OVE platform (last search date 5 November 2021). We also searched the WHO International Clinical Trials Registry Platform, regulatory agency websites, and Retraction Watch. SELECTION CRITERIA: We included randomized controlled trials (RCTs) comparing COVID-19 vaccines to placebo, no vaccine, other active vaccines, or other vaccine schedules. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. We used GRADE to assess the certainty of evidence for all except immunogenicity outcomes.  We synthesized data for each vaccine separately and presented summary effect estimates with 95% confidence intervals (CIs).  MAIN RESULTS: We included and analyzed 41 RCTs assessing 12 different vaccines, including homologous and heterologous vaccine schedules and the effect of booster doses. Thirty-two RCTs were multicentre and five were multinational. The sample sizes of RCTs were 60 to 44,325 participants. Participants were aged: 18 years or older in 36 RCTs; 12 years or older in one RCT; 12 to 17 years in two RCTs; and three to 17 years in two RCTs. Twenty-nine RCTs provided results for individuals aged over 60 years, and three RCTs included immunocompromized patients. No trials included pregnant women. Sixteen RCTs had two-month follow-up or less, 20 RCTs had two to six months, and five RCTs had greater than six to 12 months or less. Eighteen reports were based on preplanned interim analyses. Overall risk of bias was low for all outcomes in eight RCTs, while 33 had concerns for at least one outcome. We identified 343 registered RCTs with results not yet available.  This abstract reports results for the critical outcomes of confirmed symptomatic COVID-19, severe and critical COVID-19, and serious adverse events only for the 10 WHO-approved vaccines. For remaining outcomes and vaccines, see main text. The evidence for mortality was generally sparse and of low or very low certainty for all WHO-approved vaccines, except AD26.COV2.S (Janssen), which probably reduces the risk of all-cause mortality (risk ratio (RR) 0.25, 95% CI 0.09 to 0.67; 1 RCT, 43,783 participants; high-certainty evidence). Confirmed symptomatic COVID-19 High-certainty evidence found that BNT162b2 (BioNtech/Fosun Pharma/Pfizer), mRNA-1273 (ModernaTx), ChAdOx1 (Oxford/AstraZeneca), Ad26.COV2.S, BBIBP-CorV (Sinopharm-Beijing), and BBV152 (Bharat Biotect) reduce the incidence of symptomatic COVID-19 compared to placebo (vaccine efficacy (VE): BNT162b2: 97.84%, 95% CI 44.25% to 99.92%; 2 RCTs, 44,077 participants; mRNA-1273: 93.20%, 95% CI 91.06% to 94.83%; 2 RCTs, 31,632 participants; ChAdOx1: 70.23%, 95% CI 62.10% to 76.62%; 2 RCTs, 43,390 participants; Ad26.COV2.S: 66.90%, 95% CI 59.10% to 73.40%; 1 RCT, 39,058 participants; BBIBP-CorV: 78.10%, 95% CI 64.80% to 86.30%; 1 RCT, 25,463 participants; BBV152: 77.80%, 95% CI 65.20% to 86.40%; 1 RCT, 16,973 participants). Moderate-certainty evidence found that NVX-CoV2373 (Novavax) probably reduces the incidence of symptomatic COVID-19 compared to placebo (VE 82.91%, 95% CI 50.49% to 94.10%; 3 RCTs, 42,175 participants). There is low-certainty evidence for CoronaVac (Sinovac) for this outcome (VE 69.81%, 95% CI 12.27% to 89.61%; 2 RCTs, 19,852 participants). Severe or critical COVID-19 High-certainty evidence found that BNT162b2, mRNA-1273, Ad26.COV2.S, and BBV152 result in a large reduction in incidence of severe or critical disease due to COVID-19 compared to placebo (VE: BNT162b2: 95.70%, 95% CI 73.90% to 99.90%; 1 RCT, 46,077 participants; mRNA-1273: 98.20%, 95% CI 92.80% to 99.60%; 1 RCT, 28,451 participants; AD26.COV2.S: 76.30%, 95% CI 57.90% to 87.50%; 1 RCT, 39,058 participants; BBV152: 93.40%, 95% CI 57.10% to 99.80%; 1 RCT, 16,976 participants). Moderate-certainty evidence found that NVX-CoV2373 probably reduces the incidence of severe or critical COVID-19 (VE 100.00%, 95% CI 86.99% to 100.00%; 1 RCT, 25,452 participants). Two trials reported high efficacy of CoronaVac for severe or critical disease with wide CIs, but these results could not be pooled. Serious adverse events (SAEs) mRNA-1273, ChAdOx1 (Oxford-AstraZeneca)/SII-ChAdOx1 (Serum Institute of India), Ad26.COV2.S, and BBV152 probably result in little or no difference in SAEs compared to placebo (RR: mRNA-1273: 0.92, 95% CI 0.78 to 1.08; 2 RCTs, 34,072 participants; ChAdOx1/SII-ChAdOx1: 0.88, 95% CI 0.72 to 1.07; 7 RCTs, 58,182 participants; Ad26.COV2.S: 0.92, 95% CI 0.69 to 1.22; 1 RCT, 43,783 participants); BBV152: 0.65, 95% CI 0.43 to 0.97; 1 RCT, 25,928 participants). In each of these, the likely absolute difference in effects was fewer than 5/1000 participants. Evidence for SAEs is uncertain for BNT162b2, CoronaVac, BBIBP-CorV, and NVX-CoV2373 compared to placebo (RR: BNT162b2: 1.30, 95% CI 0.55 to 3.07; 2 RCTs, 46,107 participants; CoronaVac: 0.97, 95% CI 0.62 to 1.51; 4 RCTs, 23,139 participants; BBIBP-CorV: 0.76, 95% CI 0.54 to 1.06; 1 RCT, 26,924 participants; NVX-CoV2373: 0.92, 95% CI 0.74 to 1.14; 4 RCTs, 38,802 participants). For the evaluation of heterologous schedules, booster doses, and efficacy against variants of concern, see main text of review. AUTHORS' CONCLUSIONS: Compared to placebo, most vaccines reduce, or likely reduce, the proportion of participants with confirmed symptomatic COVID-19, and for some, there is high-certainty evidence that they reduce severe or critical disease. There is probably little or no difference between most vaccines and placebo for serious adverse events. Over 300 registered RCTs are evaluating the efficacy of COVID-19 vaccines, and this review is updated regularly on the COVID-NMA platform (covid-nma.com). Implications for practice Due to the trial exclusions, these results cannot be generalized to pregnant women, individuals with a history of SARS-CoV-2 infection, or immunocompromized people. Most trials had a short follow-up and were conducted before the emergence of variants of concern. Implications for research Future research should evaluate the long-term effect of vaccines, compare different vaccines and vaccine schedules, assess vaccine efficacy and safety in specific populations, and include outcomes such as preventing long COVID-19. Ongoing evaluation of vaccine efficacy and effectiveness against emerging variants of concern is also vital.

Comparative efficacy, cognitive effects and acceptability of electroconvulsive therapies for the treatment of depression: protocol for a systematic review and network meta-analysis.

INTRODUCTION: There have been important advances in the use of electroconvulsive therapy (ECT) to treat major depressive episodes. These include variations to the type of stimulus the brain regions stimulated, and the stimulus parameters (eg, stimulus duration/pulse width). Our aim is to investigate ECT types using a network meta-analysis (NMA) approach and report on comparative treatment efficacy, cognitive side effects and acceptability. METHOD: We will conduct a systematic review to identify randomised controlled trials that compared two or more ECT protocols to treat depression. This will be done using the following databases: Embase, MEDLINE PubMed, Web of Science, Scopus, PsycINFO, Cochrane CENTRAL and will be supplemented by personal contacts with researchers in the field. All authors will be contacted to provide missing information. Primary outcomes will be symptom severity on a validated continuous clinician-rated scale of depression, cognitive functioning measured using anterograde verbal recall, and acceptability calculated using all-cause drop-outs. Secondary outcomes will include response and remission rates, autobiographical memory following a course of ECT, and anterograde visuospatial recall.Bayesian random effects hierarchical models will compare ECT types. Additional meta-regressions may be conducted to determine the impact of effect modifiers and patient-specific prognostic factors if sufficient data are available. DISCUSSION: This NMA will facilitate clinician decision making and allow more sophisticated selection of ECT type according to the balance of efficacy, cognitive side effects and acceptability. ETHICS: This systematic review and NMA does not require research ethics approval as it will use published aggregate data and will not collect nor disclose individually identifiable participant data. PROSPERO REGISTRATION NUMBER: CRD42022357098.

The response of subgroups of patients with schizophrenia to different antipsychotic drugs: a systematic review and meta-analysis.

BACKGROUND: As comparatively few trials in subgroups of patients with schizophrenia have been done, clinicians need to know whether they can rely on the results of randomised controlled trials (RCTs) in the general population of patients with schizophrenia. We aimed to compare the efficacy and side-effects of antipsychotic drugs in different subgroups. METHODS: In this systematic review and meta-analysis, we searched reference lists of previous systematic reviews and meta-analyses, the Cochrane Schizophrenia Group's Study-Based Register (from database inception to April 27, 2020), and PubMed (from April 1, 2020 to June 14, 2021). We excluded studies in patients with stable schizophrenia (ie, relapse prevention studies), studies with a high risk of bias, and studies from mainland China due to quality concerns concerning allocation and masking methods. We included single-blind RCTs or better that assessed one or more of 16 second-generation and 18 first-generation antipsychotics in the general population of patients with schizophrenia or in one or more of the subgroups: children and adolescents (age range as defined in the original studies), patients with a first episode, patients with predominant or prominent negative symptoms, patients with comorbid substance use, patients with treatment-resistant schizophrenia, or older patients (age range as defined in the original studies). Two authors independently screened the results of the search, retrieved full-text articles, and checked the inclusion criteria. Using the Preferred Reporting Items for Systematic Reviews and Meta-analyses guideline, all parameters were extracted in duplicate. The primary outcome was change in overall symptoms. We compared drug efficacy between subgroups, by sex, schizoaffective disorder versus schizophrenia, and study origin using random-effects, inverse variance meta-analyses and random-effects subgroup tests, and meta-regression. FINDINGS: We included 537 RCTs with 76 382 participants, 26 627 (34·9%) women, 49 755 (65·1%) men, mean age 37·3 years (range of means 7·9-80·2; ethnicity data not available). 412 RCTs included patients in the general population of patients with schizophrenia, 42 included patients with treatment-resistant schizophrenia, 25 included children and adolescents, 20 included patients with their first episode, 20 included patients with predominant or prominent negative symptoms, 13 included patients with comorbid substance use, and 11 included older patients. Of 507 random-effects subgroup tests done, 46 (9%) showed a significant difference (p<0·05) between subgroups, but there was no clear indication as to which drug should be used in which subgroup. INTERPRETATION: The effects of antipsychotics in various patient subgroups were usually similar to those in the general population of patients with schizophrenia, but comparably few studies contributed to the subgroups, in particular in terms of side-effects. If the evidence for treatment in a given subgroup is small, guideline makers and clinicians should consider using the results in the much better studied group of the general population of patients with schizophrenia. FUNDING: German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung; FKZ 01KG1508).

Network meta-analysis of rare events using penalized likelihood regression.

Network meta-analysis (NMA) of rare events has attracted little attention in the literature. Until recently, networks of interventions with rare events were analyzed using the inverse-variance NMA approach. However, when events are rare the normal approximations made by this model can be poor and effect estimates are potentially biased. Other methods for the synthesis of such data are the recent extension of the Mantel-Haenszel approach to NMA or the use of the noncentral hypergeometric distribution. In this article, we suggest a new common-effect NMA approach that can be applied even in networks of interventions with extremely low or even zero number of events without requiring study exclusion or arbitrary imputations. Our method is based on the implementation of the penalized likelihood function proposed by Firth for bias reduction of the maximum likelihood estimate to the logistic expression of the NMA model. A limitation of our method is that heterogeneity cannot be taken into account as an additive parameter as in most meta-analytical models. However, we account for heterogeneity by incorporating a multiplicative overdispersion term using a two-stage approach. We show through simulation that our method performs consistently well across all tested scenarios and most often results in smaller bias than other available methods. We also illustrate the use of our method through two clinical examples. We conclude that our "penalized likelihood NMA" approach is promising for the analysis of binary outcomes with rare events especially for networks with very few studies per comparison and very low control group risks.

Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.

BACKGROUND: Psoriasis is an immune-mediated disease with either skin or joints manifestations, or both, and it has a major impact on quality of life. Although there is currently no cure for psoriasis, various treatment strategies allow sustained control of disease signs and symptoms. The relative benefit of these treatments remains unclear due to the limited number of trials comparing them directly head-to-head, which is why we chose to conduct a network meta-analysis. OBJECTIVES: To compare the efficacy and safety of non-biological systemic agents, small molecules, and biologics for people with moderate-to-severe psoriasis using a network meta-analysis, and to provide a ranking of these treatments according to their efficacy and safety. SEARCH METHODS: For this update of the living systematic review, we updated our searches of the following databases monthly to October 2021: the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, and Embase. SELECTION CRITERIA: Randomised controlled trials (RCTs) of systemic treatments in adults over 18 years with moderate-to-severe plaque psoriasis, at any stage of treatment, compared to placebo or another active agent. The primary outcomes were: proportion of participants who achieved clear or almost clear skin, that is, at least Psoriasis Area and Severity Index (PASI) 90; proportion of participants with serious adverse events (SAEs) at induction phase (8 to 24 weeks after randomisation). DATA COLLECTION AND ANALYSIS: We conducted duplicate study selection, data extraction, risk of bias assessment and analyses. We synthesised data using pairwise and network meta-analysis (NMA) to compare treatments and rank them according to effectiveness (PASI 90 score) and acceptability (inverse of SAEs). We assessed the certainty of NMA evidence for the two primary outcomes and all comparisons using CINeMA, as very low, low, moderate, or high. We contacted study authors when data were unclear or missing. We used the surface under the cumulative ranking curve (SUCRA) to infer treatment hierarchy, from 0% (worst for effectiveness or safety) to 100% (best for effectiveness or safety). MAIN RESULTS: This update includes an additional 19 studies, taking the total number of included studies to 167, and randomised participants to 58,912, 67.2% men, mainly recruited from hospitals. Average age was 44.5 years, mean PASI score at baseline was 20.4 (range: 9.5 to 39). Most studies were placebo-controlled (57%). We assessed a total of 20 treatments. Most (140) trials were multicentric (two to 231 centres). One-third of the studies (57/167) had high risk of bias; 23 unclear risk, and most (87) low risk. Most studies (127/167) declared funding by a pharmaceutical company, and 24 studies did not report a funding source. Network meta-analysis at class level showed that all interventions (non-biological systemic agents, small molecules, and biological treatments) showed a higher proportion of patients reaching PASI 90 than placebo. Anti-IL17 treatment showed a higher proportion of patients reaching PASI 90 compared to all the interventions, except anti-IL23. Biologic treatments anti-IL17, anti-IL12/23, anti-IL23 and anti-TNF alpha showed a higher proportion of patients reaching PASI 90 than the non-biological systemic agents. For reaching PASI 90, the most effective drugs when compared to placebo were (SUCRA rank order, all high-certainty evidence): infliximab (risk ratio (RR) 50.19, 95% CI 20.92 to 120.45), bimekizumab (RR 30.27, 95% CI 25.45 to 36.01), ixekizumab (RR 30.19, 95% CI 25.38 to 35.93), risankizumab (RR 28.75, 95% CI 24.03 to 34.39). Clinical effectiveness of these drugs was similar when compared against each other. Bimekizumab, ixekizumab and risankizumab showed a higher proportion of patients reaching PASI 90 than other anti-IL17 drugs (secukinumab and brodalumab) and guselkumab. Infliximab, anti-IL17 drugs (bimekizumab, ixekizumab, secukinumab and brodalumab) and anti-IL23 drugs (risankizumab and guselkumab) except tildrakizumab showed a higher proportion of patients reaching PASI 90 than ustekinumab and three anti-TNF alpha agents (adalimumab, certolizumab and etanercept). Ustekinumab was superior to certolizumab; adalimumab and ustekinumab were superior to etanercept. No significant difference was shown between apremilast and two non-biological drugs: ciclosporin and methotrexate. We found no significant difference between any of the interventions and the placebo for the risk of SAEs. The risk of SAEs was significantly lower for participants on methotrexate compared with most of the interventions. Nevertheless, the SAE analyses were based on a very low number of events with low- to moderate-certainty for all the comparisons (except methotrexate versus placebo, which was high-certainty). The findings therefore have to be viewed with caution. For other efficacy outcomes (PASI 75 and Physician Global Assessment (PGA) 0/1), the results were similar to the results for PASI 90. Information on quality of life was often poorly reported and was absent for several of the interventions. AUTHORS' CONCLUSIONS: Our review shows that, compared to placebo, the biologics infliximab, bimekizumab, ixekizumab, and risankizumab were the most effective treatments for achieving PASI 90 in people with moderate-to-severe psoriasis on the basis of high-certainty evidence. This NMA evidence is limited to induction therapy (outcomes measured from 8 to 24 weeks after randomisation), and is not sufficient for evaluating longer-term outcomes in this chronic disease. Moreover, we found low numbers of studies for some of the interventions, and the young age (mean 44.5 years) and high level of disease severity (PASI 20.4 at baseline) may not be typical of patients seen in daily clinical practice. We found no significant difference in the assessed interventions and placebo in terms of SAEs, and the safety evidence for most interventions was low to moderate quality. More randomised trials directly comparing active agents are needed, and these should include systematic subgroup analyses (sex, age, ethnicity, comorbidities, psoriatic arthritis). To provide long-term information on the safety of treatments included in this review, an evaluation of non-randomised studies and postmarketing reports from regulatory agencies is needed. Editorial note: This is a living systematic review. Living systematic reviews offer a new approach to review updating, in which the review is continually updated, incorporating relevant new evidence as it becomes available. Please refer to the Cochrane Database of Systematic Reviews for the current status of this review.