Arm-based Network Meta-analysis Research Articles

The use of fixed study main effects in arm-based network meta-analysis.

Methods of network meta-analysis (NMA) can be classified as arm-based and contrast-based approaches. There are several arm-based approaches, and some of these have been criticized because they recover inter-study information and hence do not obey the principle of concurrent control. Here, we point out that recovery of inter-study information in arm-based NMA can be prevented by fitting a fixed main effect for studies. Advantages of arm-based NMA are discussed.

Two Intramedullary and 1 Extramedullary Cortical Button, With or Without Interference Screw, Show Biomechanical Properties Superior to Native Tendon in Repair of the Distal Biceps Tendon: A Systematic Review and Network Meta-analysis of Biomechanical Performance

The aim of this study was to use a systematic review and network meta-analysis (NMA) to compare the failure strength, maximum strength, stiffness, and displacement of available constructs for distal biceps repair. An NMA was conducted to determine the performance of 2 all-suture suture anchors (2x ASA), 2 intramedullary cortical buttons (2x IM CB), 2 suture anchors (2x SA), extramedullary cortical buttons (EM CB), extramedullary cortical button plus interference screw (EM CB+IFS), interference screw (IFS), single intramedullary cortical button (IM CB), single suture anchor (SA), trans-osseous suture (TOS), tension slide technique (TST), and tension slide technique plus suture tape (TST+ST). Analysis consisted of arm-based network meta-analysis under Bayesian random-effects model with Markov Chain Monte Carlo (MCMC) sampling. Biomechanical outcomes were summarized as treatment effects and their corresponding 95% confidence intervals (CI). Rank probabilities were calculated and used to generate each treatment's surface under the cumulative ranking (SUCRA) curve. Biomechanical properties were compared to native tendon. Displacement >10mm was defined as clinical failure. Twenty-one studies were included. For failure strength, no construct outperformed the native tendon but 2x SA, IFS, SA, and TOS demonstrated poorer failure strength. For the maximum load to failure, EM CB+IFS outperformed the native tendon. Compared to native tendon, EM CB+IFS, EM CB, and 2xIM CB were stiffer, while 2x SA and IFS were less stiff. No construct demonstrated >10 mm of displacement, but constructs with displacement above the mean (3.5 mm) included 2x ASA, 2xIM CB, and TOS. The fixation constructs that consistently demonstrated comparable or better biomechanical properties (failure strength, maximum strength, stiffness) to native tendon in distal biceps tendon repair were the extramedullary cortical button with or without interference screw and two intramedullary cortical buttons. No construct demonstrated displacement beyond standard definitions for clinical failure. This network meta-analysis of biomechanical studies suggest that extramedullary cortical button and two intramedullary cortical buttons may be the most stable construct for distal biceps repair fixation, with equivalent or better biomechanical properties compared to native tendon.

Multivariate Bayesian Arm-Based Network Meta-Analysis of Pharmacological Interventions for the Treatment of Acute Bipolar Mania in Adults.

In a network meta-analysis (NMA), multiple treatments can be compared simultaneously by aggregating pieces of evidence from direct as well as indirect treatment comparisons in different randomized controlled trials (RCTs). Conventional NMA are performed using a normal approximation approach and can be applied for arm-level binary outcome data as well. This study aimed to estimate the treatment effects within a Bayesian framework using a binomial likelihood for a multivariate NMA model. The dataset consists of 57 RCTs comparing the effect of ten pharmacological drugs and a placebo for acute bipolar mania in adults. The binary outcomes of interest were treatment response and all-cause dropouts measured three weeks from the baseline. Binomial distribution was adopted for the number of events and the probability of event occurrence modeled on the logit scale. Jeffrey's Beta prior was considered for the heterogeneity and inconsistency of standard deviation (SD) parameters. Cholesky and spherical decomposition strategies were adopted for the between-study variance-covariance matrix. Deviance information criterion (DIC) indices were computed to determine the model fit. All results pertaining to Markov chain Monte Carlo simulations and all analyses were carried out in WinBUGS software. The estimated common heterogeneity SDs were similar, and the DIC values did not provide any evidence for superiority between the two decomposition strategies. The correlation (95% credible interval) between the outcomes was estimated as -0.31 (-0.71, -0.02) and -0.37 (-0.73, -0.03) for the Cholesky and spherical decompositions, respectively. Gelman-Rubin convergence statistics were stable, and Monte Carlo errors for all the parameters were around 0.005. Overall, olanzapine, paliperidone, and quetiapine were both significantly more effective and acceptable than a placebo when both the study outcomes were considered simultaneously. The findings favoring olanzapine, paliperidone, and quetiapine possess an excellent concordance with the one adopted in clinical practice, and the Canadian Network for Mood and Anxiety Treatments and Royal Australian and New Zealand College of Psychiatrists guidelines recommend these as first-line drugs for treating bipolar disorder.

Poster 186: Repair of the Distal Biceps Tendon: A Systematic Review & Network Meta-Analysis of Biomechanical Performance

Objectives:Rupture of the distal biceps is common and demonstrates excellent short- and long-term clinical outcomes following surgical repair. Prior studies have individually evaluated the biomechanical construct strength of multiple fixation devices, but none has comprehensively evaluated constructs in a head-to-head comparison. We sought to compare the failure strength, maximum strength, stiffness and displacement of available constructs for distal biceps repair.Methods:A network meta-analysis was conducted to determine the relative performance of 2 all-suture suture anchors, 2 intramedullary cortical buttons, 2 suture anchors, extramedullary cortical buttons, extramedullary cortical button plus interference screw, interference screw, single intramedullary cortical button, single suture anchor, trans-osseous suture, tension slide technique and tension slide technique plus suture tape. Analysis consisted of arm-based network meta-analysis under Bayesian random-effects model with Markov Chain Monte Carlo (MCMC) sampling. Geometry of the network was represented visually via a network plot with nodes representing treatments and edges representing direct comparative evidence. Biomechanical outcomes of fixation techniques were summarized as treatment effects and their corresponding 95% confidence intervals (CI). Rank probabilities were calculated and used to generate each treatment’s surface under the cumulative ranking (SUCRA) curve.Results:A total of 21 studies were included in the network meta-analysis. For failure strength, the two intramedullary cortical buttons ranked highest (92.73%). For maximum strength, the extramedullary cortical button alone (86.96%) and extramedullary button plus interference screw (83.40%) ranked highest. The two intramedullary cortical buttons ranked highest in stiffness (98.75%), followed by the extramedullary cortical button with interference screw (88.75%) and extramedullary cortical button (75.00%). Finally, with respect to demonstrating the least displacement after loading, the two suture anchors (89.43%) ranked highest, followed by tension slide technique with suture tape (73.14%) and extramedullary cortical button (72.71%).Conclusions:The fixation constructs that demonstrated the greatest overall biomechanical performance in distal biceps tendon repair were the extramedullary cortical button and two intramedullary cortical buttons. Two suture anchors demonstrated the least displacement after loading.Figure 1.Cochrane risk of bias summary of included studies.Figure 2.Evidence networks for outcomes of failure strength (A), maximum strength (B), stiffness (C), and displacement (D). The thickness of each line connecting two nodes is proportional to how often these two interventions were compared, while the size of each node is proportional to the respective patient sample size.Figure 3.Forest plot displaying the effect difference of each intervention on (A) failure strength, (B) maximum strength, (c) stiffness, and (D) displacement.

Bridging randomized controlled trials and single-arm trials using commensurate priors in arm-based network meta-analysis

Network meta-analysis (NMA) is a powerful tool to compare multiple treatments directly and indirectly by combining and contrasting multiple independent clinical trials. Because many NMAs collect only a few eligible randomized controlled trials (RCTs), there is an urgent need to synthesize different sources of information, for example, from both RCTs and single-arm trials. However, single-arm trials and RCTs may have different populations and quality so that assuming they are exchangeable may be inappropriate. This article presents a novel method using a commensurate prior on variance (CPV) to borrow variance (rather than mean) information from single-arm trials in an arm-based (AB) Bayesian NMA. We illustrate the advantages of this CPV method by reanalyzing an NMA of immune checkpoint inhibitors in cancer patients. Comprehensive simulations investigate the impact on statistical inference of including single-arm trials. The simulation results show that the CPV method provides efficient and robust estimation, even when the two sources of information are moderately inconsistent.

Monoclonal antibodies in type 2 asthma: an updated network meta-analysis.

Novel treatments target eosinophilic inflammation in type 2 asthma. We aimed to evaluate and meta-analyze the efficacy of monoclonal antibodies to reduce exacerbation rate. PubMed and Embase were searched for phase II and phase III randomized clinical trials with monoclonal antibodies targeting key mediators of type 2-associated asthma between 2019 and 2021 to update our previous meta-analysis covering studies published from 2005 to 2018. Five-hundred and sixty six publications have been identified, of which six recent trials (on top of 30 previously identified) involving mepolizumab, benralizumab, reslizumab and dupilumab met our inclusion criteria. As no head-to-head trials were retrieved from literature, we performed an arm-based network meta-analysis including a total of 19 RCTs to compare effects on exacerbation rate between the different treatments. Benralizumab significantly reduced the risk of exacerbations compared to the pooled placebo in our network meta-analysis (median effect difference: -0.520, 95% CI [-1.010- -0.048]). No biologic showed superiority over the others in indirect comparisons. Large reductions in exacerbation rates were observed compared to placebo, though only benralizumab was sufficiently powered (N.=2564) to demonstrate significantly decreased exacerbation rates both in the overall population and in the subgroup analysis of IL-5 acting agents compared to placebo. Monoclonal antibodies have proven their benefit to reduce exacerbation rates in severe persistent eosinophilic asthma in the published trials. No biological showed superiority over the others emphasizing the need for clearly defined endotypes indicating those patients who will optimally benefit for each treatment.

Root Coverage Predictability in the Treatment of Gingival Recessions on Mandibular Anterior Teeth.

Mandibular anterior teeth are most frequently affected by gingival recession. However, data regarding mucogingival treatment aimed at root coverage in this specific location are limited. The purpose of this study was to systematically review the scientific literature and to use the meta-analytic approach to address the following focused question: "What is the effectiveness of different surgical approaches on clinical and patient-related outcomes in the treatment of buccal gingival recessions on mandibular anterior teeth?" Studies were located by searching 3 electronic databases (Medline, Scopus, and Cochrane databases) and cross-referencing. Randomized and nonrandomized studies including at least 1 arm involving the use of pedicle flaps and/or free soft tissue grafts in the treatment of gingival recessions (recession type [RT] 1 and RT2) located on the buccal aspects of mandibular centrals, laterals and canines, were included in the analysis. Primary outcome was mean root coverage (mRC), expressed in percentage, based on a 3- to 12-mo follow-up observation. A Bayesian single-arm network meta-analysis was performed to identify a treatment hierarchy of the different surgical techniques. Sixteen studies, with a total of 23 arms, were included in the quantitative analysis. The greatest mRC is associated with laterally positioned flap (LPF) + connective tissue graft (CTG) (91.2%) and tunnel (TUN) + CTG (89.4%), whereas LPF alone, coronally advanced flap (CAF) + CTG, and free gingival graft (FGG) showed lower mRC (79.1%, 78.9%, and 68.5% respectively). TUN + CTG provides significantly greater mRC compared to CAF+CTG. No difference among the procedures could be observed in terms of keratinized tissue width gain. Treatment hierarchy generated by an arm-based network meta-analysis model suggested that tunnel and laterally positioned flap, both in combination with connective tissue graft, may provide the greatest mean root coverage in the treatment of mandibular anterior recessions. The results of the present systematic review can be used by clinicians when deciding which approach to adopt when treating buccal gingival recessions on mandibular anterior teeth. In particular, procedures based on a laterally positioned flap or a tunneling technique, both in combination with connective tissue graft, seem to be the most predictable therapeutic decision.

Comparative Renal Effects of Dipeptidyl Peptidase-4 Inhibitors and Sodium-Glucose Cotransporter 2 Inhibitors on Individual Outcomes in Patients with Type 2 Diabetes: A Systematic Review and Network Meta-Analysis.

BackgroundTo compare the renal effects of dipeptidyl peptidase-4 (DPP-4) inhibitors and sodium-glucose cotransporter 2 (SGLT2) inhibitors on individual outcomes in patients with type 2 diabetes.MethodsWe searched electronic databases (MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials) from inception to June 2019 to identity eligible randomized controlled trials of DPP-4 inhibitors or SGLT2 inhibitors that reported at least one kidney outcome in patients with type 2 diabetes. Outcomes of interest were microalbuminuria, macroalbuminuria, worsening nephropathy, and end-stage kidney disease (ESKD). We performed an arm-based network meta-analysis using Bayesian methods and calculated absolute risks and rank probabilities of each treatment for the outcomes.ResultsSeventeen studies with 87,263 patients were included. SGLT2 inhibitors significantly lowered the risks of individual kidney outcomes, including microalbuminuria (odds ratio [OR], 0.64; 95% credible interval [CrI], 0.41 to 0.93), macroalbuminuria (OR, 0.48; 95% CrI, 0.24 to 0.72), worsening nephropathy (OR, 0.65; 95% CrI, 0.44 to 0.91), and ESKD (OR, 0.65; 95% CrI, 0.46 to 0.98) as compared with placebo. However, DPP-4 inhibitors did not lower the risks. SGLT2 inhibitors were considerably associated with higher absolute risk reductions in all kidney outcomes than DPP-4 inhibitors, although the benefits were statistically insignificant. The rank probabilities showed that SGLT2 inhibitors were better treatments for lowering the risk of albuminuria and ESKD than placebo or DPP-4 inhibitors.ConclusionSGLT2 inhibitors were superior to DPP-4 inhibitors in reducing the risk of albuminuria and ESKD in patients with type 2 diabetes.

A variance shrinkage method improves arm-based Bayesian network meta-analysis.

Network meta-analysis is a commonly used tool to combine direct and indirect evidence in systematic reviews of multiple treatments to improve estimation compared to traditional pairwise meta-analysis. Unlike the contrast-based network meta-analysis approach, which focuses on estimating relative effects such as odds ratios, the arm-based network meta-analysis approach can estimate absolute risks and other effects, which are arguably more informative in medicine and public health. However, the number of clinical studies involving each treatment is often small in a network meta-analysis, leading to unstable treatment-specific variance estimates in the arm-based network meta-analysis approach when using non- or weakly informative priors under an unequal variance assumption. Additional assumptions, such as equal (i.e. homogeneous) variances for all treatments, may be used to remedy this problem, but such assumptions may be inappropriately strong. This article introduces a variance shrinkage method for an arm-based network meta-analysis. Specifically, we assume different treatment variances share a common prior with unknown hyperparameters. This assumption is weaker than the homogeneous variance assumption and improves estimation by shrinking the variances in a data-dependent way. We illustrate the advantages of the variance shrinkage method by reanalyzing a network meta-analysis of organized inpatient care interventions for stroke. Finally, comprehensive simulations investigate the impact of different variance assumptions on statistical inference, and simulation results show that the variance shrinkage method provides better estimation for log odds ratios and absolute risks.

The impact of covariance priors on arm-based Bayesian network meta-analyses with binary outcomes.

Bayesian analyses with the arm-based (AB) network meta-analysis (NMA) model require researchers to specify a prior distribution for the covariance matrix of the treatment-specific event rates in a transformed scale, for example, the treatment-specific log-odds when a logit transformation is used. The commonly used conjugate prior for the covariance matrix, the inverse-Wishart (IW) distribution, has several limitations. For example, although the IW distribution is often described as noninformative or weakly informative, it may in fact provide strong information when some variance components are small (eg, when the standard deviation of study-specific log-odds of a treatment is smaller than 1/2), as is common in NMAs with binary outcomes. In addition, the IW prior generally leads to underestimation of correlations between treatment-specific log-odds, which are critical for borrowing strength across treatment arms to estimate treatment effects efficiently and to reduce potential bias. Alternatively, several separation strategies (ie, separate priors on variances and correlations) can be considered. To study the IW prior's impact on NMA results and compare it with separation strategies, we did simulation studies under different missing-treatment mechanisms. A separation strategy with appropriate priors for the correlation matrix and variances performs better than the IW prior, and should be recommended as the default vague prior in the AB NMA approach. Finally, we reanalyzed three case studies and illustrated the importance, when performing AB-NMA, of sensitivity analyses with different prior specifications on variances.

272-OR: Do Diabetes Prevention Treatments Promote Regression to Normal Glucose Regulation? A Network Meta-analysis

Objective: In this meta-analysis, we compared the effect of different non-surgical diabetes prevention strategies on regression to normoglycemia among people with prediabetes. Methods: We systematically searched MEDLINE, EMBASE and Cochrane Library for articles published between 01-01-2000 to 05-30-2017. We included randomized controlled trials testing non-surgical interventions to prevent diabetes or improve glucose tolerance in adults with prediabetes, lasting at least three months, and reporting regression to normoglycemia rates. Using the number of participants that regressed to normoglycemia (fasting blood glucose <100 mg/dL, or two-hour post load glucose <140 mg/dL, or Hemoglobin A1c <5.7%) at the end of the intervention, we estimated the pooled risk difference (RD), number needed to treat (NNT) and relative risk using a Bayesian arm-based network meta-analysis. Results: Fifty-one studies were included (25,440 participants, mean age 54 years, 46% male). Of these, 30 study arms tested lifestyle modification (LSM), 15 tested medications (60% glucose sensitizers), 8 tested medications+LSM, 8 tested dietary supplements (vitamins, minerals and herbs), and 7 tested supplements+LSM. Compared to control arms (n=29) at a mean 1.6 years of follow up [range 0.2-5.0], medications achieved the largest regression rates (RD=12%, NNT=8), followed by LSM (RD=6%, NNT=17), medications+LSM (RD=5%, NNT=20), and supplements (RD=2%, NNT=50 with or without LSM). The corresponding relative risks were 2.06 (1.39, 2.95) for medications, 1.76 (1.34, 2.36) for LSM, 2.36 (1.55, 3.52) for medications+LSM, 2.60 (1.74, 3.66) for supplements+LSM, and 1.67 (1.07, 2.55) for supplements. Conclusion: Medications, glucose sensitizers in particular, are the most effective treatments for restoring normal glucose regulation in adults with prediabetes. LSM is also effective either alone or in combination with medications. Disclosure K.I. Galaviz: None. M. Weber: None. U. Gujral: None. J. Wei: None. K. Suvada: None. J. Haw: None. K. Narayan: None. M.K. Ali: Research Support; Self; Merck & Co., Inc. Funding National Heart, Lung, and Blood Institute (1K01HL149479-01); National Institute of Diabetes and Digestive and Kidney Diseases (P30DK111024)

Drug-associated adverse events in the treatment of multidrug-resistant tuberculosis: an individual patient data meta-analysis

Treatment of multidrug-resistant tuberculosis requires long-term therapy with a combination of multiple second-line drugs. These drugs are associated with numerous adverse events that can cause severe morbidity, such as deafness, and in some instances can lead to death. Our aim was to estimate the absolute and relative frequency of adverse events associated with different tuberculosis drugs to provide useful information for clinicians and tuberculosis programmes in selecting optimal treatment regimens. We did a meta-analysis using individual-level patient data that were obtained from studies that reported adverse events that resulted in permanent discontinuation of anti-tuberculosis medications. We used a database created for our previous meta-analysis of multidrug-resistant tuberculosis treatment and outcomes, for which we did a systematic review of literature published between Jan 1, 2009, and Aug 31, 2015 (updated April 15, 2016), and requested individual patient-level information from authors. We also considered for this analysis studies contributing patient-level data in response to a public call made by WHO in 2018. Meta-analysis for proportions and arm-based network meta-analysis were done to estimate the incidence of adverse events for each tuberculosis drug. 58 studies were identified, including 50 studies from the updated individual patient data meta-analysis for multidrug-resistant tuberculosis treatment. 35 of these studies, with 9178 patients, were included in our analysis. Using meta-analysis of proportions, drugs with low risks of adverse event occurrence leading to permanent discontinuation included levofloxacin (1·3% [95% CI 0·3-5·0]), moxifloxacin (2·9% [1·6-5·0]), bedaquiline (1·7% [0·7-4·2]), and clofazimine (1·6% [0·5-5·3]). Relatively high incidence of adverse events leading to permanent discontinuation was seen with three second-line injectable drugs (amikacin: 10·2% [6·3-16·0]; kanamycin: 7·5% [4·6-11·9]; capreomycin: 8·2% [6·3-10·7]), aminosalicylic acid (11·6% [7·1-18·3]), and linezolid (14·1% [9·9-19·6]). Risk of bias in selection of studies was judged to be low because there were no important differences between included and excluded studies. Variability between studies was significant for most outcomes analysed. Fluoroquinolones, clofazimine, and bedaquiline had the lowest incidence of adverse events leading to permanent drug discontinuation, whereas second-line injectable drugs, aminosalicylic acid, and linezolid had the highest incidence. These results suggest that close monitoring of adverse events is important for patients being treated for multidrug-resistant tuberculosis. Our results also underscore the urgent need for safer and better-tolerated drugs to reduce morbidity from treatment itself for patients with multidrug-resistant tuberculosis. Canadian Institutes of Health Research, Centers for Disease Control and Prevention (USA), American Thoracic Society, European Respiratory Society, and Infectious Diseases Society of America.

Robotic assistance in ventral hernia repair may decrease the incidence of hernia recurrence.

Background:Since the advent of laparoscopic surgery, many studies have shown the advantages of laparoscopic surgery over open surgery for ventral hernia repair (VHR). As robotic surgery is gaining popularity, we sought to compare the outcomes of this newer robotic-assisted technique to the outcomes of established open and laparoscopic techniques to assess for any additional benefit.Methods:A meta-analysis research design was employed. Multiple databases were queried for publications over the past 10 years and 23 articles were selected based on pre-determined selection criteria. Data were extracted and the arm-based network meta-analysis method was utilised to examine the effect difference for the three arms of our study: Open, laparoscopic and robotic-assisted VHR.Results:As expected, laparoscopy had an advantage over open VHR in terms of infection rates. This advantage was also observed in the robotic group over the open group; however, there was no statistical difference between the laparoscopic and robotic groups when infection rates were compared head-to-head. The robotic group had a significant advantage over both the open and more importantly, the laparoscopic groups in recurrence rates.Conclusions:The results of this study suggest that robotic surgery maintains some of the advantages of laparoscopic surgery and may also provide the additional advantage of recurrence rate reduction. This may be explained by the ability to perform a more complex hernia repair with robotic assistance secondary to the ease of closure of the fascial defect. More research is needed to validate this finding.

Performing Arm-Based Network Meta-Analysis in R with the pcnetmeta Package.

Network meta-analysis is a powerful approach for synthesizing direct and indirect evidence about multiple treatment comparisons from a collection of independent studies. At present, the most widely used method in network meta-analysis is contrast-based, in which a baseline treatment needs to be specified in each study, and the analysis focuses on modeling relative treatment effects (typically log odds ratios). However, population-averaged treatment-specific parameters, such as absolute risks, cannot be estimated by this method without an external data source or a separate model for a reference treatment. Recently, an arm-based network meta-analysis method has been proposed, and the R package pcnetmeta provides user-friendly functions for its implementation. This package estimates both absolute and relative effects, and can handle binary, continuous, and count outcomes.

Sensitivity to Excluding Treatments in Network Meta-analysis.

Network meta-analysis of randomized controlled trials is increasingly used to combine both direct evidence comparing treatments within trials and indirect evidence comparing treatments across different trials. When the outcome is binary, the commonly used contrast-based network meta-analysis methods focus on relative treatment effects such as odds ratios comparing two treatments. As shown in a recent report, when using contrast-based network meta-analysis, the impact of excluding a treatment in the network can be substantial, suggesting a methodological limitation. In addition, relative treatment effects are sometimes not sufficient for patients to make decisions. For example, it can be challenging for patients to trade off efficacy and safety for two drugs if they only know the relative effects, not the absolute effects. A recently proposed arm-based network meta-analysis, based on a missing-data framework, provides an alternative approach. It focuses on estimating population-averaged treatment-specific absolute effects. This article examines the influence of treatment exclusion empirically using 14 published network meta-analyses, for both arm- and contrast-based approaches. The difference between these two approaches is substantial, and it is almost entirely due to single-arm trials. When a treatment is removed from a contrast-based network meta-analysis, it is necessary to exclude other treatments in two-arm studies that investigated the excluded treatment; such exclusions are not necessary in arm-based network meta-analysis, leading to substantial gain in performance.

Linear mixed model approach to network meta-analysis for continuous outcomes in periodontal research.

Analysing continuous outcomes for network meta-analysis by means of linear mixed models is a great challenge, as it requires statistical software packages to specify special patterns of model error variance and covariance structure. This article demonstrates a non-Bayesian approach to network meta-analysis for continuous outcomes in periodontal research with a special focus on the adjustment of data dependency. Seventeen studies on guided tissue regeneration were used to illustrate how the proposed linear mixed models for network meta-analysis of continuous outcomes. Arm-based network meta-analysis use treatment arms from each study as the unit of analysis; when patients are randomly assigned to each arm, data are deemed independent and therefore no adjustment is required for multi-arm trials. Trial-based network meta-analysis use treatment contrasts as the unit of analysis, and therefore treatment contrasts within a multi-arm trial are not independent. This data dependency occurs also in split-mouth studies, and adjustments for data dependency are therefore required. Arm-based analysis is the preferred approach to network meta-analysis, when all included studies use the parallel group design and some compare more than two treatment arms. When included studies used designs that yield dependent data, the trial-based analysis is the preferred approach.

Antipsychotic treatment for children and adolescents with schizophrenia spectrum disorders: protocol for a network meta-analysis of randomised trials

IntroductionAntipsychotic treatment in early-onset schizophrenia (EOS) lacks a rich evidence base, and efforts to rank different drugs concerning their efficacy have not proven any particular drug superior. In contrast to...

OP0072 Comparative effectiveness of injection therapies in lateral epicondylitis: A systematic review and network meta-analysis of randomized controlled trials

BackgroundInjection therapy with glucocorticoids has been used since the 1950s as a treatment strategy for lateral epicondylitis (tennis elbow). Lately several other injection therapies have become available.ObjectivesUsing a systematic review...