Novel presentational approaches were developed for reporting network meta-analysis.

Objectives: To present graphical tools for reporting network meta-analysis (NMA) results aiming to increase the accessibility, transparency, interpretability, and acceptability of NMA analyses.

Study Design And Settings: The key components of NMA results were identified based on recommendations by agencies such as the National Institute for Health and Care Excellence (United Kingdom). Three novel graphs were designed to amalgamate the identified components using familiar graphical tools such as the bar, line, or pie charts and adhering to good graphical design principles.

Meta-analysis of the accuracy of two diagnostic tests used in combination: application to the ddimer test and the wells score for the diagnosis of deep vein thrombosis.

Objectives: It is standard practice for diagnostic tests to be evaluated against gold standards in isolation. In routine clinical practice, however, it is commonplace for multiple tests to be used before making definitive diagnoses. This article describes a meta-analytic modeling framework developed to estimate the accuracy of the combination of two diagnostic tests, accounting for the likely nonindependence of the tests.

Evaluating the cost-effectiveness of diagnostic tests in combination: is it important to allow for performance dependency?

Objectives: To investigate the importance of accounting for potential performance dependency when evaluating the cost-effectiveness of two diagnostic tests used in combination.

Methods: Two meta-analysis models were fitted to estimate the diagnostic accuracy of Wells score and Ddimer in combination. The first model assumes that the two tests perform independently of one another; thus, two separate meta-analyses were fitted to the Ddimer and Wells score data and then combined.

Graphical augmentations to the funnel plot assess the impact of additional evidence on a meta-analysis.

Objective: We aim to illustrate the potential impact of a new study on a meta-analysis, which gives an indication of the robustness of the meta-analysis.

Study Design And Setting: A number of augmentations are proposed to one of the most widely used of graphical displays, the funnel plot. Namely, 1) statistical significance contours, which define regions of the funnel plot in which a new study would have to be located to change the statistical significance of the meta-analysis; and 2) heterogeneity contours, which show how a new study would affect the extent of heterogeneity in a given meta-analysis.

Assessment of publication bias, selection bias, and unavailable data in meta-analyses using individual participant data: a database survey.

Objective: To examine the potential for publication bias, data availability bias, and reviewer selection bias in recently published meta-analyses that use individual participant data and to investigate whether authors of such meta-analyses seemed aware of these issues.

Design: In a database of 383 meta-analyses of individual participant data that were published between 1991 and March 2009, we surveyed the 31 most recent meta-analyses of randomised trials that examined whether an intervention was effective. Identification of relevant articles and data extraction was undertaken by one author and checked by another.

Bayesian model selection for meta-analysis of diagnostic test accuracy data: Application to Ddimer for deep vein thrombosis.

A number of statistical models have been developed for meta-analysis (MA) of diagnostic test (DT) accuracy data. Here we consider these alternative MA models, explore the relationships between them, and consider the use of the deviance information criteria (DIC) to decide which is the most appropriate model for a given dataset. A Bayesian statistical approach is adopted throughout.

Empirical assessment suggests that existing evidence could be used more fully in designing randomized controlled trials.

Background: Meta-analyses of randomized controlled trials (RCTs) provide the highest level of evidence regarding the effectiveness of interventions. Less is known about how they are used to inform the design and reporting of RCTs.

Methods: A sample of RCTs published in leading medical journals in 2007 was assessed to establish whether authors considered previous trials in the design of their trial.

Evidence synthesis as the key to more coherent and efficient research.

Background: Systematic review and meta-analysis currently underpin much of evidence-based medicine. Such methodologies bring order to previous research, but future research planning remains relatively incoherent and inefficient.

Methods: To outline a framework for evaluation of health interventions, aimed at increasing coherence and efficiency through i) making better use of information contained within the existing evidence-base when designing future studies; and ii) maximising the information available and thus potentially reducing the need for future studies.

Integration of meta-analysis and economic decision modeling for evaluating diagnostic tests.

Meta-analysis of diagnostic test accuracy data is more difficult than of effectiveness data because of 1) statistical challenges of dealing with multiple measures of accuracy (e.g., sensitivity and specificity) simultaneously and 2) incorporating threshold effects.

Cost-effectiveness and value of information analyses of neuraminidase inhibitors for the treatment of influenza.

Objectives: To assess the cost-effectiveness of alternative strategies for the treatment of suspected influenza in otherwise healthy adults and to identify future research priorities using value of information analysis.

Methods: A decision model was used to estimate the costs and effects, in terms of quality-adjusted life-years (QALYs) of amantadine, zanamivir, and oseltamivir for the treatment of influenza in otherwise healthy adults using data predominantly from meta-analysis of randomized controlled trials. Probabilistic sensitivity analysis using Monte Carlo simulation was conducted.

Recent developments in meta-analysis.

The art and science of meta-analysis, the combination of results from multiple independent studies, is now more than a century old. In the last 30 years, however, as the need for medical research and clinical practice to be based on the totality of relevant and sound evidence has been increasingly recognized, the impact of meta-analysis has grown enormously. In this paper, we review highlights of recent developments in meta-analysis in medical research.

Bivariate random-effects meta-analysis and the estimation of between-study correlation.

Background: When multiple endpoints are of interest in evidence synthesis, a multivariate meta-analysis can jointly synthesise those endpoints and utilise their correlation. A multivariate random-effects meta-analysis must incorporate and estimate the between-study correlation (rhoB).

Methods: In this paper we assess maximum likelihood estimation of a general normal model and a generalised model for bivariate random-effects meta-analysis (BRMA).

Predicting costs over time using Bayesian Markov chain Monte Carlo methods: an application to early inflammatory polyarthritis.

This article focuses on the modelling and prediction of costs due to disease accrued over time, to inform the planning of future services and budgets. It is well documented that the modelling of cost data is often problematic due to the distribution of such data; for example, strongly right skewed with a significant percentage of zero-cost observations. An additional problem associated with modelling costs over time is that cost observations measured on the same individual at different time points will usually be correlated.

Evidence-based sample size calculations based upon updated meta-analysis.

Meta-analyses of randomized controlled trials (RCTs) provide the highest level of evidence regarding the effectiveness of interventions and as such underpin much of evidence-based medicine. Despite this, meta-analyses are usually produced as observational by-products of the existing literature, with no formal consideration of future meta-analyses when individual trials are being designed. Basing the sample size of a new trial on the results of an updated meta-analysis which will include it, may sometimes make more sense than powering the trial in isolation.

Mixed comparison of stroke prevention treatments in individuals with nonrheumatic atrial fibrillation.

Background: We aimed to identify different stroke prevention treatments for atrial fibrillation assessed in randomized controlled trials and to compare them within a single evidence synthesis framework.

Methods: We updated the Cochrane review on anticoagulants and antiplatelet therapy for nonrheumatic atrial fibrillation to include randomized controlled trials published between January 2000 and March 2005 identified via the CENTRAL database and MEDLINE. A mixed-treatment comparison method was used to combine direct within-trial, between-treatment comparisons with indirect trial evidence while maintaining randomization.

Role of multivitamins and mineral supplements in preventing infections in elderly people: systematic review and meta-analysis of randomised controlled trials.

Objective: To evaluate the effectiveness of multivitamins and mineral supplements in reducing infections in an elderly population.

Design: Systematic review and meta-analysis of randomised controlled trials.

Data Sources: Medline and other databases.

A Bayesian approach to evaluating net clinical benefit allowed for parameter uncertainty.

Background And Objective: Although randomized controlled trials (RCTs) are conducted to establish whether novel interventions work on average in the patient population, there is a growing desire to move to a more individualized approach to evaluation. The potential benefits and harms of a treatment policy may differ between individuals. If these benefits and harms are not evaluated distinctly, and in a quantitative framework, transparency can be lost in the decision-making process.

What to add to nothing? Use and avoidance of continuity corrections in meta-analysis of sparse data.

Objectives: To compare the performance of different meta-analysis methods for pooling odds ratios when applied to sparse event data with emphasis on the use of continuity corrections.

Background: Meta-analysis of side effects from RCTs or risk factors for rare diseases in epidemiological studies frequently requires the synthesis of data with sparse event rates. Combining such data can be problematic when zero events exist in one or both arms of a study as continuity corrections are often needed, but, these can influence results and conclusions.

Effectiveness of neuraminidase inhibitors in treatment and prevention of influenza A and B: systematic review and meta-analyses of randomised controlled trials.

Objective: To review the clinical effectiveness of oseltamivir and zanamivir for the treatment and prevention of influenza A and B.

Design: Systematic review and meta-analyses of randomised controlled trials.

Data Sources: Published studies were retrieved from electronic bibliographic databases; supplementary data were obtained from the manufacturers.

Generalized synthesis of evidence and the threat of dissemination bias. the example of electronic fetal heart rate monitoring (EFM).

Assessment of the potential impact of dissemination bias is necessary for meta-analysis. When evidence is available from studies of different designs, the different study types may be affected by dissemination bias to differing degrees. The evidence relating to electronic fetal heart rate monitoring (EFM) for preventing perinatal mortality is used to explore the feasibility of carrying out a dissemination bias assessment in a generalized synthesis of evidence (gse) framework.

Meta-analysis of rare and adverse event data.

Potentially beneficial drugs may have side effects. Such adverse events may be serious but rare, making their effect difficult to quantify, or even their identification problematic within randomized controlled trials. Meta-analysis provides a means of combining such outcome data across a series of studies and provides a more powerful analysis than is possible from a single study.