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Li, Hua; Shih, Ming-Chieh; Tu, Yu-Kang – Research Synthesis Methods, 2023
Component network meta-analysis (CNMA) compares treatments comprising multiple components and estimates the effects of individual components. For network meta-analysis, a standard network plot with nodes for treatments and edges for direct comparisons between treatments is drawn to visualize the evidence structure and the connections between…
Descriptors: Networks, Meta Analysis, Graphs, Comparative Analysis
Konstantina Chalkou; Tasnim Hamza; Pascal Benkert; Jens Kuhle; Chiara Zecca; Gabrielle Simoneau; Fabio Pellegrini; Andrea Manca; Matthias Egger; Georgia Salanti – Research Synthesis Methods, 2024
Some patients benefit from a treatment while others may do so less or do not benefit at all. We have previously developed a two-stage network meta-regression prediction model that synthesized randomized trials and evaluates how treatment effects vary across patient characteristics. In this article, we extended this model to combine different…
Descriptors: Medical Research, Outcomes of Treatment, Risk, Randomized Controlled Trials
Bengough, Theresa; Sommer, Isolde; Hannes, Karin – Research Synthesis Methods, 2023
Contextual factors such as cultural values and traditions impact on implementation processes of healthcare interventions. It is one of the reasons why local stakeholders may decide to role out a programme differently from how it has originally been developed or described in scientific literature. This can result in different but most likely more…
Descriptors: Context Effect, Evaluation Methods, Cultural Influences, Intervention
Noma, Hisashi; Hamura, Yasuyuki; Sugasawa, Shonosuke; Furukawa, Toshi A. – Research Synthesis Methods, 2023
Network meta-analysis has played an important role in evidence-based medicine for assessing the comparative effectiveness of multiple available treatments. The prediction interval has been one of the standard outputs in recent network meta-analysis as an effective measure that enables simultaneous assessment of uncertainties in treatment effects…
Descriptors: Intervals, Meta Analysis, Evidence Based Practice, Comparative Analysis
Thompson Coon, Jo; Gwernan-Jones, Ruth; Garside, Ruth; Nunns, Michael; Shaw, Liz; Melendez-Torres, G. J.; Moore, Darren – Research Synthesis Methods, 2020
The incorporation of evidence derived from multiple research designs into one single synthesis can enhance the utility of systematic reviews making them more worthwhile, useful, and insightful. Methodological guidance for mixed-methods synthesis continues to emerge and evolve but broadly involves a sequential, parallel, or convergent approach…
Descriptors: Evidence, Medical Research, Mixed Methods Research, Case Studies
Luo, Yan; Chaimani, Anna; Furukawa, Toshi A.; Kataoka, Yuki; Ogawa, Yusuke; Cipriani, Andrea; Salanti, Georgia – Research Synthesis Methods, 2021
It is often challenging to present the available evidence in a timely and comprehensible manner. We aimed to visualize the evolution of evidence about antidepressants for depression by conducting cumulative network meta-analyses (NMAs) and to examine whether it could have helped the selection of optimal drugs. We built a Shiny web application that…
Descriptors: Networks, Network Analysis, Meta Analysis, Drug Therapy
Anwer, Sumayya; Ades, A. E.; Dias, Sofia – Research Synthesis Methods, 2020
Background: When there are structural relationships between outcomes reported in different trials, separate analyses of each outcome do not provide a single coherent analysis, which is required for decision-making. For example, trials of intrapartum anti-bacterial prophylaxis (IAP) to prevent early onset group B streptococcal (EOGBS) disease can…
Descriptors: Meta Analysis, Outcomes of Treatment, Diseases, Decision Making
Noma, Hisashi; Gosho, Masahiko; Ishii, Ryota; Oba, Koji; Furukawa, Toshi A. – Research Synthesis Methods, 2020
Network meta-analysis has been gaining prominence as an evidence synthesis method that enables the comprehensive synthesis and simultaneous comparison of multiple treatments. In many network meta-analyses, some of the constituent studies may have markedly different characteristics from the others, and may be influential enough to change the…
Descriptors: Networks, Meta Analysis, Evidence, Comparative Analysis
Shih, Ming-Chieh; Tu, Yu-Kang – Research Synthesis Methods, 2019
Network meta-analysis (NMA) uses both direct and indirect evidence to compare the efficacy and harm between several treatments. Structural equation modeling (SEM) is a statistical method that investigates relations among observed and latent variables. Previous studies have shown that the contrast-based Lu-Ades model for NMA can be implemented in…
Descriptors: Meta Analysis, Structural Equation Models, Evidence, Comparative Analysis
Reid, Edwin; Guise, Jeanne-Marie; Fiordalisi, Celia; Macdonald, Scott; Chang, Stephanie – Research Synthesis Methods, 2021
Evidence-based decision-making is predicated on the ability of users to find and comprehend results from systematic review. Evidence producers have an obligation to support evidence users in this process. The Agency for Healthcare Research and Quality (AHRQ) Evidence-based Practice Center (EPC) program--a producer of rigorous and comprehensive…
Descriptors: Evidence Based Practice, Decision Making, Criticism, Health Services
Stevens, John W.; Fletcher, Christine; Downey, Gerald; Sutton, Anthea – Research Synthesis Methods, 2018
A network meta-analysis allows a simultaneous comparison between treatments evaluated in randomised controlled trials that share at least one treatment with at least one other study. Estimates of treatment effects may be required for treatments across disconnected networks of evidence, which requires a different statistical approach and modelling…
Descriptors: Meta Analysis, Network Analysis, Comparative Analysis, Outcomes of Treatment
Watkins, Claire; Bennett, Iain – Research Synthesis Methods, 2018
In studies with time-to-event data, outcomes may be reported as hazard ratios (HR) or binomial counts/proportions at a specific time point. If the intent is to synthesise evidence by performing a meta-analysis or network meta-analysis (NMA) using the HR as the measure of treatment effect, studies that only report binomial data cannot be included…
Descriptors: Meta Analysis, Medical Research, Network Analysis, Outcomes of Treatment
Melendez-Torres, G. J.; Sutcliffe, Katy; Burchett, Helen E. D.; Rees, Rebecca; Thomas, James – Research Synthesis Methods, 2019
Qualitative comparative analysis (QCA) was originally developed as a tool for cross-national comparisons in macrosociology, but its use in evaluation and evidence synthesis of complex interventions is rapidly developing. QCA is theory-driven and relies on Boolean logic to identify pathways to an outcome (e.g., is the intervention effective or…
Descriptors: Comparative Analysis, Intervention, Evidence, Logical Thinking
Freeman, S. C.; Fisher, D.; Tierney, J. F.; Carpenter, J. R. – Research Synthesis Methods, 2018
Background: Stratified medicine seeks to identify patients most likely to respond to treatment. Individual participant data (IPD) network meta-analysis (NMA) models have greater power than individual trials to identify treatment-covariate interactions (TCIs). Treatment-covariate interactions contain "within" and "across" trial…
Descriptors: Medical Research, Patients, Outcomes of Treatment, Meta Analysis
Donegan, Sarah; Welton, Nicky J.; Tudur Smith, Catrin; D'Alessandro, Umberto; Dias, Sofia – Research Synthesis Methods, 2017
Background: Many reviews aim to compare numerous treatments and report results stratified by subgroups (eg, by disease severity). In such cases, a network meta-analysis model including treatment by covariate interactions can estimate the relative effects of all treatment pairings for each subgroup of patients. Two key assumptions underlie such…
Descriptors: Network Analysis, Meta Analysis, Outcomes of Treatment, Comparative Analysis
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