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Konstantinos I. Bougioukas; Paschalis Karakasis; Konstantinos Pamporis; Emmanouil Bouras; Anna-Bettina Haidich – Research Synthesis Methods, 2024
Systematic reviews (SRs) have an important role in the healthcare decision-making practice. Assessing the overall confidence in the results of SRs using quality assessment tools, such as "A MeaSurement Tool to Assess Systematic Reviews 2" (AMSTAR 2), is crucial since not all SRs are conducted using the most rigorous methods. In this…
Descriptors: Programming Languages, Research Methodology, Decision Making, Medical Research
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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
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Andreas Halman; Alicia Oshlack – Research Synthesis Methods, 2024
A systematic review is a type of literature review that aims to collect and analyse all available evidence from the literature on a particular topic. The process of screening and identifying eligible articles from the vast amounts of literature is a time-consuming task. Specialised software has been developed to aid in the screening process and…
Descriptors: Literature Reviews, Medical Research, Computer Software, Users (Information)
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Siegel, Lianne; Chu, Haitao – Research Synthesis Methods, 2023
Reference intervals, or reference ranges, aid medical decision-making by containing a pre-specified proportion (e.g., 95%) of the measurements in a representative healthy population. We recently proposed three approaches for estimating a reference interval from a meta-analysis based on a random effects model: a frequentist approach, a Bayesian…
Descriptors: Bayesian Statistics, Meta Analysis, Intervals, Decision Making
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Godolphin, Peter J.; White, Ian R.; Tierney, Jayne F.; Fisher, David J. – Research Synthesis Methods, 2023
Estimation of within-trial interactions in meta-analysis is crucial for reliable assessment of how treatment effects vary across participant subgroups. However, current methods have various limitations. Patients, clinicians and policy-makers need reliable estimates of treatment effects within specific covariate subgroups, on relative and absolute…
Descriptors: Meta Analysis, Outcomes of Treatment, Medical Research, Comparative Analysis
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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
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Sutton, Anthea; O'Keefe, Hannah; Johnson, Eugenie Evelynne; Marshall, Christopher – Research Synthesis Methods, 2023
The Systematic Review Toolbox aims provide a web-based catalogue of tools that support various tasks within the systematic review and wider evidence synthesis process. Identifying publications surrounding specific systematic review tools is currently challenging, leading to a high screening burden for few eligible records. We aimed to develop a…
Descriptors: Search Strategies, Automation, Evidence, Synthesis
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Efthimiou, Orestis; White, Ian R. – Research Synthesis Methods, 2020
Standard models for network meta-analysis simultaneously estimate multiple relative treatment effects. In practice, after estimation, these multiple estimates usually pass through a formal or informal selection procedure, eg, when researchers draw conclusions about the effects of the best performing treatment in the network. In this paper, we…
Descriptors: Models, Meta Analysis, Network Analysis, Simulation
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Seide, Svenja E.; Jensen, Katrin; Kieser, Meinhard – Research Synthesis Methods, 2021
Traditional visualization in meta-analysis uses forest plots to illustrate the combined treatment effect, along with the respective results from primary trials. While the purpose of visualization is clear in the pairwise setting, additional treatments broaden the focus and extend the results to be illustrated in network meta-analysis. The…
Descriptors: Graphs, Visualization, Simulation, Meta Analysis
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Porgo, Teegwendé V.; Norris, Susan L.; Salanti, Georgia; Johnson, Leigh F.; Simpson, Julie A.; Low, Nicola; Egger, Matthias; Althaus, Christian L. – Research Synthesis Methods, 2019
Mathematical modeling studies are increasingly recognised as an important tool for evidence synthesis and to inform clinical and public health decision-making, particularly when data from systematic reviews of primary studies do not adequately answer a research question. However, systematic reviewers and guideline developers may struggle with…
Descriptors: Mathematical Models, Evidence, Glossaries, Medical Research
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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
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Tipton, Elizabeth; Pustejovsky, James E.; Ahmadi, Hedyeh – Research Synthesis Methods, 2019
Having surveyed the history and methods of meta-regression in a previous paper, in this paper, we review which and how meta-regression methods are applied in recent research syntheses. To do so, we reviewed studies published in 2016 across four leading research synthesis journals: "Psychological Bulletin," the "Journal of Applied…
Descriptors: Medical Research, Psychological Studies, Regression (Statistics), Journal Articles
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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
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Schmitz, Tom; Bukowski, Mark; Koschmieder, Steffen; Schmitz-Rode, Thomas; Farkas, Robert – Research Synthesis Methods, 2019
Launching biomedical innovations based on clinical demands instead of translating basic research findings to practice reduces the risk that the results will not fit the clinical routine. To realize this type of innovation, a meta-analysis of the body of research is necessary to reveal demand-matching concepts. However, both the data deluge and the…
Descriptors: Innovation, Biomedicine, Medical Research, Meta Analysis
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Rücker, Gerta; Cates, Christopher J.; Schwarzer, Guido – Research Synthesis Methods, 2017
Systematic reviewers conducting pairwise meta-analyses sometimes encounter multi-arm studies. To include these studies, and to avoid a unit-of-analysis error, often two or more arms are combined or the control arm is split. In this tutorial, we present 5 different approaches that can be used. Particularly, we present a novel approach (method 4)…
Descriptors: Meta Analysis, Medical Research, Outcomes of Treatment, Error of Measurement
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