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Andrija Babic; Ognjen Barcot; Tomislav Viskovic; Frano Šaric; Aleksandar Kirkovski; Ivana Barun; Zvonimir Križanac; Roshan Arjun Ananda; Yuli Viviana Fuentes Barreiro; Narges Malih; Daiana Anne-Marie Dimcea; Josipa Ordulj; Ishanka Weerasekara; Matteo Spezia; Marija Franka Žuljevic; Jelena Šuto; Luca Tancredi; Andela Pijuk; Susanna Sammali; Veronica Iascone; Thilo Groote; Tina Poklepovic Pericic; Livia Puljak – Research Synthesis Methods, 2024
Risk of bias (RoB) assessment is essential to the systematic review methodology. The new version of the Cochrane RoB tool for randomized trials (RoB 2) was published in 2019 to address limitations identified since the first version of the tool was published in 2008 and to increase the reliability of assessments. This study analyzed the frequency…
Descriptors: Risk, Bias, Use Studies, Meta Analysis
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Yuan Tian; Xi Yang; Suhail A. Doi; Luis Furuya-Kanamori; Lifeng Lin; Joey S. W. Kwong; Chang Xu – Research Synthesis Methods, 2024
RobotReviewer is a tool for automatically assessing the risk of bias in randomized controlled trials, but there is limited evidence of its reliability. We evaluated the agreement between RobotReviewer and humans regarding the risk of bias assessment based on 1955 randomized controlled trials. The risk of bias in these trials was assessed via two…
Descriptors: Risk, Randomized Controlled Trials, Classification, Robotics
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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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Yao, Minghong; Wang, Yuning; Ren, Yan; Jia, Yulong; Zou, Kang; Li, Ling; Sun, Xin – Research Synthesis Methods, 2023
Rare events meta-analyses of randomized controlled trials (RCTs) are often underpowered because the outcomes are infrequent. Real-world evidence (RWE) from non-randomized studies may provide valuable complementary evidence about the effects of rare events, and there is growing interest in including such evidence in the decision-making process.…
Descriptors: Evidence, Meta Analysis, Randomized Controlled Trials, Decision Making
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Nejstgaard, Camilla Hansen; Lundh, Andreas; Abdi, Suhayb; Clayton, Gemma; Gelle, Mustafe Hassan Adan; Laursen, David Ruben Teindl; Olorisade, Babatunde Kazeem; Savovic, Jelena; Hróbjartsson, Asbjørn – Research Synthesis Methods, 2022
Randomised trials are often funded by commercial companies and methodological studies support a widely held suspicion that commercial funding may influence trial results and conclusions. However, these studies often have a risk of confounding and reporting bias. The risk of confounding is markedly reduced in meta-epidemiological studies that…
Descriptors: Medical Research, Randomized Controlled Trials, Corporations, Financial Support
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Held, Leonhard; Matthews, Robert; Ott, Manuela; Pawel, Samuel – Research Synthesis Methods, 2022
It is now widely accepted that the standard inferential toolkit used by the scientific research community--null-hypothesis significance testing (NHST)--is not fit for purpose. Yet despite the threat posed to the scientific enterprise, there is no agreement concerning alternative approaches for evidence assessment. This lack of consensus reflects…
Descriptors: Bayesian Statistics, Statistical Inference, Hypothesis Testing, Credibility
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Armijo-Olivo, Susan; Craig, Rodger; Campbell, Sandy – Research Synthesis Methods, 2020
Background: Evidence from new health technologies is growing, along with demands for evidence to inform policy decisions, creating challenges in completing health technology assessments (HTAs)/systematic reviews (SRs) in a timely manner. Software can decrease the time and burden by automating the process, but evidence validating such software is…
Descriptors: Comparative Analysis, Computer Software, Decision Making, Randomized Controlled Trials
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Moustgaard, Helene; Jones, Hayley E.; Savovic, Jelena; Clayton, Gemma L.; Sterne, Jonathan AC; Higgins, Julian PT; Hróbjartsson, Asbjørn – Research Synthesis Methods, 2020
Randomized clinical trials underpin evidence-based clinical practice, but flaws in their conduct may lead to biased estimates of intervention effects and hence invalid treatment recommendations. The main approach to the empirical study of bias is to collate a number of meta-analyses and, within each, compare the results of trials with and without…
Descriptors: Epidemiology, Evidence, Medical Research, Intervention
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Robertson, Clare; Ramsay, Craig; Gurung, Tara; Mowatt, Graham; Pickard, Robert; Sharma, Pawana – Research Synthesis Methods, 2014
We describe our experience of using a modified version of the Cochrane risk of bias (RoB) tool for randomised and non-randomised comparative studies. Objectives: (1) To assess time to complete RoB assessment; (2) To assess inter-rater agreement; and (3) To explore the association between RoB and treatment effect size. Methods: Cochrane risk of…
Descriptors: Risk, Randomized Controlled Trials, Research Design, Comparative Analysis
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Norris, Susan L.; Moher, David; Reeves, Barnaby C.; Shea, Beverley; Loke, Yoon; Garner, Sarah; Anderson, Laurie; Tugwell, Peter; Wells, George – Research Synthesis Methods, 2013
Background: Selective outcome and analysis reporting (SOR and SAR) occur when only a subset of outcomes measured and analyzed in a study is fully reported, and are an important source of potential bias. Key methodological issues: We describe what is known about the prevalence and effects of SOR and SAR in both randomized controlled trials (RCTs)…
Descriptors: Health Services, Intervention, Outcomes of Treatment, Research Methodology