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Use of Multiple Covariates in Assessing Treatment-Effect Modifiers: A Methodological Review of Individual Participant Data Meta-Analyses
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Peter J. Godolphin; Nadine Marlin; Chantelle Cornett; David J. Fisher; Jayne F. Tierney; Ian R. White; Ewelina Rogozinska – Research Synthesis Methods, 2024
Individual participant data (IPD) meta-analyses of randomised trials are considered a reliable way to assess participant-level treatment effect modifiers but may not make the best use of the available data. Traditionally, effect modifiers are explored one covariate at a time, which gives rise to the possibility that evidence of treatment-covariate…
Descriptors: Meta Analysis, Randomized Controlled Trials, Statistical Analysis, Participant Characteristics
Consensus on the Definition and Assessment of External Validity of Randomized Controlled Trials: A Delphi Study
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Andres Jung; Tobias Braun; Susan Armijo-Olivo; Dimitris Challoumas; Kerstin Luedtke – Research Synthesis Methods, 2024
External validity is an important parameter that needs to be considered for decision making in health research, but no widely accepted measurement tool for the assessment of external validity of randomized controlled trials (RCTs) exists. One of the most limiting factors for creating such a tool is probably the substantial heterogeneity and lack…
Descriptors: Randomized Controlled Trials, Validity, Delphi Technique, Definitions
Frequency of Use and Adequacy of Cochrane Risk of Bias Tool 2 in Non-Cochrane Systematic Reviews Published in 2020: Meta-Research Study
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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
Data Extraction for Evidence Synthesis Using a Large Language Model: A Proof-of-Concept Study
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Gerald Gartlehner; Leila Kahwati; Rainer Hilscher; Ian Thomas; Shannon Kugley; Karen Crotty; Meera Viswanathan; Barbara Nussbaumer-Streit; Graham Booth; Nathaniel Erskine; Amanda Konet; Robert Chew – Research Synthesis Methods, 2024
Data extraction is a crucial, yet labor-intensive and error-prone part of evidence synthesis. To date, efforts to harness machine learning for enhancing efficiency of the data extraction process have fallen short of achieving sufficient accuracy and usability. With the release of large language models (LLMs), new possibilities have emerged to…
Descriptors: Data Collection, Evidence, Synthesis, Language Processing
Accuracy and Precision of Fixed and Random Effects in Meta-Analyses of Randomized Control Trials for Continuous Outcomes
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Timo Gnambs; Ulrich Schroeders – Research Synthesis Methods, 2024
Meta-analyses of treatment effects in randomized control trials are often faced with the problem of missing information required to calculate effect sizes and their sampling variances. Particularly, correlations between pre- and posttest scores are frequently not available. As an ad-hoc solution, researchers impute a constant value for the missing…
Descriptors: Accuracy, Meta Analysis, Randomized Controlled Trials, Effect Size
Development of the Individual Participant Data Integrity Tool for Assessing the Integrity of Randomised Trials Using Individual Participant Data
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Kylie E. Hunter; Mason Aberoumand; Sol Libesman; James X. Sotiropoulos; Jonathan G. Williams; Wentao Li; Jannik Aagerup; Ben W. Mol; Rui Wang; Angie Barba; Nipun Shrestha; Angela C. Webster; Anna Lene Seidler – Research Synthesis Methods, 2024
Increasing integrity concerns in medical research have prompted the development of tools to detect untrustworthy studies. Existing tools primarily assess published aggregate data (AD), though scrutiny of individual participant data (IPD) is often required to detect trustworthiness issues. Thus, we developed the IPD Integrity Tool for detecting…
Descriptors: Integrity, Randomized Controlled Trials, Data Use, Individual Characteristics
The Individual Participant Data Integrity Tool for Assessing the Integrity of Randomised Trials
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Kylie E. Hunter; Mason Aberoumand; Sol Libesman; James X. Sotiropoulos; Jonathan G. Williams; Jannik Aagerup; Rui Wang; Ben W. Mol; Wentao Li; Angie Barba; Nipun Shrestha; Angela C. Webster; Anna Lene Seidler – Research Synthesis Methods, 2024
Increasing concerns about the trustworthiness of research have prompted calls to scrutinise studies' Individual Participant Data (IPD), but guidance on how to do this was lacking. To address this, we developed the IPD Integrity Tool to screen randomised controlled trials (RCTs) for integrity issues. Development of the tool involved a literature…
Descriptors: Integrity, Randomized Controlled Trials, Participant Characteristics, Computer Software
Twenty Years of Network Meta-Analysis: Continuing Controversies and Recent Developments
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A. E. Ades; Nicky J. Welton; Sofia Dias; David M. Phillippo; Deborah M. Caldwell – Research Synthesis Methods, 2024
Network meta-analysis (NMA) is an extension of pairwise meta-analysis (PMA) which combines evidence from trials on multiple treatments in connected networks. NMA delivers internally consistent estimates of relative treatment efficacy, needed for rational decision making. Over its first 20 years NMA's use has grown exponentially, with applications…
Descriptors: Network Analysis, Meta Analysis, Medicine, Clinical Experience
Towards the Automatic Risk of Bias Assessment on Randomized Controlled Trials: A Comparison of RobotReviewer and Humans
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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
Individual Participant Data Meta-Analysis to Examine Linear or Non-Linear Treatment-Covariate Interactions at Multiple Time-Points for a Continuous Outcome
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Miriam Hattle; Joie Ensor; Katie Scandrett; Marienke van Middelkoop; Danielle A. van der Windt; Melanie A. Holden; Richard D. Riley – Research Synthesis Methods, 2024
Individual participant data (IPD) meta-analysis projects obtain, harmonise, and synthesise original data from multiple studies. Many IPD meta-analyses of randomised trials are initiated to identify treatment effect modifiers at the individual level, thus requiring statistical modelling of interactions between treatment effect and participant-level…
Descriptors: Meta Analysis, Randomized Controlled Trials, Outcomes of Treatment, Evaluation Methods
Combining Randomized and Non-Randomized Data to Predict Heterogeneous Effects of Competing Treatments
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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
Combining Endpoint and Change Data Did Not Affect the Summary Standardised Mean Difference in Pairwise and Network Meta-Analyses: An Empirical Study in Depression
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Edoardo G. Ostinelli; Orestis Efthimiou; Yan Luo; Clara Miguel; Eirini Karyotaki; Pim Cuijpers; Toshi A. Furukawa; Georgia Salanti; Andrea Cipriani – Research Synthesis Methods, 2024
When studies use different scales to measure continuous outcomes, standardised mean differences (SMD) are required to meta-analyse the data. However, outcomes are often reported as endpoint or change from baseline scores. Combining corresponding SMDs can be problematic and available guidance advises against this practice. We aimed to examine the…
Descriptors: Network Analysis, Meta Analysis, Depression (Psychology), Regression (Statistics)