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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
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
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
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
Daly, Caitlin H.; Maconachie, Ross; Ades, A. E.; Welton, Nicky J. – Research Synthesis Methods, 2022
Randomised controlled trials of cancer treatments typically report progression free survival (PFS) and overall survival (OS) outcomes. Existing methods to synthesise evidence on PFS and OS either rely on the proportional hazards assumption or make parametric assumptions which may not capture the diverse survival curve shapes across studies and…
Descriptors: Nonparametric Statistics, Randomized Controlled Trials, Evidence, Networks
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
Cope, Shannon; Chan, Keith; Jansen, Jeroen P. – Research Synthesis Methods, 2020
Background: Network meta-analysis (NMA) of survival data with a multidimensional treatment effect has been introduced as an alternative to NMA based on the proportional hazards assumption. However, these flexible models have some limitations, such as the use of an approximate likelihood based on discrete hazards, rather than a likelihood for…
Descriptors: Multivariate Analysis, Meta Analysis, Network Analysis, Models
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
Albanese, Emiliano; Bütikofer, Lukas; Armijo-Olivo, Susan; Ha, Christine; Egger, Matthias – Research Synthesis Methods, 2020
Background: There is an agreement that the methodological quality of randomized trials should be assessed in systematic reviews, but there is a debate on how this should be done. We conducted a construct validation study of the Physiotherapy Evidence Database (PEDro) scale, which is widely used to assess the quality of trials in physical therapy…
Descriptors: Construct Validity, Physical Therapy, Item Response Theory, Factor Analysis
Schünemann, Holger J.; Tugwell, Peter; Reeves, Barnaby C.; Akl, Elie A.; Santesso, Nancy; Spencer, Frederick A.; Shea, Beverley; Wells, George; Helfand, Mark – Research Synthesis Methods, 2013
The terms applicability, generalizability, external validity and transferability are related, sometimes used interchangeably and have in common that they lack a clear and consistent definition in the classic epidemiological literature. However, all of these terms generally describe one overarching theme: whether or not available research evidence…
Descriptors: Intervention, Randomized Controlled Trials, Literature Reviews, Comparative Analysis
Verde, Pablo E.; Ohmann, Christian – Research Synthesis Methods, 2015
Researchers may have multiple motivations for combining disparate pieces of evidence in a meta-analysis, such as generalizing experimental results or increasing the power to detect an effect that a single study is not able to detect. However, while in meta-analysis, the main question may be simple, the structure of evidence available to answer it…
Descriptors: Randomized Controlled Trials, Bayesian Statistics, Comparative Analysis, Evidence
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