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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
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
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
Nejstgaard, Camilla Hansen; Laursen, David Ruben Teindl; Lundh, Andreas; Hróbjartsson, Asbjørn – Research Synthesis Methods, 2023
We investigated to which degree commercial funding is associated with estimated intervention effects in randomized trials. We included meta-epidemiological studies with published data on the association between commercial funding and results or conclusions of randomized trials. We searched five databases and other sources. We selected one result…
Descriptors: Private Financial Support, Intervention, Randomized Controlled Trials, Literature Reviews
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
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
Evrenoglou, Theodoros; Boutron, Isabelle; Seitidis, Georgios; Ghosn, Lina; Chaimani, Anna – Research Synthesis Methods, 2023
Outputs from living evidence syntheses projects have been used widely during the pandemic by guideline developers to form evidence-based recommendations. However, the needs of different stakeholders cannot be accommodated by solely providing pre-defined non amendable numerical summaries. Stakeholders also need to understand the data and perform…
Descriptors: COVID-19, Pandemics, Meta Analysis, Computer Oriented Programs
Riley, Richard D.; Collins, Gary S.; Hattle, Miriam; Whittle, Rebecca; Ensor, Joie – Research Synthesis Methods, 2023
Before embarking on an individual participant data meta-analysis (IPDMA) project, researchers should consider the power of their planned IPDMA conditional on the studies promising their IPD and their characteristics. Such power estimates help inform whether the IPDMA project is worth the time and funding investment, before IPD are collected. Here,…
Descriptors: Computation, Meta Analysis, Participant Characteristics, Data
Qi, Hongchao; Rizopoulos, Dimitris; Rosmalen, Joost – Research Synthesis Methods, 2023
The meta-analytic-predictive (MAP) approach is a Bayesian method to incorporate historical controls in new trials that aims to increase the statistical power and reduce the required sample size. Here we investigate how to calculate the sample size of the new trial when historical data is available, and the MAP approach is used in the analysis. In…
Descriptors: Sample Size, Computation, Meta Analysis, Bayesian Statistics
Siemens, Waldemar; Meerpohl, Joerg J.; Rohe, Miriam S.; Buroh, Sabine; Schwarzer, Guido; Becker, Gerhild – Research Synthesis Methods, 2022
Using the Hartung-Knapp method and 95% prediction intervals (PIs) in random-effects meta-analyses is recommended by experts but rarely applied. Therefore, we aimed to reevaluate statistically significant meta-analyses using the Hartung-Knapp method and 95% PIs. In this methodological study, three databases were searched from January 2010 to July…
Descriptors: Cancer, Meta Analysis, Medical Research, Patients
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
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)
Proctor, Tanja; Zimmermann, Samuel; Seide, Svenja; Kieser, Meinhard – Research Synthesis Methods, 2022
During drug development, a biomarker is sometimes identified as separating a patient population into those with more and those with less benefit from evaluated treatments. Consequently, later studies might be targeted, while earlier ones are performed in mixed patient populations. This poses a challenge in evidence synthesis, especially if only…
Descriptors: Comparative Analysis, Meta Analysis, Patients, Medical Research
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