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Landan Zhang; Sylwia Bujkiewicz; Dan Jackson – Research Synthesis Methods, 2024
Simulated treatment comparison (STC) is an established method for performing population adjustment for the indirect comparison of two treatments, where individual patient data (IPD) are available for one trial but only aggregate level information is available for the other. The most commonly used method is what we call 'standard STC'. Here we fit…
Descriptors: Simulation, Patients, Outcomes of Treatment, Comparative Analysis
Landan Zhang; Dan Jackson – Research Synthesis Methods, 2024
A recent paper proposed an alternative weighting scheme when performing matching-adjusted indirect comparisons. This alternative approach follows the conventional one in matching the covariate means across two studies but differs in that it maximizes the effective sample size when doing so. The appendix of this paper showed, assuming there is one…
Descriptors: Comparative Analysis, Medical Research, Sample Size, Research Methodology
Remiro-Azócar, Antonio; Heath, Anna; Baio, Gianluca – Research Synthesis Methods, 2023
We examine four important considerations in the development of covariate adjustment methodologies for indirect treatment comparisons. First, we consider potential advantages of weighting versus outcome modeling, placing focus on bias-robustness. Second, we outline why model-based extrapolation may be required and useful, in the specific context of…
Descriptors: Medical Research, Outcomes of Treatment, Comparative Analysis, Barriers
Cheng, David; Tchetgen, Eric Tchetgen; Signorovitch, James – Research Synthesis Methods, 2023
Matching-adjusted indirect comparison (MAIC) enables indirect comparisons of interventions across separate studies when individual patient-level data (IPD) are available for only one study. Due to its similarity with propensity score weighting, it has been speculated that MAIC can be combined with outcome regression models in the spirit of…
Descriptors: Comparative Analysis, Robustness (Statistics), Intervention, Patients
Shijie Ren; Sa Ren; Nicky J. Welton; Mark Strong – Research Synthesis Methods, 2024
Population-adjusted indirect comparisons, developed in the 2010s, enable comparisons between two treatments in different studies by balancing patient characteristics in the case where individual patient-level data (IPD) are available for only one study. Health technology assessment (HTA) bodies increasingly rely on these methods to inform funding…
Descriptors: Medical Research, Outcomes of Treatment, Standards, Safety
Li, Hua; Shih, Ming-Chieh; Tu, Yu-Kang – Research Synthesis Methods, 2023
Component network meta-analysis (CNMA) compares treatments comprising multiple components and estimates the effects of individual components. For network meta-analysis, a standard network plot with nodes for treatments and edges for direct comparisons between treatments is drawn to visualize the evidence structure and the connections between…
Descriptors: Networks, Meta Analysis, Graphs, Comparative Analysis
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
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
Noma, Hisashi; Hamura, Yasuyuki; Sugasawa, Shonosuke; Furukawa, Toshi A. – Research Synthesis Methods, 2023
Network meta-analysis has played an important role in evidence-based medicine for assessing the comparative effectiveness of multiple available treatments. The prediction interval has been one of the standard outputs in recent network meta-analysis as an effective measure that enables simultaneous assessment of uncertainties in treatment effects…
Descriptors: Intervals, Meta Analysis, Evidence Based Practice, Comparative Analysis
Liu, Shifeng; Bourgeois, Florence T.; Dunn, Adam G. – Research Synthesis Methods, 2022
A substantial proportion of trial registrations are not linked to corresponding published articles, limiting analyses and new tools. Our aim was to develop a method for finding articles reporting the results of trials that are registered on ClinicalTrials.gov when they do not include metadata links. We used a set of 27,280 trial registration and…
Descriptors: Medical Research, Web Sites, Identification, Computational Linguistics
Remiro-Azócar, Antonio; Heath, Anna; Baio, Gianluca – Research Synthesis Methods, 2022
Population adjustment methods such as matching-adjusted indirect comparison (MAIC) are increasingly used to compare marginal treatment effects when there are cross-trial differences in effect modifiers and limited patient-level data. MAIC is based on propensity score weighting, which is sensitive to poor covariate overlap and cannot extrapolate…
Descriptors: Patients, Medical Research, Comparative Analysis, Outcomes of Treatment
Burkholder, Leslie – Theory and Research in Education, 2021
Does the moral requirement that medical research comparing the effectiveness of two treatment methods be done only when there is community level equipoise also apply to research in teaching and learning comparing the effectiveness of two instructional methods? This article argues that it does. It evaluates three claims that the requirement does…
Descriptors: Ethics, Moral Values, Teaching Methods, Instructional Effectiveness
Memon, Amina; Connolly, Deborah; Brewin, Chris R.; Meyer, Thomas; Seidel, Julia; Anderson, Shelbie; Rijkeboer, Marleen; Arntz, Arnoud – Applied Cognitive Psychology, 2021
Adults with posttraumatic stress disorder from childhood trauma (ch-PTSD) described their 'worst' traumatic event (a single or repeated event) pre-post treatment for PTSD during an international clinical trial. The memory reports were coded for specificity ("Episodic" vs. "General") and level of detail. Repeated event (RE)…
Descriptors: Posttraumatic Stress Disorder, Trauma, Memory, Adults
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
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