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Lu Qin; Shishun Zhao; Wenlai Guo; Tiejun Tong; Ke Yang – Research Synthesis Methods, 2024
The application of network meta-analysis is becoming increasingly widespread, and for a successful implementation, it requires that the direct comparison result and the indirect comparison result should be consistent. Because of this, a proper detection of inconsistency is often a key issue in network meta-analysis as whether the results can be…
Descriptors: Meta Analysis, Network Analysis, Bayesian Statistics, Comparative Analysis
Jennifer L. Proper; Haitao Chu; Purvi Prajapati; Michael D. Sonksen; Thomas A. Murray – Research Synthesis Methods, 2024
Drug repurposing refers to the process of discovering new therapeutic uses for existing medicines. Compared to traditional drug discovery, drug repurposing is attractive for its speed, cost, and reduced risk of failure. However, existing approaches for drug repurposing involve complex, computationally-intensive analytical methods that are not…
Descriptors: Network Analysis, Meta Analysis, Prediction, Drug Therapy
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
Uhlmann, Lorenz; Jensen, Katrin; Kieser, Meinhard – Research Synthesis Methods, 2017
Network meta-analysis is becoming a common approach to combine direct and indirect comparisons of several treatment arms. In recent research, there have been various developments and extensions of the standard methodology. Simultaneously, cluster randomized trials are experiencing an increased popularity, especially in the field of health services…
Descriptors: Bayesian Statistics, Network Analysis, Meta Analysis, Randomized Controlled Trials
Leahy, Joy; Walsh, Cathal – Research Synthesis Methods, 2019
If IPD is available for some or all trials in a network meta-analysis (NMA), then incorporating this IPD into an NMA is routinely considered to be preferable. However, the situation often arises where a researcher has IPD for trials concerning a particular treatment (eg, from a sponsor) but none for other trials. Therefore, one can reweight the…
Descriptors: Comparative Analysis, Meta Analysis, Bayesian Statistics, Network Analysis
Zhao, Hong; Hodges, James S.; Carlin, Bradley P. – Research Synthesis Methods, 2017
Network meta-analysis (NMA) combines direct and indirect evidence comparing more than 2 treatments. Inconsistency arises when these 2 information sources differ. Previous work focuses on inconsistency detection, but little has been done on how to proceed after identifying inconsistency. The key issue is whether inconsistency changes an NMA's…
Descriptors: Meta Analysis, Networks, Hierarchical Linear Modeling, Bayesian Statistics
Freeman, Suzanne C.; Carpenter, James R. – Research Synthesis Methods, 2017
Network meta-analysis (NMA) combines direct and indirect evidence from trials to calculate and rank treatment estimates. While modelling approaches for continuous and binary outcomes are relatively well developed, less work has been done with time-to-event outcomes. Such outcomes are usually analysed using Cox proportional hazard (PH) models.…
Descriptors: Bayesian Statistics, Network Analysis, Meta Analysis, Data
Network Meta-Analysis of Disconnected Networks: How Dangerous Are Random Baseline Treatment Effects?
Béliveau, Audrey; Goring, Sarah; Platt, Robert W.; Gustafson, Paul – Research Synthesis Methods, 2017
In network meta-analysis, the use of fixed baseline treatment effects (a priori independent) in a contrast-based approach is regularly preferred to the use of random baseline treatment effects (a priori dependent). That is because, often, there is not a need to model baseline treatment effects, which carry the risk of model misspecification.…
Descriptors: Risk, Network Analysis, Meta Analysis, Outcomes of Treatment