ArticleStatistics in medicine2022
Bayesian models for aggregate and individual patient data component network meta-analysis.
Article in Statistics in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.
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Who cites it
11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 37 citations in OpenAlex.
- Effectiveness of prehabilitation for patients with colorectal surgery: a systematic review and network meta-analysis.Updates in surgery · 2026Pooled it
- Efficacy and safety of neoadjuvant therapies for high-risk and locally advanced prostate cancer in older adults: a systematic review and network meta-analysis.Frontiers in oncology · 2026Pooled it
- Improving the adoption of a school-based nutrition program: findings from a collaborative network of randomised trials.Implementation science : IS · 2025Trial
- Effects of combined resistance and plyometric training modalities on vertical jump and sprint: a systematic review and network meta-analysis.BMC sports science, medicine & rehabilitation · 2026Article
- Deconstructing resuscitation training for healthcare providers: a protocol for a component network meta-analysis.BMJ open · 2025Article
- Factors associated with the effectiveness of interventions to prevent obesity in children: a synthesis of evidence from 204 randomised trials.BMJ public health · 2025Article
- A Complex Meta-Regression Model to Identify Effective Features of Interventions From Multi-Arm, Multi-Follow-Up Trials.Statistics in medicine · 2024Article
- Model selection for component network meta-analysis in connected and disconnected networks: a simulation study.BMC medical research methodology · 2023Article
- Article
- Comparative effectiveness of oral antibiotics, probiotics, prebiotics, and synbiotics in the prevention of postoperative infections in patients undergoing colorectal surgery: A network meta-analysis.International wound journal · 2023Review
- Bayesian models for aggregate and individual patient data component network meta-analysis.Statistics in medicine · 2022Article
Corrections and comments
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Authors and funding
8 authors at 6 institutions in 8 countries.
Funding
Abstract
Network meta-analysis can synthesize evidence from studies comparing multiple treatments for the same disease. Sometimes the treatments of a network are complex interventions, comprising several independent components in different combinations. A component network meta-analysis (CNMA) can be used to analyze such data and can in principle disentangle the individual effect of each component. However, components may interact with each other, either synergistically or antagonistically. Deciding which interactions, if any, to include in a CNMA model may be difficult, especially for large networks with many components. In this article, we present two Bayesian CNMA models that can be used to identify prominent interactions between components. Our models utilize Bayesian variable selection methods, namely the stochastic search variable selection and the Bayesian LASSO, and can benefit from the inclusion of prior information about important interactions. Moreover, we extend these models to combine data from studies providing aggregate information and studies providing individual patient data (IPD). We illustrate our models in practice using three real datasets, from studies in panic disorder, depression, and multiple myeloma. Finally, we describe methods for developing web-applications that can utilize results from an IPD-CNMA, to allow for personalized estimates of relative treatment effects given a patient's characteristics.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.