ArticleStatistics in medicine2026
Comment on "Meta-Analysis of Cost-Effectiveness" by Bang and Zhao: Combinability, Joint Modeling, and a Two-Stage Framework for Cost-Effectiveness Analysis Synthesis.
Article in Statistics in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Meta-Analysis of Incremental Net Benefit from Trial-Based Health Economic Evaluations in R: A Tutorial.PharmacoEconomics · 2026Review
Corrections and comments
- Comment on
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bang and Zhao address an important methodological gap by proposing meta-analytic methods for cost-effectiveness analysis (CEA) based on separate pooling of incremental costs (ΔC) and incremental effectiveness (ΔE), with summaries displayed on the cost-effectiveness plane. We share the aim of expanding the toolkit for CEA synthesis; however, we believe that several issues need clarification before the proposal can serve as a general blueprint. First, the two motivating examples appear not to satisfy the key combinability criteria described by Shields and Elvidge. Second, the proposal does not incorporate the data harmonization steps recommended for the meta-analysis of economic evaluations by Bagepally et al. Third, separate univariate pooling does not retain the within-study association between ΔC and ΔE, which complicates the joint interpretation of the pooled ICER and its uncertainty. As a possible way forward, we propose a two-stage framework in which a structured combinability assessment and data harmonization precede any quantitative synthesis, and discuss why joint modeling of (ΔC, ΔE) is preferable to separate univariate pooling. In our view, such a framework provides a more defensible route to pooled ICERs, joint uncertainty summaries, and decision-relevant quantities such as cost-effectiveness acceptability curves (CEACs).
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Registered trials
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