Evidence map›Paper›PMID 42153314›Full record

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.

Gian Luca Di Tanna, Niklaus Meier, Matthias Schwenkglenks

Abstract readComment
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Gian Luca Di TannaUniversity of Applied Sciences and Arts of Southern Switzerland - SUPSI, Lugano, Switzerland.ORCID 0000-0002-5470-3567
Niklaus MeierInstitute of Health Economics and Health Policy, Bern University of Applied Sciences, Bern, Switzerland.ORCID 0009-0008-4099-355X
Matthias SchwenkglenksHealth Economics Facility, Department of Public Health, University of Basel, Basel, Switzerland.ORCID 0000-0001-7217-1173

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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).

Indexed as

Cost-Effectiveness AnalysisMeta-Analysis as TopicModels, StatisticalHumanscombinabilitycost‐effectiveness analysisdata harmonizationincremental cost‐effectiveness ratiometa‐analysissystematic review of economic evaluation

Identifiers

PMID42153314
PMCPMC13184790

What OpenQuestion holds

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Registered trials

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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.