Evidence map›Paper›PMID 16623946›Full record

ArticleBMC health services research2006

Using and interpreting cost-effectiveness acceptability curves: an example using data from a trial of management strategies for atrial fibrillation.

Elisabeth Fenwick, Deborah A Marshall, Adrian R Levy, Graham Nichol

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC health services research, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 142 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
142citing papers in PubMed, 2 pooled it
30.7field-weighted citation impact, top 1% of its field
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

142 citing papers in PubMed, 2 syntheses or guidelines pooled it, 278 citations in OpenAlex.

  1. Economic Evaluations of Pharmacologic Treatment for Opioid Use Disorder: A Systematic Literature Review.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2021
    Pooled it
  2. Cost-effectiveness analysis of the first-line EGFR-TKIs in patients with non-small cell lung cancer harbouring EGFR mutations.The European journal of health economics : HEPAC : health economics in prevention and care · 2020
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  7. Cost-effectiveness analysis of procalcitonin and lung ultrasonography guided antibiotic prescriptions in primary care.The European journal of health economics : HEPAC : health economics in prevention and care · 2025
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  19. Physiotherapy rehabilitation for osteoporotic vertebral fracture-a randomised controlled trial and economic evaluation (PROVE trial).Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2020
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82 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 4 institutions in 3 countries.

Elisabeth FenwickPublic Health and Health Policy, University of Glasgow, Glasgow, UK. e.fenwick@clinmed.gla.ac.uk
Deborah A Marshall
Adrian R Levy
Graham Nichol
Harborview Medical Center · USPublic Health Scotland · GBSt. Joseph’s Healthcare Hamilton · CAUniversity of British Columbia · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe cost-effectiveness acceptability curve (CEAC) is a method for summarizing the uncertainty in estimates of cost-effectiveness. The CEAC, derived from the joint distribution of costs and effects, illustrates the (Bayesian) probability that the data are consistent with a true cost-effectiveness ratio falling below a specified ceiling ratio. The objective of the paper is to illustrate how to construct and interpret a CEAC.

methodsA retrospective cost-effectiveness analysis of the Atrial Fibrillation Follow-up Investigation of Rhythm Management (AFFIRM) randomized controlled trial with 4060 patients followed for 3.5 years. The target population was patients with atrial fibrillation who were 65 years of age or had other risk factors for stroke or death similar to those enrolled in AFFIRM. The intervention involved the management of patients with atrial fibrillation with antiarrhythmic drugs (rhythm-control) compared with drugs that control heart rate (rate-control). Measurements of mean survival, mean costs and incremental cost-effectiveness were made. The uncertainty surrounding the estimates of cost-effectiveness was illustrated through a cost-effectiveness acceptability curve.

resultsThe base case point estimate for the difference in effects and costs between rate and rhythm-control is 0.08 years (95% CI: -0.1 years to 0.24 years) and -5,077 US dollars (95% CI: -1,100 dollars to -11,006 dollars). The CEAC shows that the decision uncertainty surrounding the adoption of rate-control strategies is less than 1.7% regardless of the maximum acceptable ceiling ratio. Thus, there is very little uncertainty surrounding the decision to adopt rate-control compared to rhythm-control for patients with atrial fibrillation from a resource point of view.

conclusionThe CEAC is straightforward to calculate, construct and interpret. The CEAC is useful to a decision maker faced with the choice of whether or not to adopt a technology because it provides a measure of the decision uncertainty surrounding the choice.

Indexed as

Bayes TheoremUncertaintyAgedAnti-Arrhythmia AgentsAnticoagulantsAtrial FibrillationCardiovascular AgentsConfidence IntervalsCost-Benefit AnalysisHeart RateHumansRandomized Controlled Trials as TopicSurvival AnalysisTechnology Assessment, BiomedicalTreatment OutcomeAnti-Arrhythmia AgentsAnticoagulantsCardiovascular Agents

Identifiers

PMID16623946
PMCPMC1538588
OpenAlexW1562415841

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.