Evidence map›Paper›PMID 32729091›Full record

ArticlePharmacoEconomics2020

Taking the Analysis of Trial-Based Economic Evaluations to the Next Level: The Importance of Accounting for Clustering.

Mohamed El Alili, Johanna M van Dongen, Keith S Goldfeld, Martijn W Heymans, Maurits W van Tulder, Judith E Bosmans

Abstract read
In one paragraph

Article in PharmacoEconomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–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

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  6. Lower urinary tract symptoms in men: the TRIUMPH cluster RCT.Health technology assessment (Winchester, England) · 2024
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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

6 authors.

Mohamed El AliliDepartment of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands. m.elalili@vu.nl.ORCID http://orcid.org/0000-0002-6341-7976
Johanna M van DongenDepartment of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands.
Keith S GoldfeldDepartment of Population Health, NYU School of Medicine, New York, NY, USA.
Martijn W HeymansDepartment of Epidemiology and Biostatistics, Amsterdam UMC, Location VU, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.
Maurits W van TulderDepartment of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands.
Judith E BosmansDepartment of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe aim of this study was to assess the performance and impact of multilevel modelling (MLM) compared with ordinary least squares (OLS) regression in trial-based economic evaluations with clustered data.

methodsThree thousand datasets with balanced and unbalanced clusters were simulated with correlation coefficients between costs and effects of - 0.5, 0, and 0.5, and intraclass correlation coefficients (ICCs) varying between 0.05 and 0.30. Each scenario was analyzed using both MLM and OLS. Statistical uncertainty around MLM and OLS estimates was estimated using bootstrapping. Performance measures were estimated and compared between approaches, including bias, root mean squared error (RMSE) and coverage probability. Cost and effect differences, and their corresponding confidence intervals and standard errors, incremental cost-effectiveness ratios, incremental net-monetary benefits and cost-effectiveness acceptability curves were compared.

resultsCost-effectiveness outcomes were similar between OLS and MLM. MLM produced larger statistical uncertainty and coverage probabilities closer to nominal levels than OLS. The higher the ICC, the larger the effect on statistical uncertainty between MLM and OLS. Significant cost-effectiveness outcomes as estimated by OLS became non-significant when estimated by MLM. At all ICCs, MLM resulted in lower probabilities of cost effectiveness than OLS, and this difference became larger with increasing ICCs. Performance measures and cost-effectiveness outcomes were similar across scenarios with varying correlation coefficients between costs and effects.

conclusionsAlthough OLS produced similar cost-effectiveness outcomes, it substantially underestimated the amount of variation in the data compared with MLM. To prevent suboptimal conclusions and a possible waste of scarce resources, it is important to use MLM in trial-based economic evaluations when data are clustered.

Indexed as

Cluster AnalysisBiasCost-Benefit AnalysisHumansLeast-Squares AnalysisUncertainty

Identifiers

PMID32729091
PMCPMC7546992

What OpenQuestion holds

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LicenceCC BY-NC
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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.