What determines the cost-effectiveness of diabetes screening?
Open accessAbstract
Aims/hypothesis The cost-effectiveness of screening for diabetes is unknown but has been modelled previously. None of these models has taken account of uncertainty. We aimed to describe these uncertainties in a model where the outcome was CHD risk.Subjects and methods Our model used population data from the Danish Inter99 study, and simulations were run in a theoretical population of 1,000,000 individuals. CHD risk was estimated using the UK Prospective Diabetes Study (UKPDS) risk engine, and risk reduction from published randomised clinical trials. Probabilistic sensitivity analysis was used to provide confidence intervals for modelled outputs. Uncertain parameter values were independently simulated from distributions derived from existing literature and deterministic sensitivity analysis performed using multiple model runs under different strategy choices and using extreme parameter estimates.Results In the least conservative model (low costs and multiplicative risk reduction for combined treatments), the 95% confidence interval of the incremental cost-effectiveness ratio varied from pound23,300-82,000. The major contributors to this uncertainty were treatment risk reduction model parameters: the risk reduction for hypertension treatment and UKPDS risk model intercept. Overall cost-effectiveness ratio was not sensitive to decisions about which groups to screen, nor the costs of screening or treatment. It was strongly affected by assumptions about how treatments combine to reduce risk.Conclusions/interpretation Our model suggests that there is considerable uncertainty about whether or not screening for diabetes would be cost-effective. The most important but uncertain parameter is the effect of treatment. In addition to directly influencing current policy decisions, health care modelling can identify important unknown or uncertain parameters that may be the target of future research.
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Modeling run on 1 x 10^6 individuals suggests considerable uncertainty as to whether screening for diabetes would be cost-effective.
“Modeling run on 1 x 10 6 individuals suggests considerable uncertainty as to whether screening for diabetes would be cost-effective (34).”
From Guidelines and recommendations for laboratory analysis in the diagnosis and management of diabetes mellitus (2011) · cites this paper as [34]
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- Authors
- Glümer, C., Yuyun, M., Griffin, S., Farewell, D., Spiegelhalter, D., Kinmonth, A. L., & Wareham, N. J.
- Affiliations
- MRC Elsie Widdowson Laboratory (GB)
- Lancaster University (GB)
- MRC Biostatistics Unit (GB)
- University of Cambridge (GB)
- Corresponding author
- Wareham, N. J.
- Venue
- Diabetologia
- Published
- 2006-04-26
- Volume
- 49
- Issue
- 7
- Pages
- 1536-1544
- ISSN
- 0012-186X (ISSN-L)
- 1432-0428
- OpenAlex
- W2163398628
- Semantic Scholar
- 2ec49f63d285965b3e096e46361dd6ffe1d0eb76
- Cited by
- 54
- References
- 36
- Citations by year
- 2023: 2 · 2022: 1 · 2020: 1 · 2018: 4 · 2017: 1 · 2016: 1 · 2015: 3 · 2014: 2 · 2013: 3 · 2012: 4
- FWCI
- 13.55
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Diabetologia (publishedVersion)
- PubMed (publishedVersion)
- ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
- Funders
- Hjerteforeningen
- Sundhed og Sygdom, Det Frie Forskningsråd
- Novo Nordisk
- Augustinus Fonden
- Diabetesforeningen
- Medical Research Council
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Keywords
- diabetes screening, cost-effectiveness, coronary heart disease risk, uncertainty analysis, probabilistic sensitivity analysis, antihypertensive therapy, UKPDS risk engine
- MeSH terms
- Adult, Cost-Benefit Analysis, Diabetes Mellitus, Type 2, Female, Humans, Male, Mass Screening, Middle Aged, Models, Theoretical, Monte Carlo Method, Sensitivity and Specificity
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