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Selecting the optimal risk threshold of diabetes risk scores to identify high-risk individuals for diabetes prevention

  • Aims: Although risk scores to predict type 2 diabetes exist, cost-effectiveness of risk thresholds to target prevention interventions are unknown. We applied cost-effectiveness analysis to identify optimal thresholds of predicted risk to target a low-cost community-based intervention in the USA. Methods: We used a validated Markov-based type 2 diabetes simulation model to evaluate the lifetime cost-effectiveness of alternative thresholds of diabetes risk. Population characteristics for the model were obtained from NHANES 2001-2004 and incidence rates and performance of two noninvasive diabetes risk scores (German diabetes risk score, GDRS, and ARIC 2009 score) were determined in the ARIC and Cardiovascular Health Study (CHS). Incremental cost-effectiveness ratios (ICERs) were calculated for increasing risk score thresholds. Two scenarios were assumed: 1-stage (risk score only) and 2-stage (risk score plus fasting plasma glucose (FPG) test (threshold 100 mg/dl) in the high-risk group). Results: In ARIC and CHS combined, theAims: Although risk scores to predict type 2 diabetes exist, cost-effectiveness of risk thresholds to target prevention interventions are unknown. We applied cost-effectiveness analysis to identify optimal thresholds of predicted risk to target a low-cost community-based intervention in the USA. Methods: We used a validated Markov-based type 2 diabetes simulation model to evaluate the lifetime cost-effectiveness of alternative thresholds of diabetes risk. Population characteristics for the model were obtained from NHANES 2001-2004 and incidence rates and performance of two noninvasive diabetes risk scores (German diabetes risk score, GDRS, and ARIC 2009 score) were determined in the ARIC and Cardiovascular Health Study (CHS). Incremental cost-effectiveness ratios (ICERs) were calculated for increasing risk score thresholds. Two scenarios were assumed: 1-stage (risk score only) and 2-stage (risk score plus fasting plasma glucose (FPG) test (threshold 100 mg/dl) in the high-risk group). Results: In ARIC and CHS combined, the area under the receiver operating characteristic curve for the GDRS and the ARIC 2009 score were 0.691 (0.677-0.704) and 0.720 (0.707-0.732), respectively. The optimal threshold of predicted diabetes risk (ICER < $50,000/QALY gained in case of intervention in those above the threshold) was 7% for the GDRS and 9% for the ARIC 2009 score. In the 2-stage scenario, ICERs for all cutoffs >= 5% were below $50,000/QALY gained. Conclusions: Intervening in those with >= 7% diabetes risk based on the GDRS or >= 9% on the ARIC 2009 score would be cost-effective. A risk score threshold >= 5% together with elevated FPG would also allow targeting interventions cost-effectively.show moreshow less

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Author details:Kristin MühlenbruchORCiD, Xiaohui Zhuo, Barbara Bardenheier, Hui Shao, Michael Laxy, Andrea IcksORCiD, Ping Zhang, Edward W. Gregg, Matthias Bernd SchulzeORCiDGND
DOI:https://doi.org/10.1007/s00592-019-01451-1
ISSN:0001-5563
ISSN:0940-5429
ISSN:1432-5233
Title of parent work (English):Acta Diabetologica
Subtitle (English):a cost-effectiveness analysis
Publisher:Springer
Place of publishing:Mailand
Publication type:Article
Language:English
Date of first publication:2019/11/19
Publication year:2019
Release date:2024/05/07
Tag:clinical prediction rule; cost-effectiveness analysis; diabetes mellitus; lifestyle risk reduction; type 2
Volume:57
Issue:4
Number of pages:8
First page:447
Last Page:454
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Ernährungswissenschaft
DDC classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Peer review:Referiert
Publishing method:Open Access / Gold Open-Access
License (German):License LogoCC-BY - Namensnennung 4.0 International
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