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Selecting the optimal risk threshold of diabetes risk scores to identify high-risk individuals for diabetes prevention: a cost-effectiveness analysis

  • Mühlenbruch, Kristin1, 2
  • Zhuo, Xiaohui3
  • Bardenheier, Barbara3
  • Shao, Hui3
  • Laxy, Michael4, 2
  • Icks, Andrea5, 6, 2
  • Zhang, Ping3
  • Gregg, Edward W.3
  • Schulze, Matthias B.1, 2, 7
  • 1 German Institute of Human Nutrition Potsdam-Rehbruecke,
  • 2 German Center for Diabetes Research (DZD),
  • 3 National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention,
  • 4 Institute of Health Economics and Health Care Management,
  • 5 Institute of Health Services Research and Health Economics, German Diabetes Centre, Leibniz-Centre for Diabetes Research, Düsseldorf, Germany
  • 6 Heinrich-Heine-University,
  • 7 University of Potsdam,
Published Article
Acta Diabetologica
Springer Milan
Publication Date
Nov 19, 2019
DOI: 10.1007/s00592-019-01451-1
PMID: 31745647
PMCID: PMC7093341
PubMed Central


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, 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. Electronic supplementary material The online version of this article (10.1007/s00592-019-01451-1) contains supplementary material, which is available to authorized users.

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