The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Computer Modeling of Diabetes and Its Complications
Abstract
Computer simulation models are mathematical equations combined in a structured framework to represent some real or hypothetical system. One of their uses is to allow the projection of short-term data from clinical trials to evaluate clinical outcomes and costs over a long-term period. This technology is becoming increasingly important to assist decision making in modern medicine in situations where there is a paucity of long-term clinical trial data, as recently acknowledged in the American Diabetes Association Consensus Panel Guidelines for Computer Modeling of Diabetes and its Complications. The Mount Hood Challenge Meetings provide a forum for computer modelers of diabetes to discuss and compare models and identify key areas of future development to advance the field. The Fourth Mount Hood Challenge in 2004 was the first meeting of its kind to ask modelers to perform simulations of outcomes for patients in published clinical trials, allowing comparison against “real life” data. Eight modeling groups participated in the challenge. Each group was given three of the following challenges: to simulate a trial of type 2 diabetes (CARDS [Collaborative Atorvastatin Diabetes Study]); to simulate a trial of type 1 diabetes (DCCT [Diabetes Control and Complications Trial]); and to calculate outcomes for a hypothetical, precisely specified patient (cross-model validation). The results of the models varied from each other and for methodological reasons, in some cases, from the published trial data in important ways. This approach of performing systematic comparisons and validation exercises has enabled the identification of key differences among the models, as well as their possible causes and directions for improvement in the future.
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Model uncertainty, data mining and statistical inference
Chatfield, C. (1995) · Journal of the Royal Statistical Society. Series A (Statistics in Society) · doi:10.2307/2983440 · Cited by 1,103
The UKPDS risk engine: a model for the risk of coronary heart disease in Type II diabetes (UKPDS 56)
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Self-citationThe Effect of Intensive Diabetes Therapy on the Development and Progression of Neuropathy
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Self-citationScreening for type 2 diabetes mellitus: a cost-effectiveness analysis
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Cited by
Hayes, A. J., Leal, J., Gray, A. M., Holman, R. R., & Clarke, P. M. (2013) · Diabetologia · doi:10.1007/s00125-013-2940-y · Cited by 495
Eddy, D. M., Hollingworth, W., Caro, J. J., Tsevat, J., McDonald, K. M., & Wong, J. B. (2012) · Value in Health · doi:10.1016/j.jval.2012.04.012 · Cited by 466
Kahn, R., Alperin, P., Eddy, D., Borch-Johnsen, K., Buse, J., Feigelman, J., Gregg, E., Holman, R. R., Kirkman, M. S., Stern, M., et al. (2010) · The Lancet · doi:10.1016/s0140-6736(09)62162-0 · Cited by 287
Screening for coronary artery disease in patients with diabetes
Bax, J. J., Young, L. H., Frye, R. L., Bonow, R. O., Steinberg, H. O., & Barrett, E. J. (2007) · Diabetes Care · doi:10.2337/dc07-9927 · Cited by 251
Basu, S., Sussman, J. B., Berkowitz, S. A., Hayward, R. A., & Yudkin, J. S. (2017) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(17)30221-8 · Cited by 206
Metadata
- Authors
- The Mount Hood 4 Modeling Group
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2007-06-01
- Volume
- 30
- Issue
- 6
- Pages
- 1638-1646
- ISSN
- 0149-5992
- 1935-5548
- OpenAlex
- W2271136532
- Cited by
- 199
- References
- 9
- FWCI
- 28.96
- Type
- journal article
- Language
- en
- Open access
- closed
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