Diabetes Care
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Published online May 28, 2008
Diabetes Care 31:1670-1671, 2008
DOI: 10.2337/dc08-0521
© 2008 by the American Diabetes Association
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
dc08-0521v1
31/8/1670    most recent
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Google Scholar
Right arrow Articles by Stern, M.
Right arrow Articles by Kahn, R.
PubMed
Right arrow PubMed Citation
Right arrow Articles by Stern, M.
Right arrow Articles by Kahn, R.
Social Bookmarking
Add to CiteULike   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

Cardiovascular and Metabolic Risk
Original Research

Validation of Prediction of Diabetes by the Archimedes Model and Comparison With Other Predicting Models

Michael Stern, MD1, Ken Williams, MS2, David Eddy, MD, PHD3 and Richard Kahn, PHD4

1 Division of Clinical Epidemiology, University of Texas Health Science Center, San Antonio, Texas
2 KenAnCo Biostatistics, San Antonio, Texas
3 Archimedes, Inc., San Francisco, California
4 American Diabetes Association, Alexandria, Virginia

Corresponding author: Richard Kahn, rkahn{at}diabetes.org

OBJECTIVE—To validate the ability of the Archimedes model to accurately predict the risk of developing diabetes in individuals.

RESEARCH DESIGN AND METHODS—Subjects were randomly selected from the San Antonio Heart Study population. The area under the receiver operating characteristic (aROC) curve derived from the Archimedes model was calculated and also compared with the aROCs from two published multiple logistic regression models designed to estimate diabetes risk.

RESULTS—The aROC for the Archimedes model was 0.818 (95% CI 0.739–0.899) compared with aROCs of 0.869 (0.801–0.936) and 0.870 (0.802–0.937) for the two logistic regression models, respectively. Risk estimates from the logistic models were highly correlated with the estimates derived from the Archimedes model.

CONCLUSIONS—The Archimedes model predicts individual diabetes risk with a high level of sensitivity and specificity, comparable with that of models designed specifically for that purpose. Unlike the latter models, Archimedes also predicts the risk of numerous other health outcomes.


Add to CiteULike CiteULike   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Diabetes Diabetes Care Clinical Diabetes Diabetes Spectrum
Copyright © 2008 by the American Diabetes Association.