Abstract
Aims
Current risk scores for undiagnosed diabetes are additive in structure. We sought
to derive a globally applicable screening model based on established non-invasive
risk factors for diabetes but with a more flexible structure.
Methods
Data from the DETECT-2 study were used, including 102,058 participants from 38 studies
covering 8 geographical regions worldwide. A global screening model for undiagnosed
diabetes was identified through tree-structured regression analysis. The performance
of the global screening model was evaluated in each of the geographical regions by
receiver operating characteristic (ROC) analysis.
Results
The global screening model included age, height, body mass index, waist circumference
and systolic- and diastolic blood pressure. Area under the ROC curve ranged between
0.64 in North America and 0.76 in Australia and New Zealand. Overall, to identify
75% of the undiagnosed diabetes cases, 49% required further diagnostic testing.
Conclusions
We identified a globally applicable screening model to detect individuals at high
risk of undiagnosed diabetes. The model performed well in most geographical regions,
is simple and requires no calculations. This global screening model may be particularly
helpful in developing countries with no population based data with which to develop
own screening models.
Abbreviations:
BMI (body mass index), WC (waist circumference), DBP (diastolic blood pressure), SBP (systolic blood pressure), AHT (antihypertensive treatment), FHD (family history of diabetes), ROC (receiver operating characteristic), AUC (area under the ROC curve)Keywords
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Article info
Publication history
Published online: December 09, 2011
Accepted:
November 14,
2011
Received in revised form:
November 3,
2011
Received:
September 6,
2011
Footnotes
Identification
Copyright
© 2011 Elsevier Ireland Ltd. Published by Elsevier Inc. All rights reserved.
