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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References
- Global and societal implications of the diabetes epidemic.Nature. 2001; 414: 782-787
- Global estimates of the prevalence of diabetes for 2010 and 2030.Diabetes Res Clin Pract. 2010; 87: 4-14
- Onset of NIDDM occurs at least 4–7 yr before clinical diagnosis.Diabetes Care. 1992; 15: 815-819
- Subclinical states of glucose intolerance and risk of death in the U.S.Diabetes Care. 2001; 24: 447-453
- Age at initiation and frequency of screening to detect type 2 diabetes: a cost-effectiveness analysis.Lancet. 2010; 375: 1365-1374
- Performance of a predictive model to identify undiagnosed diabetes in a health care setting.Diabetes Care. 1999; 22: 213-219
- Screening for type 2 diabetes and impaired glucose metabolism.Diabetes Care. 2004; 27: 367-371
- A Danish diabetes risk score for targeted screening: the Inter99 study.Diabetes Care. 2004; 27: 727-733
- Diabetes risk score: towards earlier detection of type 2 diabetes in general practice.Diabetes Metab Res Rev. 2000; 16: 164-171
- Diabetes risk calculator: a simple tool for detecting undiagnosed diabetes and pre-diabetes.Diabetes Care. 2008; 31: 1040-1045
- A new and simple questionnaire to identify people at increased risk for undiagnosed diabetes.Diabetes Care. 1995; 18: 382-387
- Performance of an NIDDM screening questionnaire based on symptoms and risk factors.Diabetes Care. 1997; 20: 491-496
- A simple risk score to identify Southern Chinese at high risk for diabetes.Diabet Med. 2010; 27: 644-649
- A simplified Indian diabetes risk score for screening for undiagnosed diabetic subjects.JAPI. 2005; 53: 759-763
- Derivation and validation of diabetes risk score for urban Asian Indians.Diabetes Res Clin Pract. 2005; 70: 63-70
- Diabetes risk score in Oman: a tool to identify prevalent type 2 diabetes among Arabs of the Middle East.Diabetes Res Clin Pract. 2007; 77: 438-444
- A multivariate logistic regression equation to screen for dysglycaemia: development and validation.Diabet Med. 2005; 22: 599-605
- Risk scores for type 2 diabetes can be applied in some populations but not all.Diabet Care. 2006; 29: 410-414
- Age, body mass index and type 2 diabetes-associations modified by ethnicity.Diabetologia. 2003; 46: 1063-1070
- Pathophysiology and aetiology of impaired fasting glycaemia and impaired glucose tolerance: does it matter for prevention and treatment of type 2 diabetes?.Diabetologia. 2009; 52: 1714-1723
- Targeted screening for undiagnosed diabetes reduces the number of diagnostic tests. Inter99(8).Diabet Med. 2004; 21: 874-880
- DETECT-2: early detection of type 2 diabetes and IGT.Diabetes Voice. 2003; 48: 11-13
Definition, diagnosis and classification of diabetes mellitus and its complications. Report of a WHO Consultation, Part 1: Diagnosis and classification of diabetes mellitus. 1999. World Health Organisation, Geneva 1999
- Classification and regression trees.Wadsworth, California1984
- An introduction to the bootstrap.Chapman & Hall, New York1993
- Classification and regression tree analysis in public health: methodological review and comparison with logistic regression.Ann Behav Med. 2003; 26: 172-181
- Unbiased recursive partitioning: a conditional inference framework.J Comput Graph Stat. 2006; 15: 651-674
- Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.Biometrics. 1988; 44: 837-845
- Use of glycated haemoglobin (HbA1c) in the diagnosis of diabetes mellitus.World Health Organisation, Geneva2011
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.