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Population screening for glucose intolerant subjects using decision tree analyses

K J Barriga1, R F Hamman, S Hoag

  • 1Department of Preventive Medicine and Biometrics, University of Colorado Health Sciences Center, Denver 80262, USA.

Diabetes Research and Clinical Practice
|October 1, 1996
PubMed
Summary
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This study developed a preliminary screening method for impaired glucose tolerance (IGT) and undiagnosed non-insulin-dependent diabetes mellitus (NIDDM) using risk indicators and decision tree analysis, reducing the need for oral glucose tolerance tests (OGTTs).

Area of Science:

  • Endocrinology
  • Diabetology
  • Biostatistics

Background:

  • Impaired glucose tolerance (IGT) and non-insulin-dependent diabetes mellitus (NIDDM) require effective screening methods.
  • Oral glucose tolerance tests (OGTTs) are standard but resource-intensive for population-wide screening.

Purpose of the Study:

  • To develop and evaluate a preliminary screening method for IGT and undiagnosed NIDDM.
  • To reduce the number of individuals requiring a full OGTT for diagnosis.

Main Methods:

  • Utilized Classification and Regression Trees (CART) software for decision tree analysis.
  • Examined Hispanic and non-Hispanic white subjects (n=1351) without prior diabetes history.
  • Simulated simultaneous and serial screening approaches using NIDDM risk indicators.

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Main Results:

  • The simultaneous approach using fasting glucose, age, and BMI achieved 91% sensitivity and 55% specificity.
  • The serial approach, starting with age and BMI, then adding fasting glucose and glycohemoglobin, yielded 85% sensitivity and 64% specificity.
  • CART models identified subgroups at increased risk for glucose tolerance abnormalities.

Conclusions:

  • Preliminary screening for IGT and undiagnosed NIDDM is feasible using simple indicators.
  • CART models offer acceptable sensitivity and specificity for preliminary diabetes risk assessment.
  • This approach can optimize the use of OGTTs in clinical and research settings.