Do
We Need the Oral Glucose Tolerance Test to Identify Persons at
High Risk for Type 2 Diabetes?
Persons
at high risk for diabetes mellitus are better identified by using
a simple prediction model than by relying exclusively on the
results of a 2-hour oral glucose tolerance test
The
standard method of identifying persons at high risk for type 2
diabetes mellitus involves detection of impaired glucose
tolerance, which requires a costly and inconvenient 2-hour oral
glucose tolerance test. Because clinical trials have indicated
that diabetes is preventable by using behavioral or pharmacologic
interventions, less expensive methods of identifying high-risk
persons are needed.
OBJECTIVE:
To determine whether multivariable models are superior to glucose
tolerance tests for identifying persons at high risk for diabetes
mellitus.
DESIGN:
Prospective cohort study. SETTING: San Antonio, Texas.
PARTICIPANTS: 1791 Mexican Americans and 1112 non-Hispanic whites
without diabetes at baseline who were randomly selected from
census tracts. MEASUREMENTS: Medical history; body mass index;
blood pressure; fasting and 2-hour plasma glucose levels; fasting
serum total, low-density lipoprotein, and high-density lipoprotein
cholesterol levels; and triglyceride level. RESULTS: For
prediction of 7.5-year incidence of type 2 diabetes, the area
under the receiver-operating characteristic (ROC) curve for a
multivariable model involving readily available clinical variables
was significantly (P < 0.001) greater than the area under the
ROC curve for the 2-hour glucose value alone (84.3% vs. 77.5%).
Impaired glucose tolerance represents a single point on the latter
curve. Adding the 2-hour glucose measurement to the multivariable
model increased the area under its ROC curve, but only from 84.3%
to 85.7%.
CONCLUSION:
Persons at high risk for diabetes mellitus are better identified
by using a simple prediction model than by relying exclusively on
the results of a 2-hour oral glucose tolerance test. Although
adding the 2-hour glucose variable to the model enhanced
prediction, the resulting slight improvement entails greater cost
and inconvenience.
Ann
Intern Med
2002 Apr 16;136(8):575-81
