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PMID: 15677800 Published · ppublish English Journal Article Research Support, U.S. Gov't, P.H.S. Validation Study

Predicting the development of diabetes in older adults: the derivation and validation of a prediction rule.

Diabetes care ·Vol. 28 ·No. 2 ·2005-02-00 ·Pages 404-8

Kanaya AM, Wassel Fyr CL, de Rekeneire N, Shorr RI, Schwartz AV, Goodpaster BH, Newman AB, Harris T, Barrett-Connor E

Abstract

To create a simple prediction rule that could perform as well as the 2-h postchallenge plasma glucose (PCPG) test to predict those at risk for diabetes. We created a prediction rule in one sample and prospectively validated it for incident diabetes in a separate cohort. A cross-sectional analysis with data from the Rancho Bernardo Study (age 67 +/- 11 years) to derive a rule predicting abnormal PCPG >/=140 mg/dl, using demographic, clinical, and laboratory data of nondiabetic participants with fasting plasma glucose (FPG) <126 mg/dl. Data from the Health, Aging and Body Composition study (age 74 +/- 3 years) were used to prospectively validate this rule for incident diabetes and compare it with the predictive ability of the PCPG test. Of 1,549 RBS participants, 514 (33%) had PCPG >/=140 mg/dl. Female sex, age, triglycerides, and FPG were most significantly associated with abnormal PCPG. Based on standardized beta-coefficients, we allotted 1 point for female sex, triglycerides >/=150 mg/dl, or FPG 95-104 mg/dl. Age >/=70 years or FPG 105-115 mg/dl were given 2 points, and FPG 116-125 mg/dl received 3 points. In the validation cohort, this simple prediction rule was as good as the 2-h PCPG test for predicting incident diabetes (C-statistic: 0.71 for both). Advanced age, female sex, FPG, and triglycerides were able to predict adults at risk for diabetes equally well as the 2-h PCPG test. Using this rule, clinicians may better identify older persons who should receive intensive lifestyle intervention to prevent type 2 diabetes.

MeSH Terms
Aged Aged, 80 and over Cross-Sectional Studies Diabetes Mellitus, Type 2/diagnosis,epidemiology,prevention & control Female Glucose Intolerance/diagnosis,epidemiology,prevention & control Humans Incidence Logistic Models Male Middle Aged Multivariate Analysis Predictive Value of Tests Prospective Studies ROC Curve Risk Factors
Authors & Affiliations
9 authors, click to expand affiliations / ORCID
Kanaya Alka M
Department of Medicine and Epidemiology and Biostatics, University of California, San Francisco, California 94115, USA. [email protected]
Wassel Fyr Christina L
de Rekeneire Nathalie
Shorr Ronald I
Schwartz Ann V
Goodpaster Bret H
Newman Anne B
Harris Tamara
Barrett-Connor Elizabeth
Article Info
Journal
Diabetes care
Abbr.
Diabetes Care
ISSN
0149-5992
Published
2005-02-00
Pages
404-8
Language
English
Region
United States
NLM ID
7805975
Subset
IM
Grants
NIAMS NIH HHS · 5 K12 AR47659 · United States
NIA NIH HHS · 5R01 AG07181 · United States
NIDDK NIH HHS · 5R01 DK31801 · United States
NIA NIH HHS · N01-AG-6-2101 · United States
NIA NIH HHS · N01-AG-6-2103 · United States
NIA NIH HHS · N01-AG-6-2106 · United States
NIA NIH HHS · P30-AG15272 · United States
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