title: Predicting the development of diabetes in older adults: the derivation and validation of a prediction rule.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  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.
  
  
  RESULTS
  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).
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Medicine and Epidemiology and Biostatics, University of California, San Francisco, California 94115, USA. alkak@itsa.ucsf.edu
authors.forename: Alka M
authors.initials: AM
authors.lastname: Kanaya
authors.forename: Christina L
authors.initials: CL
authors.lastname: Wassel Fyr
authors.forename: Nathalie
authors.initials: N
authors.lastname: de Rekeneire
authors.forename: Ronald I
authors.initials: RI
authors.lastname: Shorr
authors.forename: Ann V
authors.initials: AV
authors.lastname: Schwartz
authors.forename: Bret H
authors.initials: BH
authors.lastname: Goodpaster
authors.forename: Anne B
authors.initials: AB
authors.lastname: Newman
authors.forename: Tamara
authors.initials: T
authors.lastname: Harris
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Barrett-Connor
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D003430:Cross-Sectional Studies; D003924:Diabetes Mellitus, Type 2 / Q000175:diagnosis* / Q000453:epidemiology* / Q000517:prevention & control; D005260:Female; D018149:Glucose Intolerance / Q000175:diagnosis / Q000453:epidemiology / Q000517:prevention & control; D006801:Humans; D015994:Incidence; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012372:ROC Curve; D012307:Risk Factors