Comparative validity of 3 diabetes mellitus risk prediction scoring models in a multiethnic US cohort

American Journal of Epidemiology

Volumn 171, Issue 9, 2010, Pages 980-988

  Mann, Devin M ^a   Bertoni, Alain G ^b   Shimbo, Daichi ^c   Carnethon, Mercedes R ^d   Chen, Haiying ^b   Jenny, Nancy Swords ^e   Muntner, Paul ^f  

^a MOUNT SINAI SCHOOL OF MEDICINE   (United States)

^b WAKE FOREST SCHOOL OF MEDICINE   (United States)

^c NewYork Presbyterian Hospital   (United States)

^d NORTHWESTERN UNIVERSITY   (United States)

^e UNIVERSITY OF VERMONT COLLEGE OF MEDICINE   (United States)

^f UNIVERSITY OF ALABAMA AT BIRMINGHAM   (United States)

Author keywords

cohort studies; diabetes mellitus; models statistical; risk; validation studies as topic

Indexed keywords

ANTIDIABETIC AGENT; GLUCOSE; HIGH DENSITY LIPOPROTEIN CHOLESTEROL; TRIACYLGLYCEROL;

ADULT; CARDIOVASCULAR DISEASE; COHORT ANALYSIS; COMPARATIVE STUDY; DIABETES; DISEASE INCIDENCE; ETHNIC GROUP; HEALTH RISK; MODEL VALIDATION; PROTEIN; PUBLIC HEALTH; RISK FACTOR; STATISTICAL ANALYSIS;

ADULT; AGED; ARTICLE; ATHEROSCLEROSIS; CALIBRATION; CHOLESTEROL BLOOD LEVEL; COHORT ANALYSIS; DIABETES MELLITUS; FEMALE; FOLLOW UP; GLUCOSE BLOOD LEVEL; HUMAN; HYPERTENSION; LIPOPROTEIN BLOOD LEVEL; LONGITUDINAL STUDY; MAJOR CLINICAL STUDY; MALE; OBESITY; RISK ASSESSMENT; TRIACYLGLYCEROL BLOOD LEVEL; UNITED STATES; VALIDITY; CAUCASIAN; COMPARATIVE STUDY; ETHNIC GROUP; ETHNOLOGY; INCIDENCE; MIDDLE AGED; NON INSULIN DEPENDENT DIABETES MELLITUS; PREDICTION AND FORECASTING; REPRODUCIBILITY; STATISTICS;

UNITED STATES;

AGED; AGED, 80 AND OVER; ATHEROSCLEROSIS; COHORT STUDIES; DIABETES MELLITUS, TYPE 2; ETHNIC GROUPS; EUROPEAN CONTINENTAL ANCESTRY GROUP; FEMALE; HUMANS; INCIDENCE; LONGITUDINAL STUDIES; MALE; MIDDLE AGED; PREDICTIVE VALUE OF TESTS; REPRODUCIBILITY OF RESULTS; RISK ASSESSMENT; UNITED STATES;

EID: 77952308870     PISSN: 00029262     EISSN: 14766256     Source Type: Journal    
DOI: 10.1093/aje/kwq030     Document Type: Article

References (21)

1. King H, Aubert RE, Herman WH. Global burden of diabetes, 1995-2025: prevalence, numerical estimates, and projections. Diabetes Care. 1998;21(9):1414-1431.
2. Fox CS, Pencina MJ, Meigs JB, et al. Trends in the incidence of type 2 diabetes mellitus from the 1970s to the 1990s: the Framingham Heart Study. Circulation. 2006;113(25):2914-2918.
3. American Diabetes Association. Executive summary: standards of medical care in diabetes 2008. Diabetes Care. 2008; 31(suppl 1):S5-S11.
4. American Diabetes Association and National Institute of Diabetes and Digestive and Kidney Diseases. The prevention or delay of type 2 diabetes. Diabetes Care. 2002;25(4): 742-749.
5. Schmidt MI, Duncan BB, Bang H, et al. Identifying individuals at high risk for diabetes: the Atherosclerosis Risk in Communities Study. Diabetes Care. 2005;28(8):2013-2018.
6. Stern MP,Williams K, Haffner SM. Identification of persons at high risk for type 2 diabetes mellitus: do we need the oral glucose tolerance test? Ann Intern Med. 2002;136(8): 575-581.
7. Wilson PW, Meigs JB, Sullivan L, et al. Prediction of incident diabetes mellitus in middle-aged adults: the Framingham Offspring Study. Arch Intern Med. 2007;167(10): 1068-1074.
8. AekplakornW, Bunnag P,Woodward M, et al. A risk score for predicting incident diabetes in the Thai population. Diabetes Care. 2006;29(8):1872-1877.
9. Lindström J, Tuomilehto J. The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care. 2003;26(3): 725-731.
10. Harris MI, Flegal KM, Cowie CC, et al. Prevalence of diabetes, impaired fasting glucose, and impaired glucose tolerance in U.S. adults. The Third National Health and Nutrition Examination Survey, 1988-1994. Diabetes Care. 1998;21(4): 518-524.
11. McGeechan K, Macaskill P, Irwig L, et al. Assessing new biomarkers and predictive models for use in clinical practice: a clinicians guide. Arch Intern Med. 2008;168(21):2304-2310.
12. Weiner DE, Tighiouart H, Griffith JL, et al. Kidney disease, Framingham risk scores, and cardiac and mortality outcomes. Am J Med. 2007;120(6):552.e1- 552.e8.
13. DAgostino RB Sr, Grundy S, Sullivan LM, et al. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA. 2001; 286(2):180-187.
14. Bild DE, Bluemke DA, Burke GL, et al. Multi-Ethnic Study of Atherosclerosis: objectives and design. Am J Epidemiol. 2002; 156(9):871-881.
15. National Cholesterol Education Program (NCEP) Expert Panel on Detection. Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation. 2002;106(25):3143-3421.
16. Allison P. Survival Analysis Using SAS: A Practical Guide. Cary, NC: SAS Institute Inc; 1995.
17. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44(3):837-845.
18. Lemeshow S, Hosmer DW Jr. A review of goodness of fit statistics for use in the development of logistic regression models. Am J Epidemiol. 1982;115(1):92-106.
19. Cowie CC, Rust KF, Ford ES, et al. Full accounting of diabetes and pre-diabetes in the U.S. population in 1988-1994 and 2005-2006. Diabetes Care. 2009;32(2): 287-294.
20. Wang Y, Beydoun MA. The obesity epidemic in the United States-gender, age, socioeconomic, racial/ethnic, and geographic characteristics: a systematic review and metaregression analysis. Epidemiol Rev. 2007;29:6-28.
21. Hippisley-Cox J, Coupland C. Predicting risk of osteoporotic fracture in men and women in England andWales: prospective derivation and validation of QFractureScores [electronic article]. BMJ. 2009;339:b4229