Abstract
A novel algorithm to predict incident type 2 diabetes mellitus (iT2DM) is presented considering data from a 20-year prospective study in a Southern Italy population. Eight hundred and fifty-eight out of 1,351 subjects (24–85 years range of age) were selected. Incident type 2 diabetes was diagnosed in 103 patients in a 20-year follow-up. The Finnish Diabetes Risk Score (FINDRISC) and the Framingham Offspring Study simple clinical model (FOS) have been used as reference algorithms. Two custom algorithms have been created using Cox parametric hazard models followed by PROBIT analyses: the first one (VHSRISK) includes all the study subjects and the second one (VHS95RISK) evaluates separately subjects with baseline fasting blood glucose (FBG) above/below 5.2 mmol/L (95 mg/dL). The 44 iT2DM cases below 5.2 mmol/L of baseline FBG were predicted by high LDL cholesterol, metabolic syndrome (ATPIII criteria), BMI > 30 kg/m2, and high factor VII activity. The 59 cases above the FBG threshold were predicted by FBG classes, hypertension, and age. ROC areas for iT2DM prediction were: FINDRISC = 0.759, FOS = 0.762, VHSRISK = 0.789, and VHS95RISK = 0.803. In a Mediterranean population, the use of a custom generated algorithm evaluating separately low/high FBG subjects improves the prediction of iT2DM in subjects classified at lower risk by common estimation algorithms.
Similar content being viewed by others
References
Stegmair B, Asplund K, Kuulasmaa K, Rajakangas AM, Thorvaldsen P, Tuomilchto J (1996) Stroke incidence and mortality correlated to stroke risk factors in the WHO MONICA project: an ecological study of 18 populations. Stroke 28:1367–1374
Menotti A, Keys A, Blackburn H, Aravanis C, Dontas A, Fidanza F, Giampaoli S, Karvonen M, Kromhout D, Nedeljkovic S (1990) Twenty-year stroke mortality and prediction in twelve cohorts of the seven Countries study. Int J Epidemiol 19:309–315
Salas-Salvadó J, Fernández-Ballart J, Ros E, Martínez-González MA, Fitó M, Estruch R, Corella D, Fiol M, Gómez-Gracia E, Arós F, Flores G, Lapetra J, Lamuela-Raventós R, Ruiz-Gutiérrez V, Bulló M, Basora J, Covas MI (2008) PREDIMED Study Investigators. Effect of a Mediterranean diet supplemented with nuts on metabolic syndrome status: one year results of the PREDIMED randomized trial. Arch Intern Med 168(22):2449–2458
Barbagallo CM, Cavera G, Sapienza M, Noto D, Cefalu AB, Pagano M, Montalto G, Notarbartolo A, Averna MR (2001) Prevalence of overweight and obesity in a rural southern Italy population and relationships with total and cardiovascular mortality: the Ventimiglia di Sicilia project. Int J Obes Relat Metab Disord 25(2):185–190
Kucharska-Newton AM, Couper DJ, Pankow JS, Prineas RJ, Rea TD, Sotoodehnia N, Chakravarti A, Folsom AR, Siscovick DS, Rosamond WD (2010) Diabetes and the risk of sudden cardiac death, the atherosclerosis risk in communities study. Acta Diabetol 47(Suppl 1):161–168
Noto D, Barbagallo CM, Cefalù AB, Falletta A, Sapienza M, Cavera G, Amato S, Pagano M, Maggiore M, Carroccio A, Notarbartolo A, Averna MR (2008) The metabolic syndrome predicts cardiovascular events in subjects with normal fasting glucose: results of a 15 years follow-up in a Mediterranean population. Atherosclerosis 197(1):147–153
Roumen C, Blaak EE, Corpeleijn E (2009) Lifestyle intervention for prevention of diabetes: determinants of success for future implementation. Nutr Rev 67(3):132–146
Eriksson KF, Lindgärde F (1991) Prevention of type 2 (non-insulin-dependent) diabetes mellitus by diet and physical exercise. The 6-year Malmö feasibility study. Diabetologia 34(12):891–898
Ramachandran A, Snehalatha C, Mary S, Mukesh B, Bhaskar AD, Vijay V, Indian Diabetes Prevention Programme (IDPP) (2006) The Indian diabetes prevention programme shows that lifestyle modification and metformin prevent type 2 diabetes in Asian Indian subjects with impaired glucose tolerance (IDPP-1). Diabetologia 49(2):289–297
Schwarz PE, Li J, Lindstrom J, Tuomilehto J (2009) Tools for predicting the risk of type 2 diabetes in daily practice. Horm Metab Res 41(2):86–97
National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) (2002) 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 106(25):3143–3421
American Diabetes Association (2006) Diagnosis and classification of diabetes mellitus. Diabetes Care 29(Suppl 1):S3–S8
Lindström J, Tuomilehto J (2003) The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care 26(3):725–731
Wilson PW, Meigs JB, Sullivan L, Fox CS, Nathan DM, D’Agostino RB Sr (2007) Prediction of incident diabetes mellitus in middle-aged adults: the Framingham offspring study. Arch Intern Med 167(10):1068–1074
Lindström J, Peltonen M, Eriksson JG, Aunola S, Hämäläinen H, Ilanne-Parikka P, Keinänen-Kiukaanniemi S, Uusitupa M, Tuomilehto J (2008) Finnish diabetes prevention study (DPS) group. Determinants for the effectiveness of lifestyle intervention in the Finnish diabetes prevention study. Diabetes Care 31(5):857–862
Vergara IA, Norambuena T, Ferrada E, Slater AW, Melo F (2008) StAR: a simple tool for the statistical comparison of ROC curves. BMC Bioinformatics 9:265–268
Noto D, Cefalù AB, Barbagallo CM, Sapienza M, Cavera G, Nardi I, Pagano M, Vivona N, Notarbartolo A, Averna MR (2009) Hypertension and diabetes mellitus are associated with cardiovascular events in the elderly without cardiovascular disease. Results of a 15-year follow-up in a Mediterranean population. Nutr Metab Cardiovasc Dis 19(5):321–326
Hu Y, Liu W, Chen Y, Zhang M, Wang L, Zhou H, Wu P, Teng X, Dong Y, Zhou J, Xu H, Zheng J, Li S, Tao T, Hu Y, Jia Y (2010) Combined use of fasting plasma glucose and glycated hemoglobin A1c in the screening of diabetes and impaired glucose tolerance. Acta Diabetol 47(3):231–236
Ford ES (2005) Risks for all-cause mortality, cardiovascular disease, and diabetes associated with the metabolic syndrome: a summary of the evidence. Diabetes Care 28(7):1769–1778
Carr MC, Brunzell JD (2004) Abdominal obesity and dyslipidemia in the metabolic syndrome: importance of type 2 diabetes and familial combined hyperlipidemia in coronary artery disease risk. J Clin Endocrinol Metab 89(6):2601–2607
Grant PJ (2007) Diabetes mellitus as a prothrombotic condition. J Intern Med 262(2):15772
Noto D, Barbagallo CM, Cefalu’ AB, Cavera G, Sapienza M, Notarbartolo A, Davi’ G, Averna MR (2002) Factor VII activity is an independent predictor of cardiovascular mortality in elderly women of a Sicilian population: results of an 11-year follow-up. Thromb Haemost 87(2):206–210
Oberlinner C, Zober A, Nawroth PP, Humpert PM, Morcos M (2010) Alanine-aminotransferase levels predict impaired glucose tolerance in a worksite population. Acta Diabetol 47(2):161–165
Weitzman S, Wang CH, Pankow JS, Schmidt MI, Brancati FL (2010) Are measures of height and leg length related to incident diabetes mellitus? The ARIC (atherosclerosis risk in communities) study. Acta Diabetol 47(3):237–242
Balkau B, Lange C, Fezeu L, Tichet J, de Lauzon-Guillain B, Czernichow S, Fumeron F, Froguel P, Vaxillaire M, Cauchi S, Ducimetière P, Eschwège E (2008) Predicting diabetes: clinical, biological, and genetic approaches: data from the epidemiological study on the insulin resistance syndrome (DESIR). Diabetes Care 31(10):2056–2061
Nichols GA, Brown JB (2008) Validating the Framingham offspring study equations for predicting incident diabetes mellitus. Am J Manag Care 14(9):574–580
Li J, Bergmann A, Reimann M, Bornstein SR, Schwarz PE (2009) A more simplified Finnish diabetes risk score for opportunistic screening of undiagnosed type 2 diabetes in a German population with a family history of the metabolic syndrome. Horm Metab Res 41(2):98–103
Al-Lawati JA, Tuomilehto J (2007) Diabetes risk score in Oman: a tool to identify prevalent type 2 diabetes among Arabs of the Middle East. Diabetes Res Clin Pract 77(3):438–444
Meigs JB, Shrader P, Sullivan LM, McAteer JB, Fox CS, Dupuis J, Manning AK, Florez JC, Wilson PW, D’Agostino RB Sr, Cupples LA (2008) Genotype score in addition to common risk factors for prediction of type 2 diabetes. N Engl J Med 359(21):2208–2219
Conflict of interest
All the authors declare no conflicts of interest.
Author information
Authors and Affiliations
Corresponding author
Additional information
Dott Davide Noto and Dott Angelo B Cefalù equally contributed to the paper.
Rights and permissions
About this article
Cite this article
Noto, D., Cefalù, A.B., Barbagallo, C.M. et al. Prediction of incident type 2 diabetes mellitus based on a twenty-year follow-up of the Ventimiglia heart study. Acta Diabetol 49, 145–151 (2012). https://doi.org/10.1007/s00592-011-0305-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00592-011-0305-x