AIMS: To develop a risk-score model, based on available clinical data to assess absolute risk of type 2 diabetes among people with impaired glucose tolerance (IGT). METHODS: Data from the study to prevent non-insulin dependent diabetes mellitus (STOP-NIDDM) investigating acarbose treatment in individuals with IGT were used to develop multivariable Cox proportional hazards model for the time to onset of diabetes. The final model equation was externally validated using data from the Finnish Cardiovascular Risk Factor (FINRISK) population. RESULTS: The risk-score model included the variables acarbose treatment, gender, serum triglyceride level, waist circumference, fasting plasma glucose, height, history of cardiovascular disease (CVD) and hypertension. The final model yielded an area under the receiver-operating-characteristic curve (AUC(ROC)) of 0.64 when applied to people with IGT in the STOP-NIDDM, and 0.84 and 0.90 when applied to FINRISK population with IGT alone and IGT and normal glucose tolerance combined, respectively; AUC(ROC) is a measure of the discriminatory power of the model (1, perfect discrimination). CONCLUSIONS: The STOP-NIDDM risk-score is a simple and validated tool that can identify high-risk individuals with IGT who would benefit most from type 2 diabetes or CVD prevention strategies, such as lifestyle management or early acarbose treatment. 2009 Elsevier Ireland Ltd. All rights reserved.
AIMS: To develop a risk-score model, based on available clinical data to assess absolute risk of type 2 diabetes among people with impaired glucose tolerance (IGT). METHODS: Data from the study to prevent non-insulin dependent diabetes mellitus (STOP-NIDDM) investigating acarbose treatment in individuals with IGT were used to develop multivariable Cox proportional hazards model for the time to onset of diabetes. The final model equation was externally validated using data from the Finnish Cardiovascular Risk Factor (FINRISK) population. RESULTS: The risk-score model included the variables acarbose treatment, gender, serum triglyceride level, waist circumference, fasting plasma glucose, height, history of cardiovascular disease (CVD) and hypertension. The final model yielded an area under the receiver-operating-characteristic curve (AUC(ROC)) of 0.64 when applied to people with IGT in the STOP-NIDDM, and 0.84 and 0.90 when applied to FINRISK population with IGT alone and IGT and normal glucose tolerance combined, respectively; AUC(ROC) is a measure of the discriminatory power of the model (1, perfect discrimination). CONCLUSIONS: The STOP-NIDDM risk-score is a simple and validated tool that can identify high-risk individuals with IGT who would benefit most from type 2 diabetes or CVD prevention strategies, such as lifestyle management or early acarbose treatment. 2009 Elsevier Ireland Ltd. All rights reserved.
Authors: Konstantia Zarkogianni; Eleni Litsa; Konstantinos Mitsis; Po-Yen Wu; Chanchala D Kaddi; Chih-Wen Cheng; May D Wang; Konstantina S Nikita Journal: IEEE Trans Biomed Eng Date: 2015-08-19 Impact factor: 4.538
Authors: Anne Neumann; Margareta Norberg; Olaf Schoffer; Fredrik Norström; Ingegerd Johansson; Stefanie J Klug; Lars Lindholm Journal: BMC Public Health Date: 2013-10-26 Impact factor: 3.295