scholarly journals Racial Differences in the Performance of Existing Risk Prediction Models for Incident Type 2 Diabetes: The CARDIA Study

Diabetes Care ◽  
2015 ◽  
pp. dc150509 ◽  
Author(s):  
Mary E. Lacy ◽  
Gregory A. Wellenius ◽  
Mercedes R. Carnethon ◽  
Eric B. Loucks ◽  
April P. Carson ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Racial Differences ◽  
Risk Prediction ◽  
Prediction Models ◽  
Risk Prediction Models ◽  
Incident Type ◽  
Incident Type 2 Diabetes

scholarly journals Performance of Stepwise Screening Methods in Identifying Individuals at High Risk of Type 2 Diabetes in an Iranian Population

2021 ◽  
Author(s):  
Mojtaba Lotfaliany ◽  
Farzad Hadaegh ◽  
Mohammad Ali Mansournia ◽  
Fereidoun Azizi ◽  
Brian Oldenburg ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
High Risk ◽  
Prediction Models ◽  
Anthropometric Measurement ◽  
Screening Methods ◽  
Incident Type ◽  
Non Invasive ◽  
Incident Type 2 Diabetes ◽  
Wide Range

Background: Recent evidence recommended stepwise screening methods for identifying individuals at high risk of type 2 diabetes to be recruited in the lifestyle intervention programs for the prevention of the disease. This study aims to assess the performance of different stepwise screening methods that combine non-invasive measurements with lab-based measurements for identifying those with 5-years incident type 2 diabetes. Methods: 3037 participants aged ≥30 years without diabetes at baseline in the Tehran Lipid and Glucose Study (TLGS) were followed. Thirty-two stepwise screening methods were developed by combining a non-invasive measurement (an anthropometric measurement (waist-to-height ratio, WtHR) or a score based on a non-invasive risk score [Australian Type 2 Diabetes Risk Assessment Tool, AUSDRISK]) with a lab-based measurement (different cut-offs of fasting plasma glucose [FPG] or predicted risk based on three lab-based prediction models [Saint Antonio, SA; Framingham Offspring Study, FOS; and the Atherosclerosis Risk in Communities, ARIC]). The validation, calibration, and usefulness of lab-based prediction models were assessed before developing the stepwise screening methods. Cut-offs were derived either based on previous studies or decision-curve analyses. Results: 203 participants developed diabetes in 5 years. Lab-based risk prediction models had good discrimination power (area under the curves [AUCs]: 0.80-0.83), achieved acceptable calibration and net benefits after recalibration for population’s characteristics and were useful in a wide range of risk thresholds (5%-21%). Different stepwise methods had sensitivity ranged 20%-68%, specificity 70%-98%, and positive predictive value (PPV) 14%-46%; they identified 3%-33% of the screened population eligible for preventive interventions. Conclusion: Stepwise methods have acceptable performance in identifying those at high risk of incident type 2 diabetes.

scholarly journals Liver Function Tests and Risk Prediction of Incident Type 2 Diabetes: Evaluation in Two Independent Cohorts

PLoS ONE ◽  
2012 ◽  
Vol 7 (12) ◽  
pp. e51496 ◽  
Author(s):  
Ali Abbasi ◽  
Stephan J. L. Bakker ◽  
Eva Corpeleijn ◽  
Daphne L. van der A ◽  
Ron T. Gansevoort ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Liver Function ◽  
Risk Prediction ◽  
Liver Function Tests ◽  
Incident Type ◽  
Function Tests ◽  
Incident Type 2 Diabetes

scholarly journals The Construction of Risk Prediction Models Using GWAS Data and Its Application to a Type 2 Diabetes Prospective Cohort

PLoS ONE ◽  
2014 ◽  
Vol 9 (3) ◽  
pp. e92549 ◽  
Author(s):  
Daichi Shigemizu ◽  
Testuo Abe ◽  
Takashi Morizono ◽  
Todd A. Johnson ◽  
Keith A. Boroevich ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Risk Prediction ◽  
Prospective Cohort ◽  
Prediction Models ◽  
Gwas Data ◽  
Risk Prediction Models
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