Abstract
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. 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. 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. Stepwise methods have acceptable performance in identifying those at high risk of incident type 2 diabetes.
Highlights
We showed that two lab-based perdition models for type 2 diabetes namely Saint Antonio (SA)[19] and Framingham Offspring Study (FOS) 20 have a high discrimination power (AUCs ≥0.78) in identifying those at high risk of type 2 diabetes in Iranian population . 21,22 SA, FOS, and the Atherosclerosis Risk in Communities (ARIC) 23 lab-based prediction models were showed to have high potentials to be used in routine clinical practice.[24]
We aim to develop stepwise screening methods by combining a non-invasive measurement (WtHR or AUSDRISK) with a lab-based measurement; and to assess sensitivity, specificity, and positive predictive value (PPV) of those screening methods for predicting the 5-year incidence of type 2 diabetes
Using stepwise methods can eliminate the need for lab measurements in about half of the screened population and limit the proportion of the population who need preventive interventions to less than 35%
Summary
There is strong evidence showing that structured lifestyle interventions can prevent type 2 diabetes among individuals at high risk of type 2 diabetes.[1,2,3,4,5] These interventions showed to be most effective in short terms (
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