performance of stepwise screening methods in identifying individuals at high risk of type 2 diabetes in an iranian population

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.