Validating the CANRISK prognostic model for assessing diabetes risk in Canada's multi-ethnic population.

Abstract

Introduction: Despite high rates of undiagnosed diabetes and prediabetes, suitable risk assessment tools for estimating personal diabetes risk in Canada are currently lacking.

Methods: We conducted a cross-sectional screening study that evaluated the accuracy and discrimination of the new Canadian Diabetes Risk Assessment Questionnaire (CANRISK) for detecting diabetes and prediabetes (dysglycemia) in 6223 adults of various ethnicities. All participants had their glycemic status confirmed with the oral glucose tolerance test (OGTT). We developed electronic and paper-based CANRISK scores using logistic regression, and then validated them against reference standard blood tests using test-set methods. We used area under the curve (AUC) summary statistics from receiver operating characteristic (ROC) analyses to compare CANRISK with other alternative risk-scoring models in terms of their ability to discern true dysglycemia.

Results: The AUC for electronic and paper-based CANRISK scores were 0.75 (95% CI: 0.73-0.78) and 0.75 (95% CI: 0.73-0.78) respectively, as compared with 0.66 (95% CI: 0.63-0.69) for the Finnish FINDRISC score and 0.69 (95% CI: 0.66-0.72) for a simple Obesity model that included age, BMI, waist circumference and sex.

Conclusion: CANRISK is a statistically valid tool that may be suitable for assessing diabetes risk in Canada's multi-ethnic population. CANRISK was significantly more accurate than both the FINDRISC score and the simple Obesity model.