Background /Aims. To evaluate the performance of existing prediction models to determine risk of progression to referable diabetic retinopathy (RDR) using data from a prospective Irish cohort of people with type 2 diabetes (T2D).
Methods. A cohort of 939 people with T2D followed prospectively was used to test the performance of risk prediction models developed in Gloucester, United Kingdom, and Iceland. Observed risk of progression to RDR in the Irish cohort was compared with that derived from each of the prediction models evaluated. Receiver operating characteristic (ROC) curves assessed models’ performance.
Results. The cohort was followed for a total of 2929 person years during which 2906 screening episodes occurred. Amongst 939 individuals followed, there were 40 referrals (4%) for diabetic maculopathy, pre-proliferative DR, and proliferative DR (PDR). The original Gloucester model, which includes results of two consecutive retinal screenings; a model incorporating, in addition, systemic biomarkers [glycosylated haemoglobin (HbA1c) and serum cholesterol]; and a model including results of one retinopathy screening, HbA1c, total cholesterol and duration of diabetes, had acceptable discriminatory power (area under the curve [AUC] of 0.69, 0.76 and 0.77, respectively). The Icelandic model, which combined retinopathy grading, duration and type of diabetes, HbA1c and systolic blood pressure, performed very similarly (AUC of 0.74).
Conclusion. In an Irish cohort of people with T2D, the prediction models tested had an acceptable performance identifying those at risk of progression to RDR. These risk models would be useful in establishing more personalised screening intervals for people with T2D.
- Prediction models, referable diabetic retinopathy, sight-threatening diabetic retinopathy, external validation, area under the curve, AUC, receiver operating characteristics, ROC, diabetes, risk, diabetic retinopathy, DR.