RESUMO
AIMS: To evaluate the risk algorithm by Aspelund et al. for predicting sight-threatening diabetic retinopathy (STDR) in Type 2 diabetes (T2D), and to develop a new STDR prediction model. METHODS: The Aspelund et al. algorithm was used to calculate STDR risk from baseline variables in 1012 participants in the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) ophthalmological substudy, compared to on-trial STDR status, and receiver operating characteristic analysis performed. Using multivariable logistic regression, traditional risk factors and fenofibrate allocation as STDR predictors were evaluated, with bootstrap-based optimism-adjusted estimates of predictive performance calculated. RESULTS: STDR developed in 28 participants. The Aspelund et al. algorithm predicted STDR at 2- and 5-years with area under the curve (AUC) 0.86 (95% CI 0.77-0.94) and 0.86 (0.81-0.92), respectively. In the second model STDR risk factors were any DR at baseline (OR 24.0 [95% CI 5.53-104]), HbA1c (OR 1.95 [1.43-2.64]) and male sex (OR 4.34 [1.32-14.3]), while fenofibrate (OR 0.13 [0.05-0.38]) was protective. This model had excellent discriminatory ability (AUC = 0.89). CONCLUSIONS: The algorithm by Aspelund et al. predicts STDR well in the FIELD ophthalmology substudy. Logistic regression analysis found DR at baseline, male sex, and HbA1c were predictive of STDR and, fenofibrate was protective.