TY - JOUR
T1 - Retinopathy risk calculators in the prediction of sight-threatening diabetic retinopathy in type 2 diabetes: a FIELD substudy
AU - Rao, Benjamin N.
AU - Quinn, Nicola
AU - Januszewski, Andrzej S.
AU - Peto, Tunde
AU - Brazionis, Laima
AU - Aryal, Nanda
AU - O'Connell, Rachel L.
AU - Li, Liping
AU - Summanen, Paula
AU - Scott, Russell
AU - O'Day, Justin
AU - Keech, Anthony C.
AU - Jenkins, Alicia J.
AU - FIELD Study Group
PY - 2022/4
Y1 - 2022/4
N2 - AimsTo 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.MethodsThe 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.ResultsSTDR 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).ConclusionsThe 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.
AB - AimsTo 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.MethodsThe 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.ResultsSTDR 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).ConclusionsThe 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.
KW - Validation study
KW - Risk calculator
KW - Fenofibrate
KW - Diabetic retinopathy
U2 - 10.1016/j.diabres.2022.109835
DO - 10.1016/j.diabres.2022.109835
M3 - Article
C2 - 35314259
SN - 0168-8227
VL - 186
JO - Diabetes Research and Clinical Practice
JF - Diabetes Research and Clinical Practice
M1 - 109835
ER -