Validation of a model for the prediction of retinopathy in persons with type 1 diabetes

Vivian Schreur, Heijan Ng, Giels Nijpels, Einar Stefánsson, Cees J. Tack, B. Jeroen Klevering, Eiko K. de Jong, Carel B. Hoyng, Jan E. E. Keunen, Amber A. van der Heijden

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Background/Aim: To validate a previously developed model for prediction of diabetic retinopathy (DR) for personalised retinopathy screening in persons with type 1 diabetes. Methods: Retrospective medical data of persons with type 1 diabetes treated in an academic hospital setting were used for analysis. Sight-threatening retinopathy (STR) was defined as the presence of severe non-proliferative DR, proliferative DR or macular oedema. The presence and grade of retinopathy, onset of diabetes, systolic blood pressure, and levels of haemoglobin A 1c were used to calculate an individual risk estimate and personalised screening interval. In persons with STR, the occurrence was compared with the calculated date of screening. The model's predictive performance was measured using calibration and discrimination techniques. Results: Of the 268 persons included in our study, 24 (9.0%) developed STR during a mean follow-up of 4.6 years. All incidences of STR occurred after the calculated screening date. By applying the model, the mean calculated screening interval was 30.5 months, which is a reduction in screening frequency of 61% compared with annual screening and 21% compared with biennial screening. The discriminatory ability was good (Harrell's C-statistic=0.82, 95% CI 0.74 to 0.90), and calibration showed an overestimation of risk in persons who were assigned to a higher risk for STR. Conclusion: This validation study suggests that a screening programme based on the previously developed prediction model is safe and efficient. The use of a personalised screening frequency could improve cost-effectiveness of diabetic eye care.
Original languageEnglish
JournalBritish Journal of Ophthalmology
DOIs
Publication statusE-pub ahead of print - 1 Mar 2019

Cite this