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Diabetologia. 2014 Jul;57(7):1332-8. doi: 10.1007/s00125-014-3246-4. Epub 2014 Apr 26.

Validation of a model to estimate personalised screening frequency to monitor diabetic retinopathy.

Author information

1
EMGO Institute for Health and Care Research, VU University Medical Center, van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands, a.vanderheijden@vumc.nl.

Abstract

AIMS/HYPOTHESIS:

Our study aimed to validate a model to determine a personalised screening frequency for diabetic retinopathy.

METHODS:

A model calculating a personalised screening interval for monitoring retinopathy based on patients' risk profile was validated using the data of 3,319 type 2 diabetic patients in the Diabetes Care System West-Friesland, the Netherlands. Two-field fundus photographs were graded according to the EURODIAB coding system. Sight-threatening retinopathy (STR) was considered to be grades 3-5. Validity of the model was assessed using calibration and discrimination measures. We compared model-based time of screening with time of STR diagnosis and calculated the differences in the number of fundus photographs using the model compared with those in annual or biennial screening.

RESULTS:

During a mean of 53 months of follow-up, 76 patients (2.3%) developed STR. Using the model, the mean screening interval was 31 months, leading to a reduced screening frequency of 61% compared with annual screening and 23% compared with biennial screening. STR incidence occurred after a mean of 26 months after the model-based time of screening in 67 patients (88.2%). In nine patients (11.8%), STR had developed before the model-based time of screening. The discriminatory ability of the model was good (C-statistic 0.83; 95% CI 0.74, 0.92). Calibration showed that the model overestimated STR risk.

CONCLUSIONS/INTERPRETATION:

A large reduction in retinopathy screening was achieved using the model in this population of patients with a very low incidence of retinopathy. Considering the number of potentially missed cases of STR, there is room for improvement in the model. Use of the model for personalised screening may eventually help to reduce healthcare use and costs of diabetes care.

PMID:
24763851
DOI:
10.1007/s00125-014-3246-4
[Indexed for MEDLINE]

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