The use of statistical methodology to determine the accuracy of grading within a diabetic retinopathy screening programme. Issue 7 (10th January 2016)

• Record Type: Journal Article
• Authors: Oke, J. L.; Stratton, I. M.; Aldington, S. J.; Stevens, R. J.; Scanlon, P. H.
• Is Part Of: Diabetic medicine. Volume 33:Issue 7(2016:Jul.)
• Page Start: 896
• Page End: 903
• Publication Date: 2016-01-10
• Subjects: Diabetes -- Periodicals; 616.462
• DOI: 10.1111/dme.13053
• Languages: English
• ISSNs: 0742-3071

Abstract

Abstract: Aims: We aimed to use longitudinal data from an established screening programme with good quality assurance and quality control procedures and a stable well‐trained workforce to determine the accuracy of grading in diabetic retinopathy screening. Methods: We used a continuous time‐hidden Markov model with five states to estimate the probability of true progression or regression of retinopathy and the conditional probability of an observed grade given the true grade (misclassification). The true stage of retinopathy was modelled as a function of the duration of diabetes and HbA1c . Results: The modelling dataset consisted of 65 839 grades from 14 187 people. The median number [interquartile range (IQR)] of examinations was 5 (3, 6) and the median (IQR) interval between examinations was 1.04 (0.99, 1.17) years. In total, 14 227 grades (21.6%) were estimated as being misclassified, 10 592 (16.1%) represented over‐grading and 3635 (5.5%) represented under‐grading. There were 1935 (2.9%) misclassified referrals, 1305 were false‐positive results (2.2%) and 630 were false‐negative results (11.0%). Misclassification of background diabetic retinopathy as no detectable retinopathy was common (3.4% of all grades) but rarely preceded referable maculopathy or retinopathy. Conclusion: Misclassification between lower grades of retinopathy is not uncommon but is unlikely to lead to significant delays in referring people for sight‐threatening retinopathy. What's new?: A statistical modelling approach can be used to retrospectively evaluate the accuracy of screening programmes for diabetic retinopathy. Our model predicts that misclassification of background retinopathy as no detectable retinopathy is unlikely to lead to clinically significant delays in referring people with sight‐threatening retinopathy. This study adds to a growing body of evidence that suggests screening intervals for people graded as no background retinopathy could be safely extended to 2 or 3 years.