Nugawela, Manjula D;
Gurudas, Sarega;
Prevost, A Toby;
Mathur, Rohini;
Robson, John;
Sathish, Thirunavukkarasu;
Rafferty, JM;
... Sivaprasad, Sobha; + view all
(2022)
Development and validation of predictive risk models for sight threatening diabetic retinopathy in patients with type 2 diabetes to be applied as triage tools in resource limited settings.
eClinicalMedicine
, 51
, Article 101578. 10.1016/j.eclinm.2022.101578.
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Abstract
Background: Delayed diagnosis and treatment of sight threatening diabetic retinopathy (STDR) is a common cause of visual impairment in people with Type 2 diabetes. Therefore, systematic regular retinal screening is recommended, but global coverage of such services is challenging. We aimed to develop and validate predictive models for STDR to identify ‘at-risk’ population for retinal screening. Methods: Models were developed using datasets obtained from general practices in inner London, United Kingdom (UK) on adults with type 2 Diabetes during the period 2007–2017. Three models were developed using Cox regression and model performance was assessed using C statistic, calibration slope and observed to expected ratio measures. Models were externally validated in cohorts from Wales, UK and India. Findings: A total of 40,334 people were included in the model development phase of which 1427 (3·54%) people developed STDR. Age, gender, diabetes duration, antidiabetic medication history, glycated haemoglobin (HbA1c), and history of retinopathy were included as predictors in the Model 1, Model 2 excluded retinopathy status, and Model 3 further excluded HbA1c. All three models attained strong discrimination performance in the model development dataset with C statistics ranging from 0·778 to 0·832, and in the external validation datasets (C statistic 0·685 – 0·823) with calibration slopes closer to 1 following re-calibration of the baseline survival. Interpretation: We have developed new risk prediction equations to identify those at risk of STDR in people with type 2 diabetes in any resource-setting so that they can be screened and treated early. Future testing, and piloting is required before implementation. Funding: This study was funded by the GCRF UKRI (MR/P207881/1) and supported by the NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology.
| Type: | Article |
|---|---|
| Title: | Development and validation of predictive risk models for sight threatening diabetic retinopathy in patients with type 2 diabetes to be applied as triage tools in resource limited settings |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.eclinm.2022.101578 |
| Publisher version: | http://dx.doi.org/10.1016/j.eclinm.2022.101578 |
| Language: | English |
| Additional information: | Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/) |
| Keywords: | Science & Technology, Life Sciences & Biomedicine, Medicine, General & Internal, General & Internal Medicine, Diabetic, Retinopathy, Predictive models, Performance, Diabetes, South Asians, India, LIFETIME HEALTH OUTCOMES, INTERVAL, COMPLICATIONS, TIME, EQUATIONS |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10173088 |
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