Title: Progression of Diabetic Retinopathy from referral to treatment or vision loss: External Validation, update and net clinical benefit of a Multivariable Prediction Model
Funder: Department of Health and Social Care

Abstract: Background: The number of people with diabetes mellitus is increasing globally and consequently so too is diabetic retinopathy (DR). Detection of DR has improved through wider screening. Patients with no retinopathy and mild changes are followed up through the diabetic eye screening programme (DESP). Once the mild changes progress, patients are referred into hospital eye services (HES), however, treatment is not required at this stage for the majority of patients and current pressures on HES can result in undue delays in higher-risk patients, potentially leading to harm. At present, no model exists to stratify patients according to risk. Therefore, we previously developed a prediction model for the progression of DR to treatment stage or vision failure which could be used to identify those at highest risk, with the aim of prioritising their care to increase safety. The model was developed using primary care records and performed well; the model now requires external validation in a secondary care population under hospital eye services. Aims and objectives: To externally validate the DR prediction model in a HES population, with recalibration and updating (using additional predictors) if required. Methods: This study will use a retrospective cohort of diabetic patients aged 12 and over with referable DR (referred by DESP between 2012 and 2015), in the West Midlands, Northeast, and Southwest of England NHS trusts. Data will be obtained from electronic databases and patient notes. A composite outcome of treatment (laser, intravitreal injections) and significant vision loss will be used. Patients will be followed from the date of referral to HES until the earlier of date of treatment or vision loss, or censoring at the date of death, last known follow-up or study end. We anticipate collecting data from around 2400 patients with a minimum of 360 outcomes. We will evaluate the predictive performance of the DR model for predicting risk at a particular time point using measures of discrimination, calibration and net benefit. We will also evaluate how well the model predicts the time to a particular risk threshold, as advocated by an expert consensus panel. Missing data will be handled using multiple imputation. If necessary, the model will be recalibrated and updated using additional variables that were not available in the primary care development dataset, if these variables improve predictive performance. The results of the validation and net benefit analysis will be presented to the ophthalmic consultants expert panel to gain consensus on the most appropriate implementation strategies. Timeliness for delivery: Months 0-6: Protocol development, ethics and staff training; months 7-12: Data extraction, interim analysis and cleaning; months 12-18: Analysis and write up. Anticipated Impact and Dissemination: We anticipate that once validated and updated, the model will have the potential to provide a safer follow-up strategy based on an individual s risk, to ensure patients at higher risk of the outcomes are seen more quickly / more frequently than under the present system. This study will be published in a peer-reviewed clinical journal and presented at relevant clinical and statistical conferences.

Lay abstract: Plain English Summary Background Patients with diabetes commonly develop complications at the back of the eye, called diabetic retinopathy. This condition can cause blindness if left untreated and therefore diabetic patients are screened every one to two years in the diabetic eye screening programme. Once more serious disease develops, hospital appointments become necessary for monitoring. With diabetes becoming more common, there is increased demand for hospital appointments, resulting in delays. This means there is a chance of higher risk patients losing their sight while waiting to be seen. It would therefore be safer to have a system by which these higher risk patients could be prioritised. Aims Using information (data) collected from general practices, we have developed a model which identifies patients at high risk of progressing to diabetic retinopathy requiring treatment or to loss of vision. This model now needs testing in a hospital setting to ensure it works well in patients using hospital services. Methods We will test the performance of the model in hospital data and update it by including additional variables not available in the previously used general practice data. We will then present our findings to a group including patients and experts, to decide on how the model can be put into practice to benefit patients. Patient and public involvement (PPI) We carried out pre-application meetings with GPs, consultant eye surgeons and patients with diabetic retinopathy under hospital care to obtain advice, and we have incorporated that advice into our application. Two patient advocates agreed to join our study, one as co-applicant. He will serve on advisory group to keep the research patient-centred. The project advisory group, including patient advocate and expert doctors, will meet four times during the study to ensure patients and experts perspectives remain influential to the study. These meetings will occur at following stages: Research plan finalisation Analysis before data collection ends Model finalisation Study end PPI costs were calculated according to the official guidance (https://www.invo.org.uk/). Dissemination Based on the results of this work we aim to produce high quality information for doctors and patients about patients risk. This will enable doctors and providers to make more informed decisions about the timing of follow-up appointments and improve safety for higher risk patients. We will make results available widely by publishing in journals and targeting events where we will engage clinicians, Diabetes UK (charity), The Royal College of Ophthalmologists, and commissioners. We hope our findings will help inform management guidelines. A patient advocate will ensure the messages from the research are clear and patient-centred, and are disseminated extensively among patients, their families and carers, members of the public and diabetes related charities through media channels including university newsletters, websites and social media.

Research activity codes: 4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: METABOLIC AND ENDOCRINE;EYE