Development of a cost-effectiveness model for optimisation of the screening interval in diabetic retinopathy screening
Scanlon PH., Aldington SJ., Leal J., Luengo-Fernandez R., Oke J., Sivaprasad S., Gazis A., Stratton IM.
<jats:sec id="abs1-1"><jats:title>Background</jats:title><jats:p>The English NHS Diabetic Eye Screening Programme was established in 2003. Eligible people are invited annually for digital retinal photography screening. Those found to have potentially sight-threatening diabetic retinopathy (STDR) are referred to surveillance clinics or to Hospital Eye Services.</jats:p></jats:sec><jats:sec id="abs1-2"><jats:title>Objectives</jats:title><jats:p>To determine whether personalised screening intervals are cost-effective.</jats:p></jats:sec><jats:sec id="abs1-3"><jats:title>Design</jats:title><jats:p>Risk factors were identified in Gloucestershire, UK using survival modelling. A probabilistic decision hidden (unobserved) Markov model with a misgrading matrix was developed. This informed estimation of lifetime costs and quality-adjusted life-years (QALYs) in patients without STDR. Two personalised risk stratification models were employed: two screening episodes (SEs) (low, medium or high risk) or one SE with clinical information (low, medium–low, medium–high or high risk). The risk factor models were validated in other populations.</jats:p></jats:sec><jats:sec id="abs1-4"><jats:title>Setting</jats:title><jats:p>Gloucestershire, Nottinghamshire, South London and East Anglia (all UK).</jats:p></jats:sec><jats:sec id="abs1-5"><jats:title>Participants</jats:title><jats:p>People with diabetes in Gloucestershire with risk stratification model validation using data from Nottinghamshire, South London and East Anglia.</jats:p></jats:sec><jats:sec id="abs1-6"><jats:title>Main outcome measures</jats:title><jats:p>Personalised risk-based algorithm for screening interval; cost-effectiveness of different screening intervals.</jats:p></jats:sec><jats:sec id="abs1-7"><jats:title>Results</jats:title><jats:p>Data were obtained in Gloucestershire from 12,790 people with diabetes with known risk factors to derive the risk estimation models, from 15,877 people to inform the uptake of screening and from 17,043 people to inform the health-care resource-usage costs. Two stratification models were developed: one using only results from previous screening events and one using previous screening and some commonly available GP data. Both models were capable of differentiating groups at low and high risk of development of STDR. The rate of progression to STDR was 5 per 1000 person-years (PYs) in the lowest decile of risk and 75 per 1000 PYs in the highest decile. In the absence of personalised risk stratification, the most cost-effective screening interval was to screen all patients every 3 years, with a 46% probability of this being cost-effective at a £30,000 per QALY threshold. Using either risk stratification models, screening patients at low risk every 5 years was the most cost-effective option, with a probability of 99-100% at a £30,000 per QALY threshold. For the medium-risk groups screening every 3 years had a probability of 43 –48% while screening high-risk groups every 2 years was cost-effective with a probability of 55–59%.</jats:p></jats:sec><jats:sec id="abs1-8"><jats:title>Conclusions</jats:title><jats:p>The study found that annual screening of all patients for STDR was not cost-effective. Screening this entire cohort every 3 years was most likely to be cost-effective. When personalised intervals are applied, screening those in our low-risk groups every 5 years was found to be cost-effective. Screening high-risk groups every 2 years further improved the cost-effectiveness of the programme. There was considerable uncertainty in the estimated incremental costs and in the incremental QALYs, particularly with regard to implications of an increasing proportion of maculopathy cases receiving intravitreal injection rather than laser treatment. Future work should focus on improving the understanding of risk, validating in further populations and investigating quality issues in imaging and assessment including the potential for automated image grading.</jats:p></jats:sec><jats:sec id="abs1-9"><jats:title>Study registration</jats:title><jats:p>Integrated Research Application System project number 118959.</jats:p></jats:sec><jats:sec id="abs1-10"><jats:title>Funding details</jats:title><jats:p>The National Institute for Health Research Health Technology Assessment programme.</jats:p></jats:sec>