Individual risk assessment and information technology to optimise screening frequency for diabetic retinopathy

Aspelund, Thor; Thornórisdóttir, O; Ólafsdóttir, Elín Soffia; Gudmundsdottir, Arna; Einarsdóttir, Anna Bryndís; Mehlsen, Jesper; Einarsson, Stefán; Palsson, Olafur S.; Einarsson, Guðmundur; Bek, Toke; Stefánsson, Einar

doi:10.1007/s00125-011-2257-7

Cited by 136 publications

(209 citation statements)

References 31 publications

Supporting

Mentioning

188

Contrasting

Unclassified

Order By: Relevance

“…Rates of incidence and progression of retinopathy are greater in people with a longer duration of diabetes and with poor glycaemic control (higher HbA 1c ) and may also vary with other factors such as blood pressure and diabetes type. It has been shown in Denmark that it is possible to identify those at higher absolute risk of STDR, 59 and this suggests that it may be possible to identify subgroups of those with diabetes in whom the screening interval can be extended without risk of STDR developing before the next screening visit. This Danish model was constructed using published data from several clinical trials for which patients were recruited in the 1970s and 1980s and followed into the 1990s.…”

Section: Proposed Time Period For Retention Of Relevant Documentationmentioning

confidence: 99%

Development of a cost-effectiveness model for optimisation of the screening interval in diabetic retinopathy screening

Scanlon

Aldington

Leal

et al. 2015

Health Technol Assess

106

167

View full text Add to dashboard Cite

BackgroundThe 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.ObjectivesTo determine whether personalised screening intervals are cost-effective.DesignRisk 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.SettingGloucestershire, Nottinghamshire, South London and East Anglia (all UK).ParticipantsPeople with diabetes in Gloucestershire with risk stratification model validation using data from Nottinghamshire, South London and East Anglia.Main outcome measuresPersonalised risk-based algorithm for screening interval; cost-effectiveness of different screening intervals.ResultsData 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%.ConclusionsThe 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.Study registrationIntegrated Research Application System project number 118959.Funding detailsThe National Institute for Health Research Health Technology Assessment programme.

show abstract

Section: Proposed Time Period For Retention Of Relevant Documentationmentioning

confidence: 99%

Development of a cost-effectiveness model for optimisation of the screening interval in diabetic retinopathy screening

Scanlon

Aldington

Leal

et al. 2015

Health Technol Assess

106

167

View full text Add to dashboard Cite

show abstract

“…A risk calculator has been developed for SA conditions in collaboration with Prof. Einar Steffansson, who developed a risk calculator based on the outcomes observed in a large Danish cohort. [2] Systemic risk is calculated and the outcome drawn onto a 'rev counter' that is placed next to the 'no retinopathy' photographs ( Fig. 1).…”

Section: Fig 1 Examples Of the Ossa Dr Screening System Taken From mentioning

confidence: 99%

Diabetic retinopathy – the Ophthalmology Society of Southern Africa screening programme

Cook

2013

S Afr Med J

View full text Add to dashboard Cite

“…It has been shown that healthcare costs increase with the severity of diabetic retinopathy , which suggests that preventing its progression may lower healthcare expenditure [7]. In addition, information technology based on epidemiological data may facilitate an individualised determination of screening intervals for diabetic retinopathy [8].…”

Section: Introductionmentioning

confidence: 99%

Prevalence of diabetic retinopathy in screening-detected diabetes mellitus: results from the Gutenberg Health Study (GHS)

Ponto

Koenig²,

Pető

et al. 2016

Diabetologia

View full text Add to dashboard Cite

Aims/hypothesis Individuals with type 2 diabetes mellitus may experience an asymptomatic period of hyperglycaemia, and complications may already be present at the time of diagnosis. We aimed to determine the prevalence of diabetic retinopathy in patients with newly diagnosed (screeningdetected) type 2 diabetes. Methods The Gutenberg Health Study is a population-based study with 15,010 participants aged between 35 and 74 years. We determined the weighted prevalence of diabetic retinopathy by assessing fundus photographs. Screeningdetected type 2 diabetes was defined as an HbA 1c concentration of 6.5% (47.5 mmol/mol) or more, no medical diagnosis of diabetes and no intake of insulin or oral glucoselowering agents. Results Of 14,948 participants, 1377 (9.2%) had diabetes mellitus. Of these, 347 (25.2%) had newly diagnosed type 2 diabetes detected by the screening. Overall, the weighted prevalence of screening-detected type 2 diabetes was 2.1%. Fundus photos were evaluable for 285 (82.1%) participants with newly diagnosed diabetes. The weighted prevalence of diabetic retinopathy in screening-detected type 2 diabetes was 13.0%; 12% of participants had a mild non-proliferative diabetic retinopathy and 0.6% had a moderate nonproliferative diabetic retinopathy. Diabetic retinopathy was proliferative in 0.3%. No cases of severe non-proliferative diabetic retinopathy or diabetic maculopathy were found. Thirty (14.9%) of 202 and six (7.2%) of 83 individuals with and without concomitant arterial hypertension, respectively, had diabetic retinopathy (OR 2.54, 95% CI 1.06, 7.14). Visual acuity did not differ between individuals with and without diabetic retinopathy . Conclusions/interpretation In this large European study, the prevalence of diabetic retinopathy in screening-detected type 2 diabetes was 13%. Only a very small proportion of participants with detected diabetic retinopathy needed treatment.

show abstract

Individual risk assessment and information technology to optimise screening frequency for diabetic retinopathy

Cited by 136 publications

References 31 publications

Development of a cost-effectiveness model for optimisation of the screening interval in diabetic retinopathy screening

Development of a cost-effectiveness model for optimisation of the screening interval in diabetic retinopathy screening

Diabetic retinopathy – the Ophthalmology Society of Southern Africa screening programme

Prevalence of diabetic retinopathy in screening-detected diabetes mellitus: results from the Gutenberg Health Study (GHS)

Contact Info

Product

Resources

About