Clinical trial NCT02927561: Automated Diagnostic Test for Diabetic Retinopathy in Brazilian Mass Screening
Official title: Automated Diagnostic Test for Diabetic Retinopathy in Brazilian Mass Screening
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Diabetic Retinopathy
Lead sponsor: Retina Clinic, Sao Paulo, Brazil
Sponsor class: OTHER
First posted: 2016-10-07
Enrollment: 220
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Time perspective: RETROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients with diabetic retinopathy.

Brief summary: In Brazil 10% of the adult population has diabetes. Of these, 39.0% are undiagnosed, at risk for developing complications such as diabetic retinopathy (DR). Due to the increasing prevalence of diabetes and high percentage of patients with uncontrolled disease, cost-effective tools are needed with focused attention on diabetes prevention and management in the current health system. The automatic retinopathy detection can enlarge the screening, reducing the workload and costs compared to manual image graders.

Detailed description: In the South and Central America Region, an estimated 9.4% of the adult population (20-79 years) has diabetes in 2015, and Brazil is the first country in number of people with diabetes. Of these, 39.0% are undiagnosed, at risk for developing complications such as diabetic retinopathy (DR)(1).

The rising number of people with diabetes in the world has become a real challenge for the public health system to provide care for patients with DR and for people with diabetes at risk for this complication(2). A large proportion of patients with diabetes was inadequately controlled in Brazil, which may contribute to increased rates of diabetic complications (3).

The detection of any degree of DR may result in improved medical monitoring and optimization of risk factors, delaying the progression of the disease(4). In Brazil, the great demand in the public service causes delay in early diagnosis, worsening health status of patients with diabetic retinopathy and increasing the cost of their treatment.

Due to the increasing prevalence of diabetes and high percentage of patients with uncontrolled disease, cost-effective tools are needed with focused attention on diabetes prevention and management in the current health system.

Several studies have shown that systematic screening for DR is an effective way of prevention (5). Furthermore, the automatic retinopathy detection can enlarge the screening, reducing the workload and costs compared to manual image graders(6). There are no reports on automated DR detection in Brazilian population, especially in screening campaigns with large-scale diagnosis.

Eligibility criteria: Inclusion Criteria:

* Adults ≥ 18 years with type 1 or 2 diabetes mellitus

Exclusion Criteria:

* Previous cataract, trabeculectomy or vitrectomy
* Aphakia
* External ocular infections
* Glaucoma (IOP of \> 21 mmHg or regular use of more than 2 IOP lowering drugs)
* Pregnancy or breastfeeding.

Primary outcomes:
measure: To compare the sensitivity and specificity of automated grading system versus human grading in detecting diabetic retinopathy
timeFrame: 6 months
Secondary outcomes:
Other outcomes:
Locations:
city: São Paulo
country: Brazil
facility: Retina Clinic
Study officials:
affiliation: Research Director
name: Gabriel Andrade, M.D.
role: STUDY_DIRECTOR
References:
citation: Mendes AB, Fittipaldi JA, Neves RC, Chacra AR, Moreira ED Jr. Prevalence and correlates of inadequate glycaemic control: results from a nationwide survey in 6,671 adults with diabetes in Brazil. Acta Diabetol. 2010 Jun;47(2):137-45. doi: 10.1007/s00592-009-0138-z. Epub 2009 Aug 5.
citation: Soto-Pedre E, Navea A, Millan S, Hernaez-Ortega MC, Morales J, Desco MC, Perez P. Evaluation of automated image analysis software for the detection of diabetic retinopathy to reduce the ophthalmologists' workload. Acta Ophthalmol. 2015 Feb;93(1):e52-6. doi: 10.1111/aos.12481. Epub 2014 Jun 30.
citation: Scotland GS, McNamee P, Philip S, Fleming AD, Goatman KA, Prescott GJ, Fonseca S, Sharp PF, Olson JA. Cost-effectiveness of implementing automated grading within the national screening programme for diabetic retinopathy in Scotland. Br J Ophthalmol. 2007 Nov;91(11):1518-23. doi: 10.1136/bjo.2007.120972. Epub 2007 Jun 21.
citation: Fleming AD, Philip S, Goatman KA, Olson JA, Sharp PF. Automated assessment of diabetic retinal image quality based on clarity and field definition. Invest Ophthalmol Vis Sci. 2006 Mar;47(3):1120-5. doi: 10.1167/iovs.05-1155.
citation: Malerbi FK, Morales PH, Farah ME, Drummond KR, Mattos TC, Pinheiro AA, Mallmann F, Perez RV, Leal FS, Gomes MB, Dib SA; Brazilian Type 1 Diabetes Study Group. Comparison between binocular indirect ophthalmoscopy and digital retinography for diabetic retinopathy screening: the multicenter Brazilian Type 1 Diabetes Study. Diabetol Metab Syndr. 2015 Dec 21;7:116. doi: 10.1186/s13098-015-0110-8. eCollection 2015.
citation: Grading diabetic retinopathy from stereoscopic color fundus photographs--an extension of the modified Airlie House classification. ETDRS report number 10. Early Treatment Diabetic Retinopathy Study Research Group. Ophthalmology. 1991 May;98(5 Suppl):786-806.
citation: Ribeiro L, Oliveira CM, Neves C, Ramos JD, Ferreira H, Cunha-Vaz J. Screening for Diabetic Retinopathy in the Central Region of Portugal. Added Value of Automated 'Disease/No Disease' Grading. Ophthalmologica. 2014 Nov 26. doi: 10.1159/000368426. Online ahead of print.
citation: Bhaskaranand M, Ramachandra C, Bhat S, Cuadros J, Nittala MG, Sadda S, Solanki K. Automated Diabetic Retinopathy Screening and Monitoring Using Retinal Fundus Image Analysis. J Diabetes Sci Technol. 2016 Feb 16;10(2):254-61. doi: 10.1177/1932296816628546.