Diabetic Retinopathy Clinical Trial
Official title:
Phase 0 Observational Study of a Computer-based Screening Algorithm for Detection of Diabetic Retinopathy
Verified date | September 2017 |
Source | VisionQuest Biomedical LLC |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
The study is an Observational, Phase 0 designed to establish that the risk for diabetic
retinopathy assigned by the RiskAnalyzer improves the reading accuracy and consistency of any
reader and it decreases the inter-reader variability.
Objectives: Objectives one, two, and three are arranged chronologically and in an increasing
level of complexity as a three tiered approach to support the primary and secondary endpoint
of the trial. Objective one is to test fully each system components of the study limited to a
single site. Objective two is to evaluate the efficacy of the RiskAnalyzer to assign the risk
of Diabetic Retinopathy in comparison to the gold standard. Objective three is to demonstrate
that the reader's accuracy in grading images is improved when risk levels assigned by the
RiskAnalyzer are made available to the reader while performing the grading of the images
which is the primary endpoint of the trial Methods and Research Design: A network of clinical
study sites will be established to meet the required number of cases needed as calculated by
statistical analysis. Male and Female Subjects between the ages of 18-65 who are either
pre-diabetic or diabetics will be eligible for participation in this study. Subjects will be
recruited, consented, photographed and their images graded by two trained readers and
analyzed by the RiskAnalyzer . The risk levels that are obtained from the RiskAnalyzer will
be compared to the current gold standard practice, manual grading of each case by a reader.
Data collected during this clinical trial will be reported to the referring physician in the
form of a retinal screening report completed and signed by a licensed Ophthalmic professional
and delivered to their attending physician. Risk levels for diabetic retinopathy obtained by
use of the RiskAnalyzer will not be given to the attending physician under any circumstances
in order to preserve standard of care for the patient.
The sensitivity, specificity, receiver operating characteristic (ROC), and data flow process
of the RiskAnalyzer, retinal image reading system will be analyzed and based on the current
gold standard of a human reader. This study is a three-aims study, 24 month in length,
prospective, case-only study of the performance of the RiskAnalyzer. The risk levels obtained
from the RiskAnalyzer are not made visible, i.e. are not unmasked to either of the two
readers. In year two, the risk levels obtained from the RiskAnalyzer for half of the studies
are unmasked to the two readers while grading the image.
Access to all study data and processes follows a role-based design. The clinical staff will
have access only to clinical data but not the technical data. The technical team will have
access to the technical data only but not the clinical data. The study coordinator will have
access to all data. The use of computers will adhere to the Guidance for Industry
Computerized Systems Used in Clinical Investigations and applicable sections of 21 CFRs part
11.
Status | Completed |
Enrollment | 19199 |
Est. completion date | February 24, 2015 |
Est. primary completion date | February 24, 2015 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years to 65 Years |
Eligibility |
Inclusion Criteria: - Patients over the age of 18 - Patients diagnosed as with either PreDiabetes or Diabetes type 1 or type 2 Exclusion Criteria: - People not diagnosed with either PreDiabetes or Diabetes type 1 or type 2 |
Country | Name | City | State |
---|---|---|---|
United States | Project ECHO | Albuquerque | New Mexico |
United States | CommuniCare Health Centers of San Antonio | San Antonio | Texas |
Lead Sponsor | Collaborator |
---|---|
VisionQuest Biomedical LLC | Communicare Health Centers of San Antonio, National Eye Institute (NEI), Project Extension for Community Healthcare Outcomes (ECHO), Retinal Institute of South Texas |
United States,
Abràmoff MD, Niemeijer M, Suttorp-Schulten MS, Viergever MA, Russell SR, van Ginneken B. Evaluation of a system for automatic detection of diabetic retinopathy from color fundus photographs in a large population of patients with diabetes. Diabetes Care. 2008 Feb;31(2):193-8. Epub 2007 Nov 16. — View Citation
Agurto C, Barriga ES, Murray V, Nemeth S, Crammer R, Bauman W, Zamora G, Pattichis MS, Soliz P. Automatic detection of diabetic retinopathy and age-related macular degeneration in digital fundus images. Invest Ophthalmol Vis Sci. 2011 Jul 29;52(8):5862-71. doi: 10.1167/iovs.10-7075. — View Citation
Agurto C, Murray V, Barriga E, Murillo S, Pattichis M, Davis H, Russell S, Abramoff M, Soliz P. Multiscale AM-FM methods for diabetic retinopathy lesion detection. IEEE Trans Med Imaging. 2010 Feb;29(2):502-12. doi: 10.1109/TMI.2009.2037146. — View Citation
Boucher MC, Gresset JA, Angioi K, Olivier S. Effectiveness and safety of screening for diabetic retinopathy with two nonmydriatic digital images compared with the seven standard stereoscopic photographic fields. Can J Ophthalmol. 2003 Dec;38(7):557-68. — View Citation
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Griffith SP, Freeman WL, Shaw CJ, Mitchell WH, Olden CR, Figgs LD, Kinyoun JL, Underwood DL, Will JC. Screening for diabetic retinopathy in a clinical setting: a comparison of direct ophthalmoscopy by primary care physicians with fundus photography. J Fam Pract. 1993 Jul;37(1):49-56. — View Citation
Harding SP, Broadbent DM, Neoh C, White MC, Vora J. Sensitivity and specificity of photography and direct ophthalmoscopy in screening for sight threatening eye disease: the Liverpool Diabetic Eye Study. BMJ. 1995 Oct 28;311(7013):1131-5. — View Citation
Jones CD, Greenwood RH, Misra A, Bachmann MO. Incidence and progression of diabetic retinopathy during 17 years of a population-based screening program in England. Diabetes Care. 2012 Mar;35(3):592-6. doi: 10.2337/dc11-0943. Epub 2012 Jan 25. Erratum in: Diabetes Care. 2014 Mar;37(3):887. — View Citation
Kalm H, Egertsen R, Blohmé G. Non-stereo fundus photography as a screening procedure for diabetic retinopathy among patients with type II diabetes. Compared with 60D enhanced slit-lamp examination. Acta Ophthalmol (Copenh). 1989 Oct;67(5):546-53. — View Citation
Kinyoun JL, Martin DC, Fujimoto WY, Leonetti DL. Ophthalmoscopy versus fundus photographs for detecting and grading diabetic retinopathy. Invest Ophthalmol Vis Sci. 1992 May;33(6):1888-93. — View Citation
Larsen M, Godt J, Larsen N, Lund-Andersen H, Sjølie AK, Agardh E, Kalm H, Grunkin M, Owens DR. Automated detection of fundus photographic red lesions in diabetic retinopathy. Invest Ophthalmol Vis Sci. 2003 Feb;44(2):761-6. — View Citation
Lin DY, Blumenkranz MS, Brothers RJ, Grosvenor DM. The sensitivity and specificity of single-field nonmydriatic monochromatic digital fundus photography with remote image interpretation for diabetic retinopathy screening: a comparison with ophthalmoscopy and standardized mydriatic color photography. Am J Ophthalmol. 2002 Aug;134(2):204-13. — View Citation
Niemeijer M, van Ginneken B, Russell SR, Suttorp-Schulten MS, Abràmoff MD. Automated detection and differentiation of drusen, exudates, and cotton-wool spots in digital color fundus photographs for diabetic retinopathy diagnosis. Invest Ophthalmol Vis Sci. 2007 May;48(5):2260-7. — View Citation
Niemeijer M, van Ginneken B, Staal J, Suttorp-Schulten MS, Abràmoff MD. Automatic detection of red lesions in digital color fundus photographs. IEEE Trans Med Imaging. 2005 May;24(5):584-92. — View Citation
Osareh A, Mirmehdi M, Thomas B, Markham R. Automated identification of diabetic retinal exudates in digital colour images. Br J Ophthalmol. 2003 Oct;87(10):1220-3. — View Citation
Pattichis MS, Pattichis CS, Avraam M, Bovik A, Kyriacou K. AM-FM texture segmentation in electron microscopic muscle imaging. IEEE Trans Med Imaging. 2000 Dec;19(12):1253-8. — View Citation
Philip S, Fleming AD, Goatman KA, Fonseca S, McNamee P, Scotland GS, Prescott GJ, Sharp PF, Olson JA. The efficacy of automated "disease/no disease" grading for diabetic retinopathy in a systematic screening programme. Br J Ophthalmol. 2007 Nov;91(11):1512-7. Epub 2007 May 15. — View 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. Epub 2007 Jun 21. — View Citation
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* Note: There are 21 references in all — Click here to view all references
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Sensitivity and specificity of retinal screening for risk stratification of DR using digital fundus photographs with and without the assistance of the RiskAnalyzer. | Using the gold standard, the sensitivity and specificity are calculated as: Sens=TP/(TP+FN) Spec=TN/(TN+FP) Where TP is the number of true positives (DR subjects correctly classified), FN is the number of false negatives (DR subjects incorrectly classified as normal), TN is the number of true negatives (Normal subjects correctly classified), and FP is the number of false positives (Normal subjects incorrectly classified as abnormals). |
24 months | |
Secondary | Sensitivity and specificity of retinal screening for risk stratification of DR using digital fundus photographs and the RiskAnalyzer | Using the gold standard, the sensitivity and specificity are calculated as: Sens=TP/(TP+FN) Spec=TN/(TN+FP) Where TP is the number of true positives (DR subjects correctly classified), FN is the number of false negatives (DR subjects incorrectly classified as normal), TN is the number of true negatives (Normal subjects correctly classified), and FP is the number of false positives (Normal subjects incorrectly classified as abnormals). |
24 months |
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