Retinopathy of prematurity (ROP) is a leading cause of blindness in children. The disease can be successfully treated with retinal laser surgery, but detection involves subjecting at-risk infants to physically stressful, resource-intensive and thereby costly, serial diagnostic eye exams. Risk of ROP is currently defined primarily only by birth weight and gestational age cut-points, but these criteria are not efficient for identifying severe ROP. In the US, in 2006 alone, an estimated 65,000 babies underwent eye exams, but less than 5% of infants examined required laser surgery. Nevertheless, because of the serious consequences of missing a potential case of blindness, the protocol must maintain high sensitivity, even at the cost of repeatedly examining children who never require treatment, many of whom never develop retinopathy. The overall goal of this project is to develop a ROP prognostic model that incorporates postnatal growth measurements with birth weight and gestational age in order to greatly reduce the number of infants requiring exams in the US. Basic science and clinical research suggest that slow postnatal growth is predictive of severe ROP and more accurately identifies infants at risk for developing treatment-requiring ROP. The project specific aims are to (1) develop a prognostic model using postnatal weight gain to identify infants who are likely to develop severe ROP, (2) validate the model prospectively in a diverse cohort of at-risk infants, and (3) evaluate the relative cost-effectiveness of the prognostc model versus conventional ROP screening guidelines. The Growth-ROP (G-ROP) Collaborative Study Group consists of 19 geographically and racially diverse centers (18 US, 1 Canadian). The G-ROP group will conduct a retrospective study of 8,865 infants to develop the model and subsequently a prospective study of 4,000 infants to validate the model. Accomplishing the project specific aims may lead to a proposal for revision of current US ROP screening guidelines, with a potential to greatly reduce the screening burden in the US and identify early those infants who might benefit from preventive interventions being developed.

Public Health Relevance

Retinopathy of prematurity (ROP) is a leading cause of blindness in children that can be successfully treated if identified in time. Tens of thousands of infants in the United States each year undergo repeated, stressful, and costly eye examinations in order to identify a small percentage who need treatment. In this research project, a 19-center collaborative group will develop, validate, and evaluate the cost-effectiveness of a prediction model using postnatal growth measurements, birth weight, and gestational age to more accurately assess ROP risk and greatly reduce the number of infants requiring exams in the US.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
5R01EY021137-02
Application #
8550069
Study Section
Special Emphasis Panel (ZEY1-VSN (04))
Program Officer
Schron, Eleanor
Project Start
2012-09-30
Project End
2017-08-31
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
2
Fiscal Year
2013
Total Cost
$799,463
Indirect Cost
$209,443
Name
Children's Hospital of Philadelphia
Department
Type
DUNS #
073757627
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Morrison, David; Shaffer, James; Ying, Gui-Shuang et al. (2018) Ocular complications following treatment in the Postnatal Growth and Retinopathy of Prematurity (G-ROP) Study. J AAPOS 22:128-133
Binenbaum, Gil; Tomlinson, Lauren A (2017) Postnatal Growth and Retinopathy of Prematurity Study: Rationale, Design, and Subject Characteristics. Ophthalmic Epidemiol 24:36-47
Gurwin, Jaclyn; Tomlinson, Lauren A; Quinn, Graham E et al. (2017) A Tiered Approach to Retinopathy of Prematurity Screening (TARP) Using a Weight Gain Predictive Model and a Telemedicine System. JAMA Ophthalmol :
Doty, Richard L; Beals, Evan; Osman, Allen et al. (2014) Suprathreshold odor intensity perception in early-stage Parkinson's disease. Mov Disord 29:1208-12
Binenbaum, Gil (2013) Algorithms for the prediction of retinopathy of prematurity based on postnatal weight gain. Clin Perinatol 40:261-70
Binenbaum, Gil; Ying, Gui-Shuang; Quinn, Graham E et al. (2012) The CHOP postnatal weight gain, birth weight, and gestational age retinopathy of prematurity risk model. Arch Ophthalmol 130:1560-5