Clinical Models and Algorithms for the Prediction of Retinopathy of Prematurity OTA

A Report by the American Academy of Ophthalmology Ophthalmic Technology Assessment Committee Pediatric Ophthalmology/Strabismus Panel: Amy K. Hutchinson, MD,¹ Michele Melia, ScM,² Michael B. Yang, MD,³ Deborah K. VanderVeen, MD,⁴ Lorri B. Wilson, MD,⁵ Scott R. Lambert, MD¹

Ophthalmology, April 2016, Vol 123, 804-816 © 2016 by the American Academy of Ophthalmology. Click here for free access to the OTA.

Objective: To assess the accuracy with which available retinopathy of prematurity (ROP) predictive models detect clinically significant ROP and to what extent and at what risk these models allow for the reduction of screening examinations for ROP.

Methods: A literature search of the PubMed and Cochrane Library databases was last conducted on May 1, 2015 and yielded 305 citations. After screening the abstracts of all 305 citations and reviewing the full text of 30 potentially eligible articles, the panel members determined that 22 met the inclusion criteria. One article included 2 studies, for a total of 23 studies reviewed. The panel extracted information about study design, study population, the screening algorithm tested, interventions, outcomes, and study quality. The methodologist divided the studies into two categories—model development and model validation—and assigned a level of evidence rating to each study. One study was rated level I evidence, 3 studies were rated level II evidence, and 19 studies were rated level III evidence.

Results: In some cohorts, some models would have allowed reductions in the number of infants screened for ROP without failing to identify infants requiring treatment. However, the small sample size and limited generalizability of the ROP predictive models included in this review preclude their widespread use to make all-or-none decisions about whether to screen individual infants for ROP. As an alternative, some studies proposed approaches to apply the models to reduce the number of examinations performed in low-risk infants.

Conclusions: Additional research is needed to optimize ROP predictive model development, validation, and application before such models can be widely used to reduce the burdensome number of ROP screening examinations.

¹Department of Ophthalmology, Emory University School of Medicine, Atlanta, Georgia
²Jaeb Center for Health Research, Tampa, Florida
³Department of Ophthalmology, Abrahamson Pediatric Eye Institute, Cincinnati Children's Hospital Medical Center, University of Cincinnati, College of Medicine, Cincinnati, Ohio
⁴Department of Ophthalmology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
⁵Casey Eye Institute, Oregon Health & Science University, Portland, Oregon