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Observational Study
. 2016 Aug;123(8):1795-1801.
doi: 10.1016/j.ophtha.2016.04.035. Epub 2016 May 27.

Diagnostic Discrepancies in Retinopathy of Prematurity Classification

J Peter Campbell  1 , Michael C Ryan  1 , Emily Lore  2 , Peng Tian  3 , Susan Ostmo  1 , Karyn Jonas  4 , R V Paul Chan  4 , Michael F Chiang  5 ; Imaging & Informatics in Retinopathy of Prematurity Research Consortium
Affiliations
Observational Study

Diagnostic Discrepancies in Retinopathy of Prematurity Classification

J Peter Campbell et al. Ophthalmology. 2016 Aug.

Abstract

Purpose: To identify the most common areas for discrepancy in retinopathy of prematurity (ROP) classification between experts.

Design: Prospective cohort study.

Participants: A total of 281 infants were identified as part of a multicenter, prospective, ROP cohort study from 7 participating centers. Each site had participating ophthalmologists who provided the clinical classification after routine examination using binocular indirect ophthalmoscopy (BIO) and obtained wide-angle retinal images, which were independently classified by 2 study experts.

Methods: Wide-angle retinal images (RetCam; Clarity Medical Systems, Pleasanton, CA) were obtained from study subjects, and 2 experts evaluated each image using a secure web-based module. Image-based classifications for zone, stage, plus disease, and overall disease category (no ROP, mild ROP, type II or pre-plus, and type I) were compared between the 2 experts and with the clinical classification obtained by BIO.

Main outcome measures: Inter-expert image-based agreement and image-based versus ophthalmoscopic diagnostic agreement using absolute agreement and weighted kappa statistic.

Results: A total of 1553 study eye examinations from 281 infants were included in the study. Experts disagreed on the stage classification in 620 of 1553 comparisons (40%), plus disease classification (including pre-plus) in 287 of 1553 comparisons (18%), zone in 117 of 1553 comparisons (8%), and overall ROP category in 618 of 1553 comparisons (40%). However, agreement for presence versus absence of type 1 disease was >95%. There were no differences between image-based and clinical classification except for zone III disease.

Conclusions: The most common area of discrepancy in ROP classification is stage, although inter-expert agreement for clinically significant disease, such as presence versus absence of type 1 and type 2 disease, is high. There were no differences between image-based grading and clinical examination in the ability to detect clinically significant disease. This study provides additional evidence that image-based classification of ROP reliably detects clinically significant levels of ROP with high accuracy compared with the clinical examination.

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Conflict of interest statement

Conflict of interest: No conflicting relationship exists for any author. MFC is an unpaid member of the Scientific Advisory Board for Clarity Medical Systems (Pleasanton, CA), and a consultant for Novartis (Basel, Switzerland).

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