Validation of the Colorado Retinopathy of Prematurity Screening Model

Abstract

The Colorado Retinopathy of Prematurity (CO-ROP) model uses birth weight, gestational age, and weight gain at the first month of life (WG-28) to predict risk of severe retinopathy of prematurity (ROP). In previous validation studies, the model performed very well, predicting virtually all cases of severe ROP and potentially reducing the number of infants who need ROP examinations, warranting validation in a larger, more diverse population. OBJECTIVE To validate the performance of the CO-ROP model in a large multicenter cohort. DESIGN, SETTING, PARTICIPANTS This study is a secondary analysis of data from the Postnatal Growth and Retinopathy of Prematurity (G-ROP) Study, a retrospective multicenter cohort study conducted in 29 hospitals in the United States and Canada between January 2006 and June 2012 of 6351 premature infants who received ROP examinations. MAIN OUTCOMES AND MEASURES Sensitivity and specificity for severe (early treatment of ROP [ETROP] type 1 or 2) ROP, and reduction in infants receiving examinations. The CO-ROP model was applied to the infants in the G-ROP data set with all 3 data points (infants would have received examinations if they met all 3 criteria: birth weight, <1501 g; gestational age, <30 weeks; and WG-28, <650 g). Infants missing WG-28 information were included in a secondary analysis in which WG-28 was considered fewer than 650 g. RESULTS Of 7438 infants in the G-ROP study, 3575 (48.1%) were girls, and maternal race/ethnicity was 2310 (31.1%) African American, 3615 (48.6%) white, 233 (3.1%) Asian, 40 (0.52%) American Indian/Alaskan Native, and 93 (1.3%) Pacific Islander. In the study cohort, 747 infants (11.8%) had type 1 or 2 ROP, 2068 (32.6%) had lower-grade ROP, and 3536 (55.6%) had no ROP. The CO-ROP model had a sensitivity of 96.9% (95% CI, 95.4%-97.9%) and a specificity of 40.9% (95% CI, 39.3%-42.5%). It missed 23 (3.1%) infants who developed severe ROP. The CO-ROP model would have reduced the number of infants who received examinations by 26.1% (95% CI, 25.0%-27.2%). CONCLUSIONS AND RELEVANCE The CO-ROP model demonstrated high but not 100% sensitivity for severe ROP and missed infants who might require treatment in this large validation cohort. The model requires all 3 criteria to be met to signal a need for examinations, but some infants with a birth weight or gestational age above the thresholds developed severe ROP. Most of these infants who were not detected by the CO-ROP model had obvious deviation in expected weight trajectories or nonphysiologic weight gain. These findings suggest that the CO-ROP model needs to be revised before considering implementation into clinical practice.

Poor Postnatal Weight Gain as a Predictor of Retinopathy of Prematurity

“…Still, more than 20% of infants would pass unscreened, which is unacceptable. Furthermore, if only the criterion of net weight gain in 28 days had been used for ROP screening in our study, the number of examined children would have decreased by only 2%, which is significantly less than the figure reported for the CO-ROP [16][17][18] (~23%) or WIN-ROP (~75%) algorithm 28 . The reason for this low percentage was the generally higher prevalence of any form of ROP in our cohort.…”

“…The model assesses ROP through a combination of the following three criteria: GA ≤30 weeks, BW ≤1500 g, and net weight gain of ≤650 g between birth and 4 weeks of age. Both original 17 and validation 16,18 studies demonstrated high sensitivity in predicting ROP, rendering CO-ROP a good tool for reducing the number of examinations.…”

Translational Research in Retinopathy of Prematurity: From Bedside to Bench and Back Again

“…Although various studies have been conducted from a clinical perspective to prevent blindness caused by ROP, including the identification of risk factors, development of predictive models, and diagnosis of the disease stage with artificial intelligence [ 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 ], this review will focus on the translational research that has progressed from basic research to clinical trials.…”

Validation of The DIGIROP-Birth Model in A Chinese Cohort

“…Although some models have been validated and exhibited excellent predictive performance, the validation cohorts consisted mainly of infants in highly developed countries [11][12][13][14][15][16][17][18][19]. Nevertheless, the data gathered from less-developed countries are scarce but indispensable.…”