AUTHOR=Lu Yang , Lv Zhe , Cen Jiner , Tao Jiwei , Zhang Yun , Zhang Yifan , Mao Jianbo , Chen Yiqi , Wu Mingyuan , Chen Shujun , Shen Lijun 

TITLE=Retrospective validation of G-ROP, CO-ROP, Alex-ROP, and ROPscore predictive algorithms in two Chinese medical centers

JOURNAL=Frontiers in Pediatrics

VOLUME=Volume 11 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/pediatrics/articles/10.3389/fped.2023.1079290

DOI=10.3389/fped.2023.1079290

ISSN=2296-2360

ABSTRACT=Purpose: To evaluate sensitivity and specificity of four predictive algorithms (G-ROP, CO-ROP, Alex-ROP and ROPscore) for retinopathy of prematurity and compare their performances in the Chinese population.
Methods: A retrospective study was conducted at two medical centers in China of infants born at Women’s Hospital School of Medicine ZheJiang University and Yiwu Maternal and Child Health Hospital. A total of 1634 infants who met the criteria that was GA<32weeks or BW<2000g according to Chinese guideline for ROP screening were included. Any ROP group was further grouped into severe ROP and mild ROP. The sensitivity and specificity of G-ROP, two simplified G-ROPs, CO-ROP, Alex-ROP and ROPscore were analyzed.
Results: Severe ROP and any ROP were identified in 25 and 399 of 1634 infants, respectively. According to the criteria of different models, 844, 1122, 1122 and 587 infants were eligible in the G-ROP, CO-ROP, Alex-ROP and ROPscore, respectively. G-ROP had the 96.0% sensitivity and 35.0% specificity for severe ROP. For two simplified G-ROPs (180g and 200g models), similar sensitivity was showed with original G-ROP and specificity of them was 21.8% and 14.0%, respectively. Sensitivity and specificity of Co-ROP were 96% and 64.3% for severe ROP, while Alex-ROP only had the sensitivity of 56.0% and specificity of 61.4% for severe ROP. ROPscore had the sensitivity of 91.3% and specificity of 62.4% for severe ROP . In 546 infants who met all 4 models’ inclusion criteria and included 23 infants with severe ROP, the validation outcomes showed the sensitivity of G-ROP, ROPscore, CO-ROP and Alex-ROP for severe ROP was 95.6% ,91.3% ,100% and 56.0%, and the specificity of them was 38.0% , 60.8%, 39.9% and 52.9%, respectively. 
Conclusion: G-ROP, ROPscore and CO-ROP had high sensitivity for severe ROP in Chinese population, but both sensitivity and specificity of Alex-ROP were low. CO-ROP (not high-grade CO-ROP) provided the best performance for severe ROP in a fair comparison. For further application, ROP screening models need to be adjusted by local populations.