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

Abstract

PurposeTo evaluate the 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.MethodsA 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 1,634 infants who met the criteria and who were GA < 32 weeks or BW < 2,000 g according to Chinese guidelines for ROP screening were included. The 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.ResultsSevere ROP and any ROP were identified in 25 and 399 of 1,634 infants, respectively. According to the criteria of different models, 844, 1,122, 1,122, and 587 infants were eligible in the G-ROP, CO-ROP, Alex-ROP, and ROPscore, respectively. G-ROP had 96.0% sensitivity and 35.0% specificity for severe ROP. For two simplified G-ROPs (180 g and 200 g models), similar sensitivity was showed with original G-ROP and they had specificity of 21.8% and 14.0%, respectively. The sensitivity and specificity of Co-ROP were 96% and 64.3% for severe ROP, while Alex-ROP only had sensitivity of 56.0% and specificity of 61.4% for severe ROP. ROPscore had a sensitivity of 91.3% and a 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 their specificity was 38.0%, 60.8%, 39.9%, and 52.9%, respectively.ConclusionG-ROP, ROPscore, and CO-ROP had high sensitivity for severe ROP in the Chinese population, but both the 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.

Retrospective cohort evaluation of postnatal growth and retinopathy of prematurity (G‐ROP) criteria in a tertiary centre in Turkey

“…On the other hand, studies from socio‐economically developing countries, such as Egypt, Iran, Thai, and another study from Turkey, reported the sensitivity for treated and Type 1 ROP was 100%, similar to ours (Ahmed et al., 2022; Fadakar et al., 2022; Okbay Gunes et al., 2022; Trinavarat et al., 2023) (Table 2). Furthermore, in a study from China, three severe ROP cases missed by GA and BW criteria were detected by the WG criterion (Lu et al., 2023). The authors noted that WG contributed to detecting severe ROP in infants with a relatively larger BW and older GA (Lu et al., 2023).…”

“…Furthermore, in a study from China, three severe ROP cases missed by GA and BW criteria were detected by the WG criterion (Lu et al., 2023). The authors noted that WG contributed to detecting severe ROP in infants with a relatively larger BW and older GA (Lu et al., 2023). Similarly, in the Egyptian cohort, all infants who developed Type 1 ROP that was not defined by the BW and GA criteria of the G‐ROP model were correctly defined by the WG criterion (Ahmed et al., 2022).…”

“…In a study conducted in China to validate four ROP prediction models based on postpartum weight gain, the G‐ROP criteria demonstrated 96.0% sensitivity for severe ROP (Lu et al., 2023). However, this study defined severe ROP as Type 1 ROP, Type 2 ROP, and threshold ROP.…”

“…One of the main goals of the G‐ROP study was to reduce the number of infants screened by increasing specificity, and in this study, the number of infants requiring examination was reduced by 30.3% (Binenbaum et al., 2018). In validation studies from countries with different socio‐economic levels, a decrease between 14.1% and 50.0% was determined in the number of babies requiring screening (Ahmed et al., 2022; Binenbaum et al., 2020; Caruggi et al., 2021; Huang et al., 2022; Lu et al., 2023; Okbay Gunes et al., 2022; Raffa et al., 2023; Shiraki et al., 2019; Trinavarat et al., 2023; Vinayahalingam et al., 2022; Wadley et al., 2020; Yabas Kiziloglu et al., 2020) (Table 2). Similarly, in our study, there was a 19.8% decrease in the number of babies requiring screening.…”