External Validation of a Retinopathy of Prematurity Screening Model Using Artificial Intelligence in 3 Low- and Middle-Income Populations.

Importance: Retinopathy of prematurity (ROP) is a leading cause of preventable blindness that disproportionately affects children born in low- and middle-income countries (LMICs). In-person and telemedical screening examinations can reduce this risk but are challenging to implement in LMICs owing to the multitude of at-risk infants and lack of trained ophthalmologists. Objective: To implement an ROP risk model using retinal images from a single baseline examination to identify infants who will develop treatment-requiring (TR)-ROP in LMIC telemedicine programs. Design, Setting, and Participants: In this diagnostic study conducted from February 1, 2019, to June 30, 2021, retinal fundus images were collected from infants as part of an Indian ROP telemedicine screening program. An artificial intelligence (AI)-derived vascular severity score (VSS) was obtained from images from the first examination after 30 weeks' postmenstrual age. Using 5-fold cross-validation, logistic regression models were trained on 2 variables (gestational age and VSS) for prediction of TR-ROP. The model was externally validated on test data sets from India, Nepal, and Mongolia. Data were analyzed from October 20, 2021, to April 20, 2022. Main Outcomes and Measures: Primary outcome measures included sensitivity, specificity, positive predictive value, and negative predictive value for predictions of future occurrences of TR-ROP; the number of weeks before clinical diagnosis when a prediction was made; and the potential reduction in number of examinations required. Results: A total of 3760 infants (median [IQR] postmenstrual age, 37 [5] weeks; 1950 male infants [51.9%]) were included in the study. The diagnostic model had a sensitivity and specificity, respectively, for each of the data sets as follows: India, 100.0% (95% CI, 87.2%-100.0%) and 63.3% (95% CI, 59.7%-66.8%); Nepal, 100.0% (95% CI, 54.1%-100.0%) and 77.8% (95% CI, 72.9%-82.2%); and Mongolia, 100.0% (95% CI, 93.3%-100.0%) and 45.8% (95% CI, 39.7%-52.1%). With the AI model, infants with TR-ROP were identified a median (IQR) of 2.0 (0-11) weeks before TR-ROP diagnosis in India, 0.5 (0-2.0) weeks before TR-ROP diagnosis in Nepal, and 0 (0-5.0) weeks before TR-ROP diagnosis in Mongolia. If low-risk infants were never screened again, the population could be effectively screened with 45.0% (India, 664/1476), 38.4% (Nepal, 151/393), and 51.3% (Mongolia, 266/519) fewer examinations required. Conclusions and Relevance: Results of this diagnostic study suggest that there were 2 advantages to implementation of this risk model: (1) the number of examinations for low-risk infants could be reduced without missing cases of TR-ROP, and (2) high-risk infants could be identified and closely monitored before development of TR-ROP.

Antioxidants prevent oxidative DNA damage and cellular transformation elicited by the over-expression of c-MYC.

Reactive oxygen species (ROS)-induced genomic damage may have important consequences in the initiation and progression of cancer. Deregulated expression of the proto-oncogene c-MYC is associated with intracellular oxidative stress and increased DNA damage. However, the protective role of antioxidants such as Vitamin C against MYC-induced genomic damage has not been fully investigated. In a variety of cell lines, we show that ectopic MYC over-expression results in the elevation of intracellular ROS levels and a concomitant increase in oxidative DNA damage, as assessed by levels of 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxo-dG) in the genomic DNA. Loading cells with ascorbic acid (AA) relieved MYC-elicited intracellular oxidative stress and conferred genomic protection. A mitochondrially targeted Vitamin E analog, TPPB, also protected cells from MYC-elicited oxidative DNA damage, suggesting the involvement of mitochondria in increased ROS production. We found that deregulated MYC expression resulted in the attenuation of intracellular glutathione levels, which was reversed by loading cells with Vitamin C. Additionally, cells over-expressing MYC had elevated levels of intracellular superoxide, which was significantly quenched by Vitamin C or the selective superoxide quencher, Tiron. Consequently, Vitamin C and other antioxidants protected cells from MYC-induced cellular transformation. Our studies implicate a role for ROS, and superoxide in particular, in MYC-elicited oxidative DNA damage and cellular transformation, and point to a pharmacological role of antioxidants in cancer chemoprevention.