Prognostic models for predicting sight-threatening retinopathy of prematurity in preterm infants: A systematic review.

Authors

Stella Moutzouri, Anna-Bettina Haidich, Aikaterini K Seliniotaki, Maria Lithoxopoulou, Persefoni Talimtzi, Christos Tsakalidis, Nikolaos Ziakas, Asimina Mataftsi

Published in

Acta ophthalmologica. Jul 12, 2026. Epub Jul 12, 2026.

Abstract

To identify, describe and critically appraise studies developing and/or validating models for predicting sight-threatening retinopathy of prematurity (ROP) in preterm infants undergoing screening in neonatal intensive care units. PubMed, Embase via Ovid, trial registers, and grey literature were searched from inception to 21 October 2025. Eligible studies included those that developed and/or validated prognostic models for sight-threatening ROP in screened preterm infants. Data extraction followed the CHARMS checklist. Reporting adhered to TRIPOD-SRMA and PRISMA guidelines. Model quality, risk of bias, and applicability were assessed using PROBAST+AI. The protocol is available on Open Science Framework (https://osf.io/dgc4y). Thirty-five unique prognostic models for sight-threatening ROP were identified from 30 development studies. Gestational age, birth weight, and postnatal weight gain were the most frequently reported predictors, followed by sex. Twenty-three models underwent at least one external validation (155 validations in total). Most development studies showed substantial methodological concerns related to study design, handling of missing data, lack of external validation, and inadequate reporting of performance measures. Studies assessing model performance (apparent, internal, or external) were also at high overall risk of bias due to design, analytical, and reporting shortcomings. Collectively, these limitations may reduce the generalizability and clinical applicability of existing models. Despite numerous ROP prediction models, methodological limitations and limited robust validation preclude widespread clinical adoption. Future research should prioritize development and prospective, multicentre validation across large, diverse cohorts, with emphasis on readily available and objectively measured predictors, alongside strict adherence to established methodological and reporting standards (TRIPOD-AI, PROBAST+AI) to ensure reliable, generalizable tools for optimizing ROP screening.

PMID:
42437452
Bibliographic data and abstract were imported from PubMed on 12 Jul 2026.

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