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Validation of a Visual Field Prediction Tool for Glaucoma: A Multicenter Study Involving Patients With Glaucoma in the United Kingdom

Dean, A; Fu, DJ; Zhalechian, M; Van Oyen, MP; Lavieri, MS; Khawaja, AP; Stein, JD; (2025) Validation of a Visual Field Prediction Tool for Glaucoma: A Multicenter Study Involving Patients With Glaucoma in the United Kingdom. American Journal of Ophthalmology , 272 pp. 87-97. 10.1016/j.ajo.2025.01.006. Green open access

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Abstract

PURPOSE: A previously developed machine-learning approach with Kalman filtering technology accurately predicted the disease trajectory for patients with various glaucoma types and severities using clinical trial data. This study assesses performance of the KF approach with real-world data. DESIGN: Retrospective cohort study. METHODS: We tested the performance of a previously validated KF model (PKF) initially trained using data from the African Descent and Glaucoma Evaluation Study and the Diagnostic Innovations in Glaucoma Study in patients with different types and severities of glaucoma receiving care in the United Kingdom (UK), comparing the predictive accuracy to 2 conventional linear regression (LR) models and a newly developed KF trained on UK patients (UK-KF). RESULTS: A total of 3116 patients with open-angle glaucoma or suspects were divided into training (n=1584) and testing (n=1532) sets. The predictive accuracy for MD within 2.5 dB of the observed value at 60 months’ follow-up for PKF (75.7%) was substantially better than those for the LR models (P < .01 for both) and similar to that for UK-KF (75.2%, P = .70). The proportion of MD predictions in the 95% repeatability intervals at 60 months’ follow-up for PKF (67.9%) was higher than those for the LR models (40.2%, 40.9%) and similar to that for UK-KF (71.4%). CONCLUSIONS: This study validates the performance of our previously developed KF model on a real-world, multicenter patient population. Our model substantially outperforms the current clinical standard (LR) and forecasts well for patients with different glaucoma types and severities. This study supports the generalizability of PKF performance and supports prospective study of implementation into clinical practice.

Type: Article
Title: Validation of a Visual Field Prediction Tool for Glaucoma: A Multicenter Study Involving Patients With Glaucoma in the United Kingdom
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.ajo.2025.01.006
Publisher version: https://doi.org/10.1016/j.ajo.2025.01.006
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. - For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) license to any Author Accepted Manuscript version arising
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology
URI: https://discovery.ucl.ac.uk/id/eprint/10206345
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