ArticleInvestigative ophthalmology & visual science2015
Stereo Photo Measured ONH Shape Predicts Development of POAG in Subjects With Ocular Hypertension.
Article in Investigative ophthalmology & visual science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00000125 (Ocular Hypertension Treatment Study), which is not on this map. Cited by 1 paper.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Ocular Hypertension Treatment Study (OHTS)
Who cites it
1 citing paper in PubMed.
- Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression.Investigative ophthalmology & visual science · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
purposeTo identify objective, quantitative optic nerve head (ONH) structural features and model the contributions of glaucoma.
methodsBaseline stereoscopic optic disc images of 1635 glaucoma-free participants at risk for developing primary open-angle glaucoma (POAG) were collected as part of the Ocular Hypertension Treatment Study. A stereo correspondence algorithm designed for fundus images was applied to extract the three-dimensional (3D) information about the ONH. Principal component analysis was used to identify ONH 3D structural features and the contributions of demographic features, clinical variables, and disease were modeled using linear regression and linear component analysis. The computationally identified features were evaluated based on associations with glaucoma and ability to predict which participants would develop POAG.
resultsThe computationally identified features were significantly associated with future POAG, POAG-related demographics (age, ethnicity), and clinical measurements (horizontal and vertical cup-to-disc ratio, central corneal thickness, and refraction). Models predicting future POAG development using the OHTS baseline data and STEP features achieved an AUC of 0.722 in cross-validation testing. This was a significant improvement over using only demographics (age, sex, and ethnicity), which had an AUC of 0.599.
conclusionsMethods for identifying objective, quantitative measurements of 3D ONH structure were developed using a large dataset. The identified features were significantly associated with POAG and POAG-related variables. Further, these features increased predictive model accuracy in predicting future POAG. The results indicate that the computationally identified features might be useful in POAG early screening programs or as endophenotypes to investigate POAG genetics.
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Registered trials
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