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Updated: Jan 11, 2026

Implantation and Evaluation of Melanoma in the Murine Choroid via Optical Coherence Tomography
Published on: December 2, 2022
Integrating novel OCT-based choroidal imaging: A multimodal nomogram for predicting intravenous glucocorticoid
Yinru Wang1, Qinglu Song2, Zhiyuan Zhang3
1Department of Ophthalmology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China.
Purpose:
This study aimed to develop a clinically accessible, cost-effective nomogram model to predict intravenous glucocorticoid (IVGC) response in active moderate-to-severe thyroid-associated ophthalmopathy (TAO) by integrating novel optical coherence tomography (OCT)-derived choroidal parameters, thereby addressing limitations of existing biomarkers tied to specialized infrastructure and high costs.
Methods:
A retrospective analysis included 90 patients (178 eyes) with active moderate-to-severe TAO treated with IVGC per EUGOGO guidelines. Clinically routine parameters, specifically thyrotropin receptor antibody (TRAb), total cholesterol (TC), lymphocyte-to-monocyte ratio (LMR), and OCT-derived subfoveal choroidal thickness (SFCT), were analyzed via multivariate logistic regression. Model performance was evaluated using ROC analysis, 1000-bootstrap validation, and calibration curves.
Results:
Elevated TRAb (OR = 0.95, P = 0.005), TC (OR = 0.155, P < 0.001), LMR (OR = 0.709, P = 0.006), and reduced SFCT (OR = 0.983, P < 0.001) independently predicted IVGC response. The nomogram showed high accuracy (AUC = 0.926, 95 % CI: 0.880-0.962) and robust calibration. These biomarkers collectively reflect autoimmune dysregulation, lipid-mediated inflammation, and fibrotic remodeling, underlying therapeutic resistance.
Conclusion:
The developed nomogram effectively integrates the capabilities of optical coherence tomography (OCT) and routine biomarkers to provide a precise, cost-effective, and accessible strategy for predicting IVGC treatment response in TAO. This tool empowers clinicians to guide therapeutic personalization, thereby optimizing patient outcomes and minimizing the risks associated with ineffective therapy.
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