Abstract:
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Age-related Macular Degeneration (AMD) is a polygenic and progressive neurodegenerative disease, which is a leading cause of blindness in developed countries. Some patients with AMD maintain good vision for a long time with little disease progression over time, while others quickly advance to vision-threatening late AMD. The progressions of two eyes within the same subject are often correlated. In this research, we first develop a computationally efficient copula-based score test, of which the dependence between bivariate progression times is explicitly modeled, to identify susceptible demographical/environmental and genetic risk factors associated with AMD progression. Then, using a large randomized trial data, Age-related Eye Disease Study (AREDS), we establish copula-based prediction models to predict the joint progression-free probability of two eyes within a subject. Finally, we evaluate and validate the prediction models using another independent large randomized trial AREDS2.
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