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Yu-Ying Liu, Hiroshi Ishikawa, Gadi Wollstein, Richard Anthony Bilonick, James G Fujimoto, Cynthia Mattox, Jay S Duker, Joel S Schuman, James M Rehg; Assessment of Age Effect in Structural and Functional Glaucoma Progression Analysis. Invest. Ophthalmol. Vis. Sci. 2014;55(13):988.
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© ARVO (1962-2015); The Authors (2016-present)
To assess the effect of age in structural and functional glaucoma progression, using a novel progression analysis based on two-dimensional (2-D) state-based longitudinal models accounting for both structural and functional components.
Glaucoma suspect and glaucoma subjects were followed longitudinally. Optical coherence tomography (OCT) circumpapillary retinal nerve fiber layer (RNFL) thickness (proprietary prototype OCT, and OCT 1 and 2, Stratus OCT, Cirrus OCT (Zeiss)) and visual field index (VFI; Humphrey Field Analyzer; Zeiss) were measured at every visit. Calibration equations were employed to normalize RNFL thickness measurements across OCT machines as a one-parameter continuum. 2D continuous-time Hidden Markov Model using VFI and mean RNFL thickness for 2D disease state definition was employed to model progression. Cox proportional hazard model was used to estimate the effect of age in state transition rate.
197 qualified eyes were followed for an average of 10.6+-5.0 years. 1 year of aging was associated with a 2.24% greater risk of functional loss (95% CI: 0.87%~3.61%), but the aging risk for structural loss was not statistically significant (0.84%: -0.18%~1.82%). The intricate and complex structure-function relationship was intuitively visualized as 2D state change plot (Figure). The age group [0-70] showed dominantly vertical state change (structural progression), while the age group [70-100] showed mainly horizontal state change (functional progression).
The proposed novel 2D progression analysis efficiently visualized and quantified non-linear relationship between structural and functional progression. Age-varying modeling using the 2D progression analysis may aid in more informed progression analysis and prediction.
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