Understanding Heterogeneity in Disease Progression in Patients with Primary Open-Angle Glaucoma

• Activity Number: 571
• Type: Contributed
• Date/Time: Wednesday, August 3, 2011 : 2:00 PM to 3:50 PM
• Sponsor: Biometrics Section
• Author(s): Feng Gao*+ and J. Philip Miller and Julia Beiser and Chengjie Xiong and Mae Gordon
• Companies: Washington University School of Medicine at St. Louis and Washington University School of Medicine at St. Louis and Washington University School of Medicine at St. Louis and Washington University and Washington University School of Medicine at St. Louis
• Keywords: Latent class growth model ; multivariate longitudinal data ; joint modeling

Abstract

Primary open-angle glaucoma (POAG) is among the leading causes of blindness in the United States and worldwide. It is characterized by a gradual loss of vision and the progression rate is often described using linear regression models that are only focused on the average change over time. However, the progression of POAG is more likely to be heterogeneous and such an average effect could mask important individual differences. In this paper, we use latent class growth model (LCGM) to assess the heterogeneity of visual loss based on the 274 patients developed POAG from the Ocular Hypertension Treatment Study (OHTS). The visual deterioration as measured by mean deviation (MD) index and patterns standard deviation (PSD), two standard global summary measures of visual field test, was described using a piecewise linear function to allow different progression rates during pre- and post-POAG periods. The optimal latent classes, their probabilities, and the predictive baseline factors were estimated for each measure. Joint modeling of multiple longitudinal data was also performed to assess the co-trajectory of visual loss and structural change over time.