title: Predicting Clinical Binary Outcome Using Multivariate Longitudinal Data: Application to Patients with Newly Diagnosed Primary Open-Angle Glaucoma.
abstract: Primary open angle glaucoma (POAG) is a chronic, progressive, irreversible, and potentially blinding optic neuropathy. The risk of blindness due to progressive visual field (VF) loss varies substantially from patient to patient. Early identification of those patients destined to rapid progressive visual loss is crucial to prevent further damage. In this article, a latent class growth model (LCGM) was developed to predict the binary outcome of VF progression using longitudinal mean deviation (MD) and pattern standard deviation (PSD). Specifically, the trajectories of MD and PSD were summarized by a functional principal component (FPC) analysis, and the estimated FPC scores were used to identify subgroups (latent classes) of individuals with distinct patterns of MD and PSD trajectories. Probability of VF progression for an individual was then estimated as weighted average across latent classes, weighted by posterior probability of class membership given baseline covariates and longitudinal MD/PSD series. The model was applied to the participants with newly diagnosed POAG from the Ocular Hypertension Treatment Study (OHTS), and the OHTS data was best fit by a model with 4 latent classes. Using the resultant optimal LCGM, the OHTS participants with and without VF progression could be accurately differentiated by incorporating longitudinal MD and PSD.
authors.affiliation: Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO, USA; Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA.
authors.forename: Feng
authors.initials: F
authors.lastname: Gao
authors.affiliation: Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA.
authors.forename: J Philip
authors.initials: JP
authors.lastname: Miller
authors.affiliation: Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, USA.
authors.forename: Julia A
authors.initials: JA
authors.lastname: Beiser
authors.affiliation: Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA.
authors.forename: Chengjie
authors.initials: C
authors.lastname: Xiong
authors.affiliation: Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA; Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, USA.
authors.forename: Mae O
authors.initials: MO
authors.lastname: Gordon
keywords: Functional principal component analysis; Latent class growth model; Multivariate longitudinal data; Primary open angle glaucoma