Defining 10-2 visual field progression criteria: exploratory and confirmatory factor analysis using pointwise linear regression.

Abstract

To test different visual field progression criteria using trend analysis in a glaucoma population followed with long sequences of 10-2 tests as a first attempt to understand and document rates of progression in the central field. Retrospective cohort study. We included 146 eyes of 146 patients with established glaucoma. Pointwise linear regression analysis using the methods of ordinary least squares was performed on the 68 test locations of the 10-2 visual field sequences. Threshold sensitivities at each test location were plotted as the dependent variable against follow-up time as the independent variable. Statistically significant progression or improvement of a visual field test point was defined if its regression slope measured ≤-1.0 dB/year or ≥+1.0 dB/year, respectively, at P<0.01. We explored sets of criteria to define visual field progression, generating a hypothetical sensitivity (progression), specificity (improvement), and progression-to-improvement ratio (PIR) for each criterion. The criterion with the highest PIR was deemed the one with best performance. Latent class analysis (LCA) was used to determine visual field sectors with highest inter-correlation. The performance of different visual field progression criteria to detect fast rates of mean deviation (MD) change. Median baseline 10-2 MD value was -12.0 dB (interquartile range [IQR], -6.7 to -17.8 dB), and the median rate of 10-2 MD change over time was -0.38 dB/year (IQR, -0.07 to -0.77 dB/year). The highest PIR was obtained with the progression criterion requiring at least 3 test points located in the same LCA-derived 10-2 visual field sector progressing faster than -1.0 dB/year at P<0.01. This criterion was further validated for content and convergence. This is the first study to investigate progression criteria for 10-2 visual fields using rates of change and to test their performance and validity. These findings may be useful to improve the monitoring of patients with glaucoma at different levels of functional loss and to develop new perimetric algorithms that scrutinize specific visual field locations for a more accurate detection of progression.