PURPOSE: To describe and evaluate a computer model that simulates longitudinal visual field data. METHODS: A computer model was designed using factors that influence thresholds of normal and glaucomatous visual fields. The simulation model was used to quantify the effects of fluctuation on the outcomes of pointwise linear regression by comparison with simulated gold standard data with no variability. RESULTS: Serial sets of 10 stable and 10 progressive visual fields with different fluctuation levels were generated by simulation and were analyzed using pointwise linear regression. Regression outcome measures used were slopes of -1 dB/year or worse and slopes of -1 dB/year or worse that were also statistically significant. In stable visual fields, the number of locations with regression slopes worse than -1 dB/year increased with fluctuation and defect size and was inversely related to the number of fields. The number of locations with statistically significant slopes remained low and appeared unaffected by these variables. In progressive visual fields, analysis of a small number of visual field test results (<8) overestimated the number of locations with regression slopes worse than -1 dB/year and underestimated the number of locations with statistically significant slopes. CONCLUSIONS: Computer simulation may be used to provide a gold standard outcome that permits evaluation of statistical tools for monitoring progressive glaucomatous visual field loss.
PURPOSE: To describe and evaluate a computer model that simulates longitudinal visual field data. METHODS: A computer model was designed using factors that influence thresholds of normal and glaucomatous visual fields. The simulation model was used to quantify the effects of fluctuation on the outcomes of pointwise linear regression by comparison with simulated gold standard data with no variability. RESULTS: Serial sets of 10 stable and 10 progressive visual fields with different fluctuation levels were generated by simulation and were analyzed using pointwise linear regression. Regression outcome measures used were slopes of -1 dB/year or worse and slopes of -1 dB/year or worse that were also statistically significant. In stable visual fields, the number of locations with regression slopes worse than -1 dB/year increased with fluctuation and defect size and was inversely related to the number of fields. The number of locations with statistically significant slopes remained low and appeared unaffected by these variables. In progressive visual fields, analysis of a small number of visual field test results (<8) overestimated the number of locations with regression slopes worse than -1 dB/year and underestimated the number of locations with statistically significant slopes. CONCLUSIONS: Computer simulation may be used to provide a gold standard outcome that permits evaluation of statistical tools for monitoring progressive glaucomatous visual field loss.
Authors: Carlos Gustavo De Moraes; Shaban Demirel; Stuart K Gardiner; Jeffrey M Liebmann; George A Cioffi; Robert Ritch; Mae O Gordon; Michael A Kass Journal: Invest Ophthalmol Vis Sci Date: 2012-04-02 Impact factor: 4.799
Authors: John L Keltner; Chris A Johnson; Richard A Levine; Juanjuan Fan; Kimberly E Cello; Michael A Kass; Mae O Gordon Journal: Arch Ophthalmol Date: 2005-09
Authors: Colleen M Kummet; K D Zamba; Carrie K Doyle; Chris A Johnson; Michael Wall Journal: Invest Ophthalmol Vis Sci Date: 2013-09-19 Impact factor: 4.799
Authors: T Aung; F T S Oen; H-T Wong; Y-H Chan; B-K Khoo; Y-P Liu; C-L Ho; J See; L H Thean; A C Viswanathan; S K L Seah; P T K Chew Journal: Br J Ophthalmol Date: 2004-01 Impact factor: 4.638