David P Crabb1, David F Garway-Heath. 1. Department of Optometry and Visual Science, City University London, London, United Kingdom. d.crabb@city.ac.uk
Abstract
PURPOSE: Published recommendations suggest three visual field (VF) tests per year are required to identify rapid progression in a newly diagnosed glaucomatous patient over 2 years. This report aims to determine if identification of progression would be improved by clustering tests at the beginning and end of the 2-year period. METHODS: Computer-simulated "patients" were given a rapid VF (mean deviation [MD]) loss of -2 dB/year with added MD measurement variability. Linear regression of MD against time was used to estimate progression. One group of "patients" was measured every 6 months, another every 4 months, whereas the wait-and-see group were measured either 2 or 3 times at both baseline and at the end of a 2-year period. Stable "patients" (0 dB/year) were generated to examine the effect of the follow-up patterns on false-positive (FP) progression identification. RESULTS: By 2 years, 58% and 82% of rapidly progressing patients were correctly detected using evenly spaced 6- and 4-month VFs, respectively. This power of detection significantly improved to 62% and 95% with the wait-and-see approach (P < 0.001). When compared with evenly spaced VFs, the rate of MD loss was better estimated by the wait-and-see approach, but average detection time was slightly slower. Evenly spaced testing incurred a significantly higher FP rate: up to 5.9% compared with only 0.4% in wait-and-see (P < 0.001). CONCLUSIONS: Compared with an evenly spaced follow-up, wait-and-see identifies more "patients" with rapid VF progression with fewer FPs, making it particularly applicable to clinical trials. Modeling experiments, as reported here, are useful for investigating and optimizing follow-up schemes.
PURPOSE: Published recommendations suggest three visual field (VF) tests per year are required to identify rapid progression in a newly diagnosed glaucomatouspatient over 2 years. This report aims to determine if identification of progression would be improved by clustering tests at the beginning and end of the 2-year period. METHODS: Computer-simulated "patients" were given a rapid VF (mean deviation [MD]) loss of -2 dB/year with added MD measurement variability. Linear regression of MD against time was used to estimate progression. One group of "patients" was measured every 6 months, another every 4 months, whereas the wait-and-see group were measured either 2 or 3 times at both baseline and at the end of a 2-year period. Stable "patients" (0 dB/year) were generated to examine the effect of the follow-up patterns on false-positive (FP) progression identification. RESULTS: By 2 years, 58% and 82% of rapidly progressing patients were correctly detected using evenly spaced 6- and 4-month VFs, respectively. This power of detection significantly improved to 62% and 95% with the wait-and-see approach (P < 0.001). When compared with evenly spaced VFs, the rate of MD loss was better estimated by the wait-and-see approach, but average detection time was slightly slower. Evenly spaced testing incurred a significantly higher FP rate: up to 5.9% compared with only 0.4% in wait-and-see (P < 0.001). CONCLUSIONS: Compared with an evenly spaced follow-up, wait-and-see identifies more "patients" with rapid VF progression with fewer FPs, making it particularly applicable to clinical trials. Modeling experiments, as reported here, are useful for investigating and optimizing follow-up schemes.
Authors: Michele M Iester; Gadi Wollstein; Richard A Bilonick; Juan Xu; Hiroshi Ishikawa; Larry Kagemann; Joel S Schuman Journal: Br J Ophthalmol Date: 2014-10-21 Impact factor: 4.638
Authors: Ryo Asaoka; Richard A Russell; Rizwan Malik; David F Garway-Heath; David P Crabb Journal: Graefes Arch Clin Exp Ophthalmol Date: 2012-12-07 Impact factor: 3.117
Authors: Jack Phu; Sieu K Khuu; Lisa Nivison-Smith; Barbara Zangerl; Agnes Yiu Jeung Choi; Bryan W Jones; Rebecca L Pfeiffer; Robert E Marc; Michael Kalloniatis Journal: Invest Ophthalmol Vis Sci Date: 2017-09-01 Impact factor: 4.799