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(Investigative Ophthalmology and Visual Science. 2003;44:3873-3879.)
© 2003 by The Association for Research in Vision and Ophthalmology, Inc.
DOI:  10.1167/iovs.02-1171

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Comparison of Different Methods for Detecting Glaucomatous Visual Field Progression

Eija Vesti,1,2 Chris A. Johnson,1 and Balwantray C. Chauhan3

1From Discoveries in Sight, Devers Eye Institute, Portland, Oregon; the 2Helsinki University Eye Hospital, Helsinki, Finland; and the 3Department of Ophthalmology, Dalhousie University, Halifax, Nova Scotia, Canada.

PURPOSE. To compare the performance characteristics of seven methods for analyzing glaucomatous visual field progression, using a combination of real patient data and computer simulation techniques.

METHODS. The initial and final visual field results, separated by 7 years and measured with the full-threshold 30-2 program of the Humphrey Field Analyzer (Carl Zeiss Meditec, Dublin, CA) of 76 patients with open-angle glaucoma were used. A computer simulation program generated 14 interim semiannual visual fields under conditions of high, moderate, and no variability. Progression was analyzed using the methods of the Advanced Glaucoma Intervention Study (AGIS), the Collaborative Initial Glaucoma Treatment Study (CIGTS), three criteria based on the Glaucoma Change Probability (GCP) analysis, and two criteria based on point-wise linear regression analysis (PLRA). Specificities were calculated by using the same visual field of each patient as both the initial and final field (no progression) under conditions of moderate and high variability.

RESULTS. Under the no-variability condition, progression rates were 18% for the AGIS, 36% for CIGTS, 47% to 62% for the three GCP methods, and 72% and 84% for the two PLRA methods. Progression rates increased with greater variability with the three GCP methods and decreased with all other methods. The time to detect confirmed progression was longest for the PLRA methods and shortest for the CIGTS and GCP methods. Under the moderate-variability condition, all methods yielded high specificity. The AGIS, CIGTS, and one of the GCP and PLRA methods were relatively resistant to high variability and maintained high specificities.

CONCLUSIONS. The AGIS and CIGTS methods had high specificity, but classified fewer cases of progression than the other methods. The GCP methods determined progression earliest; however, they were generally not as specific. Methods based on PLRA were specific but times to confirmed progression were the longest.





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