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Original Investigation |

Course of Glaucomatous Visual Field Loss Across the Entire Perimetric Range

Francisco Otarola, MD1,2; Andrew Chen, MD1; Esteban Morales, MS1; Fei Yu, PhD1; Abdelmonem Afifi, PhD3; Joseph Caprioli, MD1
[+] Author Affiliations
1Jules Stein Eye Institute, Glaucoma Division, David Geffen School of Medicine at UCLA (University of California, Los Angeles)
2Fundacion Oftalmologica los Andes, Universidad de los Andes, Santiago, Chile
3Department of Biostatistics, Jonathan and Karin Fielding School of Public Health at UCLA
JAMA Ophthalmol. 2016;134(5):496-502. doi:10.1001/jamaophthalmol.2016.0118.
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Importance  Identifying the course of glaucomatous visual field (VF) loss that progresses from normal to perimetric blindness is important for treatment and prognostication.

Objective  To model the process of glaucomatous VF decay over the entire perimetric range from normal to perimetric blindness.

Design, Setting, and Participants  A post hoc, retrospective analysis was performed using data from the Advanced Glaucoma Intervention Study and the UCLA (University of California, Los Angeles) Jules Stein Eye Institute Glaucoma Division. Patients with open-angle glaucoma and VFs obtained from reliable examinations (defined as <30% fixation losses, <30% false-positive rates, and <30% false-negative rates) were recruited. All tests were performed with standard automated perimetry and a 24-2 test pattern. Linear, exponential, and sigmoid regression models were used to assess the pattern of threshold sensitivity deterioration at each VF location as a function of time. Visual field locations of interest included those with a mean of the initial 2 sensitivities of 26 dB or greater and a less than 10-dB mean of the final 2 sensitivities. Root mean squared error (RMSE) was used to evaluate goodness of fit for each regression model. The error was defined as the difference between the sensitivities modeled by the function and the observed sensitivities. The Advanced Glaucoma Intervention Study was conducted from 1998 to 2006; the present post hoc analysis was conducted from March 1, 2014, to March 1, 2015.

Main Outcomes and Measures  The RMSE of the residuals (fitted minus observed values) for the 3 regression models was used to evaluate goodness of fit.

Results  A total of 798 eyes from 583 patients (mean [SD] age, 64.7 [10.7] years; 301 [51.6%] women) who had more than 6 years of follow-up and underwent more than 10 VF examinations were included in this analysis. Mean (SD) follow-up time was 8.7 (2.2) years, and each eye had a mean of 15.2 (4.9) VF tests. For the VF locations with an initial sensitivity of 26 dB or greater and final sensitivity of less than 10 dB (309 locations), the sigmoid best-fit regression model had the lowest RMSE in 248 (80.3%) of the locations, the exponential function in 39 (12.6%), and the linear function in 22 (7.1%). The means (SDs) of RMSE were sigmoid, 4.1 (1.9); exponential, 6.0 (1.5); and linear 5.8 (1.6).

Conclusions and Relevance  Pointwise sigmoid regression had a better ability to fit perimetric decay into a subset of locations that traverse the entire range of perimetric measurements from near normal to near perimetric blindness compared with linear and exponential functions. These results support the concept that the measured behavior of glaucomatous VF loss to perimetric blindness is nonlinear and that its course of deterioration may change with the course of disease.

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Figure 1.
Frequency Distribution of the Initial and Final Visual Field Sensitivities for All Visual Field Locations

A total of 798 eyes of 583 patients were included.

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Figure 2.
Fits of Linear, Exponential, and Sigmoid Regression Models

Eight sample locations with initial sensitivity values greater than 30 dB and final sensitivity less than 10 dB are presented.

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Figure 3.
Illustration of a Sigmoid Regression Model Fit for a Single Visual Field Location

The drop-off, inflection, and level-off points are highlighted with a gray square.

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