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Clinical Sciences |

Association Between Rates of Binocular Visual Field Loss and Vision-Related Quality of Life in Patients With Glaucoma FREE

Renato Lisboa, MD; Yeoun Sook Chun, MD; Linda M. Zangwill, PhD; Robert N. Weinreb, MD; Peter N. Rosen, MD; Jeffrey M. Liebmann, MD; Christopher A. Girkin, MD; Felipe A. Medeiros, MD, PhD
[+] Author Affiliations

Author Affiliations: Hamilton Glaucoma Center and Department of Ophthalmology, University of California, San Diego (Drs Lisboa, Chun, Zangwill, Weinreb, Rosen, and Medeiros); Department of Ophthalmology, Federal University of São Paulo, São Paulo, Brazil (Dr Lisboa); Department of Ophthalmology, College of Medicine, Chung-Ang University, Seoul, Korea (Dr Chun); Department of Ophthalmology, New York Eye and Ear Infirmary, New York, New York (Dr Liebmann); and Department of Ophthalmology, University of Alabama, Birmingham (Dr Girkin).


JAMA Ophthalmol. 2013;131(4):486-494. doi:10.1001/jamaophthalmol.2013.2602.
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Importance It is reasonable to hypothesize that for 2 patients with similar degrees of integrated binocular visual field (BVF) loss, the patient with a history of faster disease progression will report worse vision-related quality of life (VRQOL) than the patient with slowly progressing damage. However, to our knowledge, this hypothesis has not been investigated in the literature.

Objective To evaluate the association between binocular rates of visual field change and VRQOL in patients with glaucoma.

Design Observational cohort study.

Setting Patients were recruited from the Diagnostic Innovations in Glaucoma Study and the African Descent and Glaucoma Evaluation Study.

Participants The study included 796 eyes of 398 patients with diagnosed or suspected glaucoma followed up from October 1, 1998, until January 31, 2012, for a mean (SD) of 7.3 (2.0) years.

Main Outcome Measures The VRQOL was evaluated using the 25-item National Eye Institute Visual Function Questionnaire (NEI VFQ-25) at the last follow-up visit. The NEI VFQ-25 was completed for all patients during the period extending from December 1, 2009, through January 31, 2012. Integrated BVFs were calculated from the monocular fields of each patient. Linear regression of mean deviation values was used to evaluate rates of BVF change during the follow-up period. Logistic regression models were used to investigate the association between abnormal VRQOL and rates of BVF change, while adjusting for potentially confounding socioeconomic and demographic variables.

Results Thirty-two patients (8.0%) had abnormal VRQOL as determined by the results of the NEI VFQ-25. Patients with abnormal VRQOL had significantly faster rates of BVF change than those with normal VRQOL (−0.18 vs −0.06 dB/y; P < .001). Rates of BVF change were significantly associated with abnormality in VRQOL (odds ratio = 1.31 per 0.1 dB/y faster; P = .04), after adjustment for confounding variables.

Conclusions and Relevance Patients with faster rates of BVF change were at higher risk of reporting abnormal VRQOL. Assessment of rates of BVF change may provide useful information in determining risk of functional impairment in glaucoma.

Figures in this Article

Glaucoma is a progressive optic neuropathy that may result in significant visual impairment. The loss of vision affects quality of life and also has economic consequences for the patient and society.1 The effect of glaucoma on vision-related quality of life (VRQOL) has frequently been investigated using questionnaire-based, self-reported assessments, such as the 25-item National Eye Institute Visual Function Questionnaire (NEI VFQ-25).25 Previous studies2,5 have found a significant association between the severity of visual field defects on standard automated perimetry (SAP) and the results on the NEI VFQ-25, with more severe defects associated with worse scores. Patients with visual field loss in both eyes tend to have worse scores on the NEI VFQ-25 than those with unilateral defects. For patients with asymmetric degrees of damage, visual field assessment of the less affected eye frequently shows a stronger association with questionnaire results than the more affected eye. Such an association is understandable because one eye may compensate for the loss of vision of the other eye. For this reason, it has been suggested that binocular visual field (BVF) tests may represent the best way to gauge the effect of field losses on quality of life. In the absence of “true” binocular vision tests, one can approximate the BVF by integrating the results of monocular visual fields.6 These integration methods have been found to agree closely with the “true” BVF, thus offering a practical way for studying rates of BVF change.

Previous studies2,5 investigating the association between BVF results and NEI VFQ-25 have been conducted using cross-sectional data and have only considered the visual field status at the time of questionnaire administration. This approach ignores the rate at which the patients develop visual field defects. Although significant associations have been reported between BVF and NEI VFQ-25, the strength of the association has been far less than perfect. One reason for the imperfect association between the severity of visual field damage and patient-reported VRQOL may be the development of compensatory strategies by affected patients.7 It is likely that patients with slowly progressing disease will have more time to adapt to their limited functional status by developing compensatory strategies and, therefore, will be less likely to report an abnormal VRQOL. On the other hand, in patients with rapidly progressing disease, the visual field defects may result in substantial impairment in the ability to perform daily activities without time for development of compensatory strategies. This would be more readily recognized by such a patient and more likely to be reported as an abnormal VRQOL. Therefore, it is reasonable to hypothesize that for 2 patients with similar degrees of visual field loss, the patient with a history of faster disease progression will report worse VRQOL status than the patient with slowly progressing damage. However, to our knowledge, this hypothesis has not been investigated in the literature. Our objective was to investigate the association between rates of BVF loss and results of patient-reported VRQOL outcomes in patients with glaucoma, as assessed by the NEI VFQ-25.

STUDY PATIENTS

This was an observational cohort study. Participants in this study were included in 2 prospective longitudinal studies designed to evaluate optic nerve structure and visual function in glaucoma (the African Descent and Glaucoma Evaluation Study [ADAGES] and the Diagnostic Innovations in Glaucoma Study [DIGS]). The 3-site ADAGES collaboration includes the Hamilton Glaucoma Center at the Department of Ophthalmology, University of California, San Diego (UCSD); the New York Eye and Ear Infirmary; and the Department of Ophthalmology, University of Alabama at Birmingham. Although DIGS includes only patients recruited at UCSD, the protocol of the 2 studies is identical. Methodologic details have been described previously.8 The UCSD Human Subjects Committee approved all protocols, and methods adhered to the Declaration of Helsinki.

At each visit during follow-up, patients underwent a comprehensive ophthalmic examination, including review of medical history, best-corrected visual acuity, slitlamp biomicroscopy, intraocular pressure measurement using Goldmann applanation tonometry, gonioscopy, dilated funduscopy examination using a 78-diopter (D) lens, stereoscopic optic disc photography, and SAP with 24-2 Swedish Interactive Threshold Algorithm (Carl Zeiss Meditec, Inc). To be included, patients had to have best-corrected visual acuity of 20/40 or better, spherical refraction less than ±5.0 D, cylinder correction less than 3.0 D, and open angle with gonioscopy. Patients with coexisting retinal disease, uveitis, or nonglaucomatous optic disc neuropathy were excluded from the study.

We included 796 eyes of 398 patients with diagnosed or suspected glaucoma at the baseline visit. Eyes were classified as having glaucoma based on repeatable abnormal visual field test results at baseline, defined as a pattern standard deviation with P < .05, and/or glaucoma hemifield test results outside normal limits, regardless of the appearance of the optic disc. Patients suspected of having glaucoma were defined as those with eyes with abnormal-appearing optic discs (presence of neuroretinal rim thinning or localized or diffuse retinal nerve fiber layer defects indicative of glaucoma, ie, glaucomatous optic neuropathy) by masked stereophotographic assessment without repeatable abnormal SAP results. Patients suspected of having glaucoma also included patients with eyes with intraocular pressure greater than 22 mm Hg but with healthy-appearing optic discs and without repeatable abnormal SAP results.

Each patient was required to have a minimum of 5-paired (ie, visual field tests of both eyes on the same day) SAPs during a minimum of 5 years of follow-up before completion of the NEI VFQ-25. The period of follow-up for the study started on October 1, 1998, and extended until January 31, 2012; however, patients entered and exited the study at different dates. The NEI VFQ-25 was completed for all patients during the period extending from December 1, 2009, through January 31, 2012. For each patient, only SAPs obtained before the NEI VFQ-25 were included.

MONOCULAR AND BINOCULAR VISUAL FIELDS

Monocular SAP was performed using the 24-2 Swedish Interactive Threshold Algorithm at all visits during the follow-up period. Only reliable tests (≤33% fixation losses and false-negative results and ≤15% false-positive results) were included. In addition, all visual fields were evaluated by the UCSD Visual Field Assessment Center.9 Visual fields were reviewed and excluded in the presence of artifacts, such as eyelid or rim artifacts, fatigue effects, inattention, or inappropriate fixation. Visual fields were also reviewed for the presence of abnormalities that could indicate diseases other than glaucoma, such as homonymous hemianopia.

For calculation of the estimated pointwise sensitivities of the BVF, the monocular SAP threshold sensitivities of the right and left eyes were used. The 24-2 stimulus presentation pattern consists of 54 points within the central 24° in a 6° grid bracketing the horizontal and vertical meridians. The 2 points corresponding to the blind spot and the 2 most nasal points of each eye were excluded for the calculations of the BVF. This was necessary because these points do not have a spatial correspondent in the visual field of the fellow eye. Therefore, each individual BVF had a total of 48 overlapping points, as shown in Figure 1.

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Figure 1. Schematic representation of the binocular visual field using the summation method to integrate the sensitivities of the right and left visual fields.

The sensitivity for each point of the BVF was estimated using the binocular summation model described by Nelson-Quigg et al.6 According to this model, the binocular sensitivity can be estimated using the following formula:

where Sr and Sl are the monocular threshold sensitivities for corresponding visual field locations of the right and left eyes, respectively. To calculate the binocular sensitivity from this formula, light sensitivity had to be converted to a linear scale (apostilbs) and then converted back to logarithmic scale (decibels).

Evaluation of rates of visual field change during follow-up was performed using the mean deviation (MD). For calculation of monocular and BVF MD, we applied the formula described by Anderson10:

where L is the total number of locations, TDi is the total deviation in decibels of the normal age-matched population at location i, and Si2 is the variance of the i point in the same normal age-matched population. We used data from 102 paired visual fields of age-matched patients from the DIGS and ADAGES cohorts to calculate the TDi and the Si2 of monocular and binocular visual fields.

NATIONAL EYE INSTITUTE VISUAL FUNCTION QUESTIONNAIRE

The VRQOL was evaluated using the NEI VFQ-25. This questionnaire was designed to assess the dimensions of self-reported vision-target health status that are relevant for patients with chronic eye diseases.11,12 The NEI VFQ-25 consists of a base set of 25 vision-targeted questions that represent 11 vision-related constructs, plus an additional single-item general health rating question. The vision-related scales are as follows: general vision, near- and distance-vision activities, ocular pain, vision-related social function, vision-related role function, vision-related mental health, vision-related dependency, driving difficulties, color vision, and peripheral vision. Each subscale consists of a minimum of 1 item and a maximum of 4 items. The standard algorithm used to score the results has a scale ranging from 0 to 100, with higher scores representing better visual functioning and well-being. In this format, scores represent the achieved percentage of the total possible score (eg, a score of 50 represents 50% of the highest possible score). Thirty-six patients did not answer questions related to driving difficulties because they were not active drivers. Missing data were imputed using multivariable linear regression with information from the other NEI VFQ-25 variables.

We defined abnormal VRQOL as the presence of a score less than 50 on any 1 of the 10 vision-related subscales of the NEI VFQ-25, excluding the subscale related to ocular pain. This corresponds to approximately 2 SDs below the scores previously described for a normal reference population.12

DEMOGRAPHIC, CLINICAL, AND SOCIOECONOMIC VARIABLES

Socioeconomic and clinical questionnaires were also administered to patients at the time of the NEI VFQ-25. These questionnaires contained a survey about demographics, history of ocular and medical conditions, marital status, health insurance coverage, educational level, and income. Because these variables could potentially affect patient perceptions about VRQOL, they were included as potentially confounding factors in the analysis of the association between BVF change and NEI VFQ-25 results. These variables were categorized for inclusion in the multivariable models as marital status (married [yes/no]), presence of health insurance (yes/no), educational level (at least high school degree [yes/no]), and income (<$25 000 per year [yes/no]). Seventy-eight patients refused to provide income information. Missing data were imputed based on a multivariable logistic regression using data from the other socioeconomic variables. For comorbidities, we investigated the presence or history of the following conditions: arthritis, asthma, cancers, depression, diabetes mellitus, heart disease, hypertension, and stroke. A simple summation score was used to create a comorbidity index.13 Visual acuity was measured using an Early Treatment Diabetic Retinopathy chart, and logMAR measurements were used in the analyses. Diagnostic categorization at baseline (glaucoma [yes/no]) was also included in the analyses because glaucomatous patients and those suspected of having glaucoma could have different perceptions about VRQOL.

During follow-up, patients were treated at the discretion of the attending ophthalmologist. History of topical antiglaucomatous treatment during follow-up was also included as a potentially confounding variable in multivariable analysis.

STATISTICAL ANALYSIS

Descriptive statistics included mean (SD) for normally distributed variables and median and interquartile range for nonnormally distributed variables. The association between changesin BVF MD and abnormality in VRQOL was initially investigated using a random-intercept, random-slope, linear-mixed model with a t -distribution for random effects.1420 In these models, the mean evolution of a specific response is described using some function of time, and patient-specific deviations from this mean evolution are introduced by random intercepts and random slopes, allowing for different baseline values and different rates of change for each eye. In the linear mixed model, BVF MD values were considered the dependent variable. The presence of abnormality in VRQOL was included as a fixed-effect covariate with a value of 1 if the patient had an abnormal VRQOL as determined by the NEI VFQ-25 and a value of 0 if the patient had a normal VRQOL. Time was included as a continuous predictor. The 2-way interaction between time and VRQOL was included in the model to evaluate whether there was a significant difference in longitudinal BVF MD over time between those with normal and abnormal VRQOL. Rates of change were calculated for the BVF and for monocular visual field examinations. For each patient, eyes with faster (more negative slope) and slower rates of change (more positive slope) were identified as the worse and better eyes, respectively.

We were interested in whether rates of BVF change were predictive of abnormality in VRQOL. For this analysis, we investigated the association between VRQOL (dependent variable) and rates of BVF change using a multivariable logistic model, after adjusting for the described potentially confounding demographic, clinical, and socioeconomic variables. We also adjusted for the BVF MD value closest to the NEI VFQ-25 to determine whether rates of BVF change could provide statistically independent information besides that provided by the most recent BVF in predicting abnormality in VRQOL.

All statistical analyses were performed with commercially available software (STATA, version 11; StataCorp LP). The α level (type I error) was set at .05.

This study included 3678 calculated BVFs of 398 patients followed up for a mean (SD) of 7.3 (2.0) years before the completion of the NEI VFQ-25. Mean (SD) age at the questionnaire visit was 65.7 (11.6) years. Two hundred twenty-two (55.8%) patients were white, 167 (42.0%) were African American, and 9 (2.2%) were of other race/ethnicity. Two hundred thirty-four (58.8%) were female, and 164 (41.2%) were male. The mean (SD) number of visits during follow-up was 9.2 (3.2).

Thirty-two patients (8.0%) had abnormal VRQOL as determined by the results of the NEI VFQ-25. Table 1 lists the baseline clinical and demographic characteristics for patients with normal and abnormal VRQOL. Patients with abnormal VRQOL had significantly faster rates of BVF change than those without normal VRQOL (−0.18 vs −0.06 dB/y; P < .001). The follow-up time was similar between groups (7.4 [2.0] vs 6.8 [1.8]; P = .13). Table 2 lists the results of the NEI VFQ-25 component scores in patients who had normal VRQOL vs those who had abnormal VRQOL. Statistically significant differences were found for all vision-related subscales.

Table Graphic Jump LocationTable 1. Baseline Clinical and Demographic Characteristics of Patients With Normal and Abnormal Vision-Related Quality of Life
Table Graphic Jump LocationTable 2. Results of the National Eye Institute Visual Function Questionnaire in Patients With Normal and Abnormal Vision-Related Quality of Life

We investigated whether rates of BVF change were indicative of abnormality in VRQOL, after adjusting for BVF MD closest to the NEI VFQ-25 and other demographic, clinical, and socioeconomic variables in a logistic regression model. Table 3 lists the results of the univariable and multivariable logistic regression analyses. In univariable regressions, the rate of BVF change (odds ratio [OR] = 1.23 per 0.1 dB/y faster; P = .001), lower BVF MD closest to the questionnaire visit (OR = 1.10 per 1 dB lower; P = .03), younger age (OR = 1.39 per decade younger; P = .008), and lower income (OR = 3.67; P < .001) were significantly associated with abnormality in VRQOL. Being married at the time of the VRQOL questionnaire was associated with a decrease in the odds of having abnormal VRQOL (OR = 0.43; P = .03). Higher educational level (OR = 2.01; P = .10), longer follow-upperiod (OR = 0.85 per year longer; P = .13), higher comorbidity index (OR = 1.34 per additional comorbidity; P = .07), and African American ancestry (OR = 1.63; P = .18) tended to be associated with abnormal VRQOL, but the association did not reach statistical significance. All other variables had univariable associations with > .20. All variables with P < .20 were entered in the multivariable model as indicated in Table 3. Rate of BVF change was still significantly associated with abnormality in VRQOL even after adjustment for degree of BVF loss (MD at the visit closest to questionnaire administration) and other confounding variables (OR = 1.31 per 0.1 dB/y faster; P = .04). Each 0.1-dB/y faster slope of BVF change was associated with a 31% increase in the odds of abnormality in VRQOL. Age (OR = 1.62 per decade younger; P = .008) and income (OR = 2.87; P = .02) were also significantly associated with abnormal VRQOL in the multivariable logistic model. Figure 2 shows the probability of reporting abnormal VRQOL according to the slope of BVF MD over time. Patients with faster rates of BVF change had a higher chance of reporting abnormality in VRQOL.

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Figure 2. Probability of reporting abnormal vision-related quality of life (VRQOL) according to the slope of the binocular visual field (BVF) mean deviation (MD) over time. Patients with faster rates of BVF change had a higher probability of reporting abnormal VRQOL.

Table Graphic Jump LocationTable 3. Results of the Univariable and Multiviable Logistic Regression Models for Prediction of Abnormality in Vision-Related Quality of Life

We also evaluated whether the rate of visual field change of the worse and the better eyes was independently associated with abnormal VRQOL, after adjusting for the MD and for the same demographic, clinical, and socioeconomic variables specified previously. Rates of visual field change for the worse (OR = 1.12 per 0.1 dB/y faster; P = .10) and better eyes (OR = 1.14 per 0.1 dB/y faster; P = .10) were not statistically associated with abnormal VRQOL.

Figure 3 shows visual field test results of 2 patients included in the study who had similar BVF damage at the time corresponding to the questionnaire visit. Patient A had an abnormal VRQOL, whereas patient B had a normal VRQOL. During the follow-up period before the questionnaire administration, patient A had a rate of change of −1.29 dB/y and clearly showed progression in the BVF. Conversely, patient B had a much slower rate of change of −0.22 dB/y during follow-up.

Place holder to copy figure label and caption
Graphic Jump Location

Figure 3. Example of binocular visual field (BVF) results of 2 patients included in the study who had similar visual field damage at the time of the questionnaire. A, Patient who reported an abnormal vision-related quality of life (VRQOL) on the 25-item National Eye Institute Visual Function Questionnaire (NEI VFQ-25) and clearly showed progression during the follow-up period of 5 years, with a mean rate of change of −1.29 dB/y. B, Patient with normal VRQOL and slower rate of visual field loss of −0.22 dB/y during the follow-up period of 7 years. MD indicates mean deviation.

In the present study, we demonstrated that progressive loss in BVF sensitivity was associated with self-reported abnormal VRQOL, measured by the NEI VFQ-25. Information provided by rates of BVF change was statistically predictive of abnormality in VRQOL even after adjustment for the degree of BVF loss at the time of questionnaire administration and other demographic and clinical potential confounders. Rates of BVF change also provided more information than monocular rates of change and cross-sectional visual field information for predicting VRQOL. To the best of our knowledge, this is the first study to relate rates of progressive BVF damage to self-reported VRQOL outcomes in glaucoma. These results may have significant implications for evaluation of the risk for developing functional impairment in glaucoma.

Each 0.1-dB/y faster rate of BVF change was associated with a 31% increase in the odds of reporting abnormal VRQOL. When we investigated the association between monocular rates of visual field change (better and worse eyes) and abnormality in VRQOL, we observed that the predictive abilities were inferior to that of the BVF. Moreover, the association between monocular rates of visual field change and abnormality in VRQOL did not reach statistical significance. These results indicate that longitudinal assessment of the integrated BVF seems to provide more information for detecting patients at risk of presenting functional impairment than assessment of monocular visual fields separately. This finding can be explained by the fact that the BVF combines the sensitivities of both visual fields and, therefore, is likely to be a better representation of the patient's experience of the external world.

Cross-sectional information provided by the BVF MD was statistically associated with abnormality in VRQOL in the univariable logistic model. This result is in agreement with previous studies2,5,21 that have evaluated the association between BVF damage and VRQOL. However, cross-sectional information was not statistically associated with abnormality in VRQOL after adjustment for longitudinal information provided by the rate of BVF change and other clinical and demographic characteristics. This finding may be explained by the fact that having a sequence of visual field tests is likely to provide a more robust evaluation of the visual field status than a single test, which is subject to much more variability and may not always reflect the true existing impairment.22,23 Our findings indicate the importance of calculating rates of BVF change instead of relying only on the information provided by a single visual field examination to estimate risks of functional impairment.

Our results are not surprising if one considers that patients progressing at a faster rate in the BVF would most likely have less time to adapt to losses in quality of vision, resulting in a significantly greater effect in their daily activities. Previous studies7,24 have demonstrated that individuals with macular degeneration, for example, develop perceptual plasticity that may help them adapt to central visual field damage. It is reasonable to consider that a similar process may occur after glaucomatous visual field losses. Experimental studies2527 suggest that these mechanisms are not immediate and that long-term neuronal reorganization of the visual cortex is necessary. Similarly, the development of other compensatory mechanisms, which would enable patients to cope better with losses of visual function, are likely to occur relatively slowly. Therefore, patients with fast progressive disease may not have enough time to develop those compensatory mechanisms and would be the ones most likely to report worse VRQOL scores. However, potential compensatory mechanisms that follow visual field damage in glaucoma are not completely clear. In fact, previous studies2831 have suggested that patients with peripheral visual field loss tend to ignore the region with scotoma rather than making more eye movements to compensate for the loss. Further studies should attempt to evaluate compensatory mechanisms developed by glaucoma patients in the context of their ability to perform everyday activities and the effect of disease on quality of life.

We used estimated BVFs from monocular visual fields instead of “true” BVFs. Although “true” BVFs can be obtained using specific perimetric strategies, they are not routinely performed in clinical practice. Among the several different methods previously proposed for construction of the integrated BVF from monocular fields, we used the summation method because it has been found to have a superior correlation with the “true” BVF examination compared with other approaches.6 Although the methods used in our study to calculate BVF rates of change require some mathematical calculations, they can be easily implemented into the standard software of visual field instruments to provide clinicians with information about rates of BVF change, which may help determine risk of functional impairment.

The NEI VFQ-25 was used to assess VRQOL. This questionnaire has been previously validated to investigate quality of life in patients with chronic eye diseases and had a better correlation with visual impairment than other questionnaires.2,5,32 However, no consensus exists on how to classify patients based on the results of the NEI VFQ-25. In our study, we determined that abnormality in VRQOL was present if at least 1 of the 10 vision-related subscores was below 50, excluding the one related to ocular pain. This would represent at least 2 SDs below the scores measured on a reference population.12 This classification ensured the identification of a subgroup with significant abnormality in VRQOL, as indicated by the significant differences for all subscales listed in Table 2. In addition, the general clinical and socioeconomic variables associated with abnormal VRQOL in our analyses are in agreement with previous studies.33

Our study has limitations. We did not have longitudinal data on the NEI VFQ-25, and the incidence of VRQOL could not be established in our cohort. Therefore, a causal association between rates of visual field loss and loss in VRQOL could not be established. However, the design of our study is similar to those that have investigated associations between quality of life and a number of predictive factors in several diseases. Despite their limitations, such investigations can still provide important information about factors associated with a particular response and motivate the conduct of studies with more complex designs. Although the association found in our study was still significant after adjustment for potentially confounding variables, prospective studies determining the time course of development of functional impairment in glaucoma and its associated factors will be paramount. Another limitation of our study is that we assumed a linear rate of BVF change over time. Several studies3437 have suggested that functional changes do not follow a linear course during the natural history of the disease, which might be related to the logarithmic scaling (decibel) of visual field sensitivity data. Nevertheless, the assumption of linear change is probably a reasonable one for short and medium follow-up periods, as performed in clinical practice. Another limitation is that the NEI VFQ-25 is an instrument that provides subjective measure of VRQOL. As a consequence, this questionnaire may not reflect the true impairment experienced by patients in daily activities. It is known, for example, that adults with aging-associated cognitive impairment have a tendency to overestimate functional abilities,38 whereas patients with depression tend to underestimate their abilities.30,40 The use of more objective tests, such as driving simulators,41 could potentially provide a more accurate representation of the impairment experienced by glaucomatous patients on daily activities. Future studies should investigate the association between rates of visual field loss and objective measures of functional impairment.

In conclusion, rates of progressive BVF loss were predictive of abnormality in VRQOL and may be helpful in identifying patients at risk for development of functional impairment from glaucoma. Longitudinal information on BVFs was more predictive of VRQOL abnormality than longitudinal monocular information and cross-sectional evaluation of visual field damage.

Correspondence: Felipe A. Medeiros, MD, PhD, Hamilton Glaucoma Center, University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093 (fmedeiros@glaucoma.ucsd.edu).

Submitted for Publication: October 16, 2012; final revision received November 29, 2012; accepted December 3, 2012.

Published Online: February 28, 2013. doi:10.1001/jamaophthalmol.2013.2602

Conflict of Interest Disclosures: Dr Zangwill has received research instrument support from Heidelberg Engineering; Carl Zeiss Meditec, Inc; Optovue, Inc; and Topcon, Inc. Dr Weinreb has worked as a consultant for Meditec-Zeiss. Dr Liebmann has worked as a consultant for Alcon Laboratories, Inc; Allergan, Inc; Diopsys, Inc; Optovue, Inc; Glaukos, Inc; Quark, Inc; and Merz Laboratories, Inc, and received research support from Carl Zeiss Meditec, Inc; Diopsys, Inc; Optovue, Inc; Pfizer, Inc; Alcon Laboratories, Inc; Merck, Inc; Allergan, Inc; Topcon Medical Systems, Inc; and Glaukos, Inc. Dr Medeiros has received financial support from Carl-Zeiss Meditec, Inc, and Heidelberg Engineering, GmBH.

Funding/Support: This study was supported in part by grants EY021818 (Dr Medeiros), EY11008 (Dr Zangwill), and EY14267 (Dr Zangwill) from the National Institutes of Health/National Eye Institute; CAPES (Coordenação de Aperfeiçoamento de Pessoal de Níel Superior) grant BEX 1066/11-0; an unrestricted grant from Research to Prevent Blindness; and participant retention incentive grants in the form of glaucoma medication at no cost from Alcon Laboratories, Inc; Allergan, Inc; Pfizer, Inc; Merck, Inc; and Santen, Inc.

Weinreb RN, Khaw PT. Primary open-angle glaucoma.  Lancet. 2004;363(9422):1711-1720
PubMed   |  Link to Article
McKean-Cowdin R, Wang Y, Wu J, Azen SP, Varma R.Los Angeles Latino Eye Study Group.  Impact of visual field loss on health-related quality of life in glaucoma: the Los Angeles Latino Eye Study.  Ophthalmology. 2008;115(6):941-948
PubMed   |  Link to Article
Spaeth G, Walt J, Keener J. Evaluation of quality of life for patients with glaucoma.  Am J Ophthalmol. 2006;141(1):(suppl)  S3-S14
PubMed   |  Link to Article
Jampel HD. Glaucoma patients' assessment of their visual function and quality of life.  Trans Am Ophthalmol Soc. 2001;99:301-317
PubMed
van Gestel A, Webers CA, Beckers HJ,  et al.  The relationship between visual field loss in glaucoma and health-related quality-of-life.  Eye (Lond). 2010;24(12):1759-1769
PubMed   |  Link to Article
Nelson-Quigg JM, Cello K, Johnson CA. Predicting binocular visual field sensitivity from monocular visual field results.  Invest Ophthalmol Vis Sci. 2000;41(8):2212-2221
PubMed
Huxlin KR. Perceptual plasticity in damaged adult visual systems.  Vision Res. 2008;48(20):2154-2166
PubMed   |  Link to Article
Racette L, Liebmann JM, Girkin CA,  et al; ADAGES Group.  African Descent and Glaucoma Evaluation Study (ADAGES), III: Ancestry differences in visual function in healthy eyes.  Arch Ophthalmol. 2010;128(5):551-559
PubMed   |  Link to Article
Sample PA, Girkin CA, Zangwill LM,  et al; African Descent and Glaucoma Evaluation Study Group.  The African Descent and Glaucoma Evaluation Study (ADAGES): design and baseline data.  Arch Ophthalmol. 2009;127(9):1136-1145
PubMed   |  Link to Article
Anderson DR. The single field printout with Statpac analysis. In: Kist K, ed. Automated Static Perimetry. St Louis, MO: Mosby; 1992:84
Mangione CM, Lee PP, Gutierrez PR, Spritzer K, Berry S, Hays RD.National Eye Institute Visual Function Questionnaire Field Test Investigators.  Development of the 25-item National Eye Institute Visual Function Questionnaire.  Arch Ophthalmol. 2001;119(7):1050-1058
PubMed   |  Link to Article
Mangione CM, Lee PP, Pitts J, Gutierrez P, Berry S, Hays RD.NEI-VFQ Field Test Investigators.  Psychometric properties of the National Eye Institute Visual Function Questionnaire (NEI-VFQ).  Arch Ophthalmol. 1998;116(11):1496-1504
PubMed
Globe DR, Varma R, Torres M, Wu J, Klein R, Azen SP.Los Angeles Latino Eye Study Group.  Self-reported comorbidities and visual function in a population-based study: the Los Angeles Latino Eye Study.  Arch Ophthalmol. 2005;123(6):815-821
PubMed   |  Link to Article
Medeiros FA, Zangwill LM, Alencar LM,  et al.  Detection of glaucoma progression with stratus OCT retinal nerve fiber layer, optic nerve head, and macular thickness measurements.  Invest Ophthalmol Vis Sci. 2009;50(12):5741-5748
PubMed   |  Link to Article
Medeiros FA, Zangwill LM, Alencar LM, Sample PA, Weinreb RN. Rates of progressive retinal nerve fiber layer loss in glaucoma measured by scanning laser polarimetry.  Am J Ophthalmol. 2010;149(6):908-915
PubMed   |  Link to Article
Cnaan A, Laird NM, Slasor P. Using the general linear mixed model to analyse unbalanced repeated measures and longitudinal data.  Stat Med. 1997;16(20):2349-2380
PubMed   |  Link to Article
Feldman HA. Families of lines: random effects in linear regression analysis.  J Appl Physiol. 1988;64(4):1721-1732
PubMed
Medeiros FA, Alencar LM, Zangwill LM,  et al.  Detection of progressive retinal nerve fiber layer loss in glaucoma using scanning laser polarimetry with variable corneal compensation.  Invest Ophthalmol Vis Sci. 2009;50(4):1675-1681
PubMed   |  Link to Article
Medeiros FA, Leite MT, Zangwill LM, Weinreb RN. Combining structural and functional measurements to improve detection of glaucoma progression using Bayesian hierarchical models.  Invest Ophthalmol Vis Sci. 2011;52(8):5794-5803
PubMed   |  Link to Article
Lee KJ, Thompson SG. Flexible parametric models for random-effects distributions.  Stat Med. 2008;27(3):418-434
PubMed   |  Link to Article
Jampel HD, Friedman DS, Quigley H, Miller R. Correlation of the binocular visual field with patient assessment of vision.  Invest Ophthalmol Vis Sci. 2002;43(4):1059-1067
PubMed
Artes PH, Chauhan BC. Longitudinal changes in the visual field and optic disc in glaucoma.  Prog Retin Eye Res. 2005;24(3):333-354
PubMed   |  Link to Article
Vesti E, Johnson CA, Chauhan BC. Comparison of different methods for detecting glaucomatous visual field progression.  Invest Ophthalmol Vis Sci. 2003;44(9):3873-3879
PubMed   |  Link to Article
Zur D, Ullman S. Filling-in of retinal scotomas.  Vision Res. 2003;43(9):971-982
PubMed   |  Link to Article
Calford MB, Wright LL, Metha AB, Taglianetti V. Topographic plasticity in primary visual cortex is mediated by local corticocortical connections.  J Neurosci. 2003;23(16):6434-6442
PubMed
Darian-Smith C, Gilbert CD. Axonal sprouting accompanies functional reorganization in adult cat striate cortex.  Nature. 1994;368(6473):737-740
PubMed   |  Link to Article
Darian-Smith C, Gilbert CD. Topographic reorganization in the striate cortex of the adult cat and monkey is cortically mediated.  J Neurosci. 1995;15(3, pt 1):1631-1647
PubMed
Crabb DP, Smith ND, Rauscher FG,  et al.  Exploring eye movements in patients with glaucoma when viewing a driving scene.  PLoS One. 2010;5(3):e9710
PubMed   |  Link to Article
Wiecek E, Pasquale LR, Fiser J, Dakin S, Bex PJ. Effects of peripheral visual field loss on eye movements during visual search.  Front Psychol. 2012;3:472
PubMed   |  Link to Article
Vargas-Martín F, Peli E. Eye movements of patients with tunnel vision while walking.  Invest Ophthalmol Vis Sci. 2006;47(12):5295-5302
PubMed   |  Link to Article
Luo G, Vargas-Martin F, Peli E. The role of peripheral vision in saccade planning: learning from people with tunnel vision.  J Vis. 2008;8(14):25.1-8
PubMed   |  Link to Article
Varma R, Wu J, Chong K, Azen SP, Hays RD.Los Angeles Latino Eye Study Group.  Impact of severity and bilaterality of visual impairment on health-related quality of life.  Ophthalmology. 2006;113(10):1846-1853
PubMed   |  Link to Article
Broman AT, Munoz B, Rodriguez J,  et al.  The impact of visual impairment and eye disease on vision-related quality of life in a Mexican-American population: proyecto VER.  Invest Ophthalmol Vis Sci. 2002;43(11):3393-3398
PubMed
Hood DC, Kardon RH. A framework for comparing structural and functional measures of glaucomatous damage.  Prog Retin Eye Res. 2007;26(6):688-710
PubMed   |  Link to Article
Ajtony C, Balla Z, Somoskeoy S, Kovacs B. Relationship between visual field sensitivity and retinal nerve fiber layer thickness as measured by optical coherence tomography.  Invest Ophthalmol Vis Sci. 2007;48(1):258-263
PubMed   |  Link to Article
Strouthidis NG, Vinciotti V, Tucker AJ, Gardiner SK, Crabb DP, Garway-Heath DF. Structure and function in glaucoma: the relationship between a functional visual field map and an anatomic retinal map.  Invest Ophthalmol Vis Sci. 2006;47(12):5356-5362
PubMed   |  Link to Article
Medeiros FA, Zangwill LM, Bowd C, Mansouri K, Weinreb RN. The structure and function relationship in glaucoma: implications for detection of progression and measurement of rates of change. Invest Ophthalmol Vis Sci. 2012;53(11):6939-6946
Rubenstein LZ, Schairer C, Wieland GD, Kane R. Systematic biases in functional status assessment of elderly adults: effects of different data sources.  J Gerontol. 1984;39(6):686-691
PubMed   |  Link to Article
Kuriansky JB, Gurland BJ, Fleiss JL, Cowan D. The assessment of self-care capacity in geriatric psychiatric patients by objective and subjective methods.  J Clin Psychol. 1976;32(1):95-102
PubMed   |  Link to Article
Kiyak HA, Teri L, Borson S. Physical and functional health assessment in normal aging and in Alzheimer's disease: self-reports vs family reports.  Gerontologist. 1994;34(3):324-330
PubMed   |  Link to Article
Medeiros FA, Weinreb RN, Boer ER, Rosen PN. Driving simulation as a performance-based test of visual impairment in glaucoma.  J Glaucoma. 2012;21(4):221-227
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Graphic Jump Location

Figure 1. Schematic representation of the binocular visual field using the summation method to integrate the sensitivities of the right and left visual fields.

Place holder to copy figure label and caption
Graphic Jump Location

Figure 2. Probability of reporting abnormal vision-related quality of life (VRQOL) according to the slope of the binocular visual field (BVF) mean deviation (MD) over time. Patients with faster rates of BVF change had a higher probability of reporting abnormal VRQOL.

Place holder to copy figure label and caption
Graphic Jump Location

Figure 3. Example of binocular visual field (BVF) results of 2 patients included in the study who had similar visual field damage at the time of the questionnaire. A, Patient who reported an abnormal vision-related quality of life (VRQOL) on the 25-item National Eye Institute Visual Function Questionnaire (NEI VFQ-25) and clearly showed progression during the follow-up period of 5 years, with a mean rate of change of −1.29 dB/y. B, Patient with normal VRQOL and slower rate of visual field loss of −0.22 dB/y during the follow-up period of 7 years. MD indicates mean deviation.

Tables

Table Graphic Jump LocationTable 1. Baseline Clinical and Demographic Characteristics of Patients With Normal and Abnormal Vision-Related Quality of Life
Table Graphic Jump LocationTable 2. Results of the National Eye Institute Visual Function Questionnaire in Patients With Normal and Abnormal Vision-Related Quality of Life
Table Graphic Jump LocationTable 3. Results of the Univariable and Multiviable Logistic Regression Models for Prediction of Abnormality in Vision-Related Quality of Life

References

Weinreb RN, Khaw PT. Primary open-angle glaucoma.  Lancet. 2004;363(9422):1711-1720
PubMed   |  Link to Article
McKean-Cowdin R, Wang Y, Wu J, Azen SP, Varma R.Los Angeles Latino Eye Study Group.  Impact of visual field loss on health-related quality of life in glaucoma: the Los Angeles Latino Eye Study.  Ophthalmology. 2008;115(6):941-948
PubMed   |  Link to Article
Spaeth G, Walt J, Keener J. Evaluation of quality of life for patients with glaucoma.  Am J Ophthalmol. 2006;141(1):(suppl)  S3-S14
PubMed   |  Link to Article
Jampel HD. Glaucoma patients' assessment of their visual function and quality of life.  Trans Am Ophthalmol Soc. 2001;99:301-317
PubMed
van Gestel A, Webers CA, Beckers HJ,  et al.  The relationship between visual field loss in glaucoma and health-related quality-of-life.  Eye (Lond). 2010;24(12):1759-1769
PubMed   |  Link to Article
Nelson-Quigg JM, Cello K, Johnson CA. Predicting binocular visual field sensitivity from monocular visual field results.  Invest Ophthalmol Vis Sci. 2000;41(8):2212-2221
PubMed
Huxlin KR. Perceptual plasticity in damaged adult visual systems.  Vision Res. 2008;48(20):2154-2166
PubMed   |  Link to Article
Racette L, Liebmann JM, Girkin CA,  et al; ADAGES Group.  African Descent and Glaucoma Evaluation Study (ADAGES), III: Ancestry differences in visual function in healthy eyes.  Arch Ophthalmol. 2010;128(5):551-559
PubMed   |  Link to Article
Sample PA, Girkin CA, Zangwill LM,  et al; African Descent and Glaucoma Evaluation Study Group.  The African Descent and Glaucoma Evaluation Study (ADAGES): design and baseline data.  Arch Ophthalmol. 2009;127(9):1136-1145
PubMed   |  Link to Article
Anderson DR. The single field printout with Statpac analysis. In: Kist K, ed. Automated Static Perimetry. St Louis, MO: Mosby; 1992:84
Mangione CM, Lee PP, Gutierrez PR, Spritzer K, Berry S, Hays RD.National Eye Institute Visual Function Questionnaire Field Test Investigators.  Development of the 25-item National Eye Institute Visual Function Questionnaire.  Arch Ophthalmol. 2001;119(7):1050-1058
PubMed   |  Link to Article
Mangione CM, Lee PP, Pitts J, Gutierrez P, Berry S, Hays RD.NEI-VFQ Field Test Investigators.  Psychometric properties of the National Eye Institute Visual Function Questionnaire (NEI-VFQ).  Arch Ophthalmol. 1998;116(11):1496-1504
PubMed
Globe DR, Varma R, Torres M, Wu J, Klein R, Azen SP.Los Angeles Latino Eye Study Group.  Self-reported comorbidities and visual function in a population-based study: the Los Angeles Latino Eye Study.  Arch Ophthalmol. 2005;123(6):815-821
PubMed   |  Link to Article
Medeiros FA, Zangwill LM, Alencar LM,  et al.  Detection of glaucoma progression with stratus OCT retinal nerve fiber layer, optic nerve head, and macular thickness measurements.  Invest Ophthalmol Vis Sci. 2009;50(12):5741-5748
PubMed   |  Link to Article
Medeiros FA, Zangwill LM, Alencar LM, Sample PA, Weinreb RN. Rates of progressive retinal nerve fiber layer loss in glaucoma measured by scanning laser polarimetry.  Am J Ophthalmol. 2010;149(6):908-915
PubMed   |  Link to Article
Cnaan A, Laird NM, Slasor P. Using the general linear mixed model to analyse unbalanced repeated measures and longitudinal data.  Stat Med. 1997;16(20):2349-2380
PubMed   |  Link to Article
Feldman HA. Families of lines: random effects in linear regression analysis.  J Appl Physiol. 1988;64(4):1721-1732
PubMed
Medeiros FA, Alencar LM, Zangwill LM,  et al.  Detection of progressive retinal nerve fiber layer loss in glaucoma using scanning laser polarimetry with variable corneal compensation.  Invest Ophthalmol Vis Sci. 2009;50(4):1675-1681
PubMed   |  Link to Article
Medeiros FA, Leite MT, Zangwill LM, Weinreb RN. Combining structural and functional measurements to improve detection of glaucoma progression using Bayesian hierarchical models.  Invest Ophthalmol Vis Sci. 2011;52(8):5794-5803
PubMed   |  Link to Article
Lee KJ, Thompson SG. Flexible parametric models for random-effects distributions.  Stat Med. 2008;27(3):418-434
PubMed   |  Link to Article
Jampel HD, Friedman DS, Quigley H, Miller R. Correlation of the binocular visual field with patient assessment of vision.  Invest Ophthalmol Vis Sci. 2002;43(4):1059-1067
PubMed
Artes PH, Chauhan BC. Longitudinal changes in the visual field and optic disc in glaucoma.  Prog Retin Eye Res. 2005;24(3):333-354
PubMed   |  Link to Article
Vesti E, Johnson CA, Chauhan BC. Comparison of different methods for detecting glaucomatous visual field progression.  Invest Ophthalmol Vis Sci. 2003;44(9):3873-3879
PubMed   |  Link to Article
Zur D, Ullman S. Filling-in of retinal scotomas.  Vision Res. 2003;43(9):971-982
PubMed   |  Link to Article
Calford MB, Wright LL, Metha AB, Taglianetti V. Topographic plasticity in primary visual cortex is mediated by local corticocortical connections.  J Neurosci. 2003;23(16):6434-6442
PubMed
Darian-Smith C, Gilbert CD. Axonal sprouting accompanies functional reorganization in adult cat striate cortex.  Nature. 1994;368(6473):737-740
PubMed   |  Link to Article
Darian-Smith C, Gilbert CD. Topographic reorganization in the striate cortex of the adult cat and monkey is cortically mediated.  J Neurosci. 1995;15(3, pt 1):1631-1647
PubMed
Crabb DP, Smith ND, Rauscher FG,  et al.  Exploring eye movements in patients with glaucoma when viewing a driving scene.  PLoS One. 2010;5(3):e9710
PubMed   |  Link to Article
Wiecek E, Pasquale LR, Fiser J, Dakin S, Bex PJ. Effects of peripheral visual field loss on eye movements during visual search.  Front Psychol. 2012;3:472
PubMed   |  Link to Article
Vargas-Martín F, Peli E. Eye movements of patients with tunnel vision while walking.  Invest Ophthalmol Vis Sci. 2006;47(12):5295-5302
PubMed   |  Link to Article
Luo G, Vargas-Martin F, Peli E. The role of peripheral vision in saccade planning: learning from people with tunnel vision.  J Vis. 2008;8(14):25.1-8
PubMed   |  Link to Article
Varma R, Wu J, Chong K, Azen SP, Hays RD.Los Angeles Latino Eye Study Group.  Impact of severity and bilaterality of visual impairment on health-related quality of life.  Ophthalmology. 2006;113(10):1846-1853
PubMed   |  Link to Article
Broman AT, Munoz B, Rodriguez J,  et al.  The impact of visual impairment and eye disease on vision-related quality of life in a Mexican-American population: proyecto VER.  Invest Ophthalmol Vis Sci. 2002;43(11):3393-3398
PubMed
Hood DC, Kardon RH. A framework for comparing structural and functional measures of glaucomatous damage.  Prog Retin Eye Res. 2007;26(6):688-710
PubMed   |  Link to Article
Ajtony C, Balla Z, Somoskeoy S, Kovacs B. Relationship between visual field sensitivity and retinal nerve fiber layer thickness as measured by optical coherence tomography.  Invest Ophthalmol Vis Sci. 2007;48(1):258-263
PubMed   |  Link to Article
Strouthidis NG, Vinciotti V, Tucker AJ, Gardiner SK, Crabb DP, Garway-Heath DF. Structure and function in glaucoma: the relationship between a functional visual field map and an anatomic retinal map.  Invest Ophthalmol Vis Sci. 2006;47(12):5356-5362
PubMed   |  Link to Article
Medeiros FA, Zangwill LM, Bowd C, Mansouri K, Weinreb RN. The structure and function relationship in glaucoma: implications for detection of progression and measurement of rates of change. Invest Ophthalmol Vis Sci. 2012;53(11):6939-6946
Rubenstein LZ, Schairer C, Wieland GD, Kane R. Systematic biases in functional status assessment of elderly adults: effects of different data sources.  J Gerontol. 1984;39(6):686-691
PubMed   |  Link to Article
Kuriansky JB, Gurland BJ, Fleiss JL, Cowan D. The assessment of self-care capacity in geriatric psychiatric patients by objective and subjective methods.  J Clin Psychol. 1976;32(1):95-102
PubMed   |  Link to Article
Kiyak HA, Teri L, Borson S. Physical and functional health assessment in normal aging and in Alzheimer's disease: self-reports vs family reports.  Gerontologist. 1994;34(3):324-330
PubMed   |  Link to Article
Medeiros FA, Weinreb RN, Boer ER, Rosen PN. Driving simulation as a performance-based test of visual impairment in glaucoma.  J Glaucoma. 2012;21(4):221-227
PubMed   |  Link to Article

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