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Figure.
Examples of the 3 patterns of baseline visual field damage evaluated in the study. A, Single superior defect. B, Single inferior defect. C, Both hemifields affected, and the points are adjacent. D, Both hemifields affected, and the points are not adjacent. Note that, for all the examples, there was good agreement between the total and pattern deviation plots, and the visual field damage was mild (mean deviation no more than −6.0 dB). GHT indicates glaucoma hemifield test; MD, mean deviation; and PSD, pattern standard deviation.

Examples of the 3 patterns of baseline visual field damage evaluated in the study. A, Single superior defect. B, Single inferior defect. C, Both hemifields affected, and the points are adjacent. D, Both hemifields affected, and the points are not adjacent. Note that, for all the examples, there was good agreement between the total and pattern deviation plots, and the visual field damage was mild (mean deviation no more than −6.0 dB). GHT indicates glaucoma hemifield test; MD, mean deviation; and PSD, pattern standard deviation.

Table 1. 
Baseline Characteristics of the Study Population
Baseline Characteristics of the Study Population
Table 2. 
Distribution of Eyes Based on Rates of Visual Field Progression
Distribution of Eyes Based on Rates of Visual Field Progression
Table 3. 
Cox Proportional Hazards Including Each Variable Independently (Univariate Model)
Cox Proportional Hazards Including Each Variable Independently (Univariate Model)
Table 4. 
Cox Proportional Hazards (Multivariate Model)
Cox Proportional Hazards (Multivariate Model)
1.
Medeiros  FAWeinreb  RN Predictive models to estimate the risk of glaucoma development and progression. Prog Brain Res 2008;17315- 24
PubMed
2.
Parrish  RK  IIGedde  SJScott  IU  et al.  Visual function and quality of life among patients with glaucoma. Arch Ophthalmol 1997;115 (11) 1447- 1455
PubMedArticle
3.
Jampel  HDFriedman  DSQuigley  HMiller  R Correlation of the binocular visual field with patient assessment of vision. Invest Ophthalmol Vis Sci 2002;43 (4) 1059- 1067
PubMed
4.
Bengtsson  BHeijl  A A visual field index for calculation of glaucoma rate of progression. Am J Ophthalmol 2008;145 (2) 343- 353
PubMedArticle
5.
Heijl  ABengtsson  BChauhan  BC  et al.  A comparison of visual field progression criteria of 3 major glaucoma trials in Early Manifest Glaucoma Trial patients. Ophthalmology 2008;115 (9) 1557- 1565
PubMedArticle
6.
Leske  MCHeijl  AHyman  LBengtsson  BDong  LYang  ZEMGT Group, Predictors of long-term progression in the Early Manifest Glaucoma Trial. Ophthalmology 2007;114 (11) 1965- 1972
PubMedArticle
7.
Miglior  STorri  VZeyen  TPfeiffer  NVaz  JCAdamsons  IEGPS Group, Intercurrent factors associated with the development of open-angle glaucoma in the European Glaucoma Prevention Study. Am J Ophthalmol 2007;144 (2) 266- 275
PubMedArticle
8.
Musch  DCGillespie  BWLichter  PRNiziol  LMJanz  NKCIGTS Study Investigators, Visual field progression in the Collaborative Initial Glaucoma Treatment Study: the impact of treatment and other baseline factors. Ophthalmology 2009;116 (2) 200- 207
PubMedArticle
9.
AGIS Investigators, The Advanced Glaucoma Intervention Study (AGIS), 12: baseline risk factors for sustained loss of visual field and visual acuity in patients with advanced glaucoma. Am J Ophthalmol 2002;134 (4) 499- 512
PubMedArticle
10.
Medeiros  FASample  PAZangwill  LMBowd  CAihara  MWeinreb  RN Corneal thickness as a risk factor for visual field loss in patients with preperimetric glaucomatous optic neuropathy. Am J Ophthalmol 2003;136 (5) 805- 813
PubMedArticle
11.
Anderson  DRPatella  VM Automated Static Perimetry. 2nd ed. St Louis, MO Mosby Inc1999;
12.
Viswanathan  ACFitzke  FWHitchings  RA Early detection of visual field progression in glaucoma: a comparison of PROGRESSOR and STATPAC 2. Br J Ophthalmol 1997;81 (12) 1037- 1042
PubMedArticle
13.
Crabb  DPFitzke  FW McNaught  AIEdgar  DFHitchings  RA Improving the prediction of visual field progression in glaucoma using spatial processing. Ophthalmology 1997;104 (3) 517- 524
PubMedArticle
14.
Strouthidis  NGScott  APeter  NMGarway-Heath  DF Optic disc and visual field progression in ocular hypertensive subjects: detection rates, specificity, and agreement. Invest Ophthalmol Vis Sci 2006;47 (7) 2904- 2910
PubMedArticle
15.
Viswanathan  ACCrabb  DP McNaught  AI  et al.  Interobserver agreement on visual field progression in glaucoma: a comparison of methods. Br J Ophthalmol 2003;87 (6) 726- 730
PubMedArticle
16.
Chauhan  BCGarway-Heath  DFGoñi  FJ  et al.  Practical recommendations for measuring rates of visual field change in glaucoma. Br J Ophthalmol 2008;92 (4) 569- 573
PubMedArticle
17.
Leske  MCHeijl  AHussein  MBengtsson  BHyman  LKomaroff  EEarly Manifest Glaucoma Trial Group, Factors for glaucoma progression and the effect of treatment: the Early Manifest Glaucoma Trial. Arch Ophthalmol 2003;121 (1) 48- 56
PubMedArticle
18.
Mikelberg  FSDrance  SM The mode of progression of visual field defects in glaucoma. Am J Ophthalmol 1984;98 (4) 443- 445
PubMedArticle
19.
Boden  CBlumenthal  EZPascual  J  et al.  Patterns of glaucomatous visual field progression identified by three progression criteria. Am J Ophthalmol 2004;138 (6) 1029- 1036
PubMedArticle
20.
Boden  CSample  PABoehm  AGVasile  CAkinepalli  RWeinreb  RN The structure-function relationship in eyes with glaucomatous visual field loss that crosses the horizontal meridian. Arch Ophthalmol 2002;120 (7) 907- 912
PubMedArticle
21.
Gaasterland  DTanishima  TKuwabara  T Axoplasmic flow during chronic experimental glaucoma, 1: light and electron microscopic studies of the monkey optic nervehead during development of glaucomatous cupping. Invest Ophthalmol Vis Sci 1978;17 (9) 838- 846
PubMed
22.
Minckler  DSBunt  AHJohanson  GW Orthograde and retrograde axoplasmic transport during acute ocular hypertension in the monkey. Invest Ophthalmol Vis Sci 1977;16 (5) 426- 441
PubMed
23.
Quigley  HAAddicks  EMGreen  WRMaumenee  AE Optic nerve damage in human glaucoma, II: the site of injury and susceptibility to damage. Arch Ophthalmol 1981;99 (4) 635- 649
PubMedArticle
24.
Burgoyne  CFDowns  JC Premise and prediction: how optic nerve head biomechanics underlies the susceptibility and clinical behavior of the aged optic nerve head. J Glaucoma 2008;17 (4) 318- 328
PubMedArticle
25.
Jonas  JBFernández  MCStürmer  J Pattern of glaucomatous neuroretinal rim loss. Ophthalmology 1993;100 (1) 63- 68
PubMedArticle
26.
Jonas  JBMardin  CYSchlötzer-Schrehardt  UNaumann  GO Morphometry of the human lamina cribrosa surface. Invest Ophthalmol Vis Sci 1991;32 (2) 401- 405
PubMed
27.
Demirel  SFortune  BFan  J  et al.  Predicting progressive glaucomatous optic neuropathy using baseline standard automated perimetry data. Invest Ophthalmol Vis Sci 2009;50 (2) 674- 680
PubMedArticle
28.
Pascual  JPSchiefer  UPaetzold  J  et al.  Spatial characteristics of visual field progression determined by Monte Carlo simulation: diagnostic innovations in glaucoma study. Invest Ophthalmol Vis Sci 2007;48 (4) 1642- 1650
PubMedArticle
29.
Nouri-Mahdavi  KHoffman  DGaasterland  DCaprioli  J Prediction of visual field progression in glaucoma. Invest Ophthalmol Vis Sci 2004;45 (12) 4346- 4351
PubMedArticle
30.
Vesti  EJohnson  CAChauhan  BC Comparison of different methods for detecting glaucomatous visual field progression. Invest Ophthalmol Vis Sci 2003;44 (9) 3873- 3879
PubMedArticle
Clinical Sciences
September 14, 2009

Glaucoma With Early Visual Field Loss Affecting Both Hemifields and the Risk of Disease Progression

Author Affiliations

Author Affiliations: Einhorn Clinical Research Center, Department of Ophthalmology, New York Eye and Ear Infirmary (Drs De Moraes, Prata, Tello, Ritch, and Liebmann); New York Medical College, Department of Ophthalmology (Drs Tello and Ritch); New York University School of Medicine, Department of Ophthalmology (Dr Liebmann); and Manhattan Eye, Ear, and Throat Hospital, Department of Ophthalmology (Dr Liebmann), New York.

Arch Ophthalmol. 2009;127(9):1129-1134. doi:10.1001/archophthalmol.2009.165
Abstract

Objective  To evaluate whether damage to both hemifields in glaucomatous eyes predicts more rapid disease progression than does single-hemifield involvement.

Methods  We reviewed the medical records of 43 660 consecutive patients. Eyes with glaucomatous optic neuropathy, 10 or more Swedish Interactive Threshold Algorithm standard 24-2 visual fields in at least 5 years, and mean deviation (MD) smaller than −6.0 dB were included. Pointwise linear regression was used to determine progression. Cox proportional hazards analysis was used to calculate risk of progression based on different baseline covariates.

Results  We enrolled 205 eyes (205 patients; mean [SD] age, 64.2 [11.0] years; follow-up, 6.5 [1.8] years; number of visual fields, 12.3 [2.9]). Patients were divided into 3 groups: initial superior defect (group A; n = 79; MD, −3.4 [1.9] dB), initial inferior defect (group B; n = 61; MD, −3.4 [1.8] dB), and both hemifields affected (group C; n = 65; MD, −4.2 [1.5] dB). Group C progressed faster than did groups A and B (P < .02). Multivariate analysis showed significant effect of higher baseline intraocular pressure, thinner central corneal thickness, and initial damage to both hemifields.

Conclusions  Initial damage to both hemifields increases the risk of glaucoma progression. More aggressive therapy should be considered for these eyes.

Identification of ocular or systemic risk factors associated with a faster rate of visual field (VF) loss remains an important goal of glaucoma research. A combination of variables, such as the extent of baseline optic nerve and VF damage, life expectancy, and the presence of additional risk factors, has been used to estimate the risk of loss of visual function and to determine future management.1 Although a variety of structural and functional tests are used to diagnose and follow glaucoma, standard achromatic perimetry remains the most widely used method for assessing visual function.25

Several studies610 have investigated whether baseline VF characteristics are associated with increased risk of future disease progression and have typically focused on VF global indexes (ie, mean deviation [MD] and pattern deviation). These are well-established indexes that summarize measures of the entire VF but provide scarce spatial information.

Although patterns of VF injury vary in patients, glaucomatous field loss often begins with localized injury that respects the horizontal meridian and subsequently spreads in an arcuate pattern consistent with the orientation of the retinal nerve fiber bundles. In more advanced disease, these scotomata, particularly when present in both hemifields, may threaten fixation.11 We hypothesize that eyes with VF defects in both hemifields early in the disease course are more likely to experience progressive functional injury. To investigate this hypothesis, we evaluated eyes with similar baseline global VF damage to determine whether VF loss affecting both hemifields could be a harbinger of a worse prognosis than those with a similar degree of total damage limited to one hemifield.

METHODS

This retrospective study was part of a larger cohort initiated to investigate whether the findings of the major prospective multicenter clinical trials are applicable to the heterogeneous populations that confront physicians in daily practice. The different arms of this study originated from the medical records of 43 660 consecutive patients (132 512 VF tests) evaluated in the glaucoma referral practice of some of us (C.T., R.R., and J.M.L.). The study was approved by the New York Eye and Ear Infirmary institutional review board and followed the tenets of the Declaration of Helsinki.

The medical records of all patients examined between January 1, 1999, and June 30, 2008, were reviewed. Only patients with 10 or more Swedish Interactive Threshold Algorithm standard 24-2 fields (SITA-SAP, HFA II; Carl Zeiss Meditec Inc, Dublin, California) in either eye were included. A glaucomatous VF was defined as a glaucoma hemifield test result outside normal limits on at least 2 consecutive baseline VF tests and the presence of at least 3 contiguous test points in the same hemifield on the pattern standard deviation plot at P <.010 with at least one at P <.005, excluding points on the edge of the field and those directly above and below the blind spot.11 If the same criteria were observed across the horizontal meridian, both hemifields were considered to be affected. The 2 baseline tests required reliability indexes better than 25% to be included. Other inclusion criteria were baseline MD smaller than −6.0 dB, minimum follow-up of 5 years, and the absence of ocular disorders other than glaucoma likely to affect the VF. If both eyes met the inclusion criteria, the one with the smallest MD was chosen.

Pointwise linear regression (PLR) analysis was performed using Progressor software (version 3.3; Medisoft Inc, London, England), providing slopes of progression globally and locally for each point and its level of significance (P values).12 A gaussian filter (based on a 3 × 3 test point grid) was also applied to reduce measurement variability without recourse to additional testing or exclusion of “noisy” tests; thus, all available VF tests except the 2 baseline tests were included in the analysis irrespective of reliability criteria.13 Progression was defined as the presence of a test point with a slope of sensitivity across time greater than 1 dB loss per year, with P < .01. For edge points, a stricter slope criterion of a greater than 2 dB loss per year (also with P < .01) was used.14,15 All the patients were familiar with automated perimetry and had undergone a minimum of 2 VF tests before study enrollment.

Demographic and ocular characteristics of enrolled patients were recorded at baseline. Central corneal thickness (CCT) (DGH-550; DGH Technology Inc, Exton, Pennsylvania) was calculated using an average of 5 measurements. The MD value and the number of abnormal points (P <.01) of the pattern deviation plot from the baseline VF test were used in the analysis to assess baseline functional damage.

Comparisons of continuous and categorical variables between groups were performed using analysis of variance with Bonferroni post hoc analysis and the χ2 test, respectively. Because eyes with both hemifields affected were more likely to have a larger number of abnormal points at baseline, a general linear model was used to adjust the rate of progression to the MD values and the number of abnormal points. Other variables analyzed as potential risk factors were age, baseline intraocular pressure (IOP), CCT, baseline MD, and the presence of exfoliation syndrome, which have been previously reported to be risk factors for disease progression.610

Hazard ratios (HRs) for the association between different variables and VF progression were obtained using Cox proportional hazards models. We used HRs from univariate models, which do not adjust for other covariates, and adjusted HRs from multivariate models. Only variables with P < .10 in the univariate analysis were entered into the multivariate analysis.

Because we compared the rates of VF progression between groups using single-hemifield damage (superior or inferior) vs those with damage to both hemifields, a sample size calculation determined that a minimum of 177 eyes (59 eyes per group) was required to detect a 20% difference in rates of progression among 3 groups, with a power of 80% and type I error of 5%. Similarly, selecting a cohort of patients with greater than 10 VF tests, performing a mean of 2 examinations per year, would provide 80% power to detect significant VF change in this population.16 Statistical analysis was performed using a software package (SPSS version 17.0; SPSS Inc, Chicago, Illinois).

RESULTS

Two hundred five eyes (205 patients) met the entry criteria. The mean (SD) patient age was 64.2 (11.0) years; 58.8% were women and 86.0% were of European descent. Mean follow-up was 6.5 (1.8) years, and the mean number of VF tests was 12.3 (2.9).

Patients were divided into 3 groups: initial superior defect (group A, n = 79), initial inferior defect (group B, n = 61), and damage to both hemifields (group C, n = 65) (Figure). Patients received a variety of glaucoma treatments during the study. Table 1 summarizes the baseline characteristics of each group. The MD value and the number of abnormal points in group C were greater than those in the other groups (P = .02 for both). There were more eyes with exfoliation glaucoma in the group with superior hemifield damage (P < .01).

Group C progressed faster (mean, 0.90 [0.9] dB per year) than did group A (0.52 [0.8] dB per year) and group B (0.33 [0.5] dB per year). Because the MD and the number of points with P < .01 in the 3 groups differed, we adjusted the mean slope of the groups to these covariates (general linear model), and the differences remained significant (P < .025). Forty-three eyes (54.4%) in group A reached a progression end point compared with 17 (27.9%) in group B and 45 (69.2%) in group C (P < .01). Group C had almost twice as many eyes with a fast rate of progression (>1.5 dB per year) as the other 2 groups combined (Table 2).

In the univariate model, damage to both hemifields was associated with an increased risk of VF progression (HR, 1.58; 95% confidence interval, 1.07-2.32; P = .02). Elevated baseline IOP and thinner CCT were also associated with a greater chance of reaching a progression end point (P < .01) (Table 3). Older age was associated with disease progression, although this was not significant (P = .10). After adjusting for these covariates, baseline damage to both hemifields remained a significant predictor of progression (HR, 1.62; 95% confidence interval, 1.09-2.39; P = .01) (Table 4). The presence of this pattern of damage increased the risk of future field loss by 62%, whereas each 1–mm Hg higher baseline IOP increased the risk by 7% and each 40-μm decrease in CCT increased the risk by 27%.

COMMENT

Glaucoma is a multifactorial disease that results in different patterns and rates of progression for different individuals. An improved understanding of risk factors at all stages of disease is critical to estimating the risk of future disease progression for a specific affected individual. The results of the present study confirm that initial damage to both visual hemifields connotes a worse prognosis than does more localized damage limited to one hemifield, even when there is early VF loss (MD smaller than −6.0 dB). This involvement of both hemifields is an independent predictor of more rapid future VF injury in eyes with early functional damage and greatly increases the risk of progression.

In agreement with other studies, we found a significant role for higher baseline IOP610 and thinner CCT6,10 as risk factors for progression. The continued importance of these risk factors in treated patients with glaucoma is particularly important for physicians who must make clinical decisions for patients who may not precisely resemble the individuals who were enrolled in masked, prospective, longitudinal clinical trials. Despite an initial mean baseline IOP of 17 mm Hg in eyes with early VF loss, the risk of progression increased 7% for each additional 1 mm Hg. A thinner CCT was also a risk factor for progression, increasing the risk by 27% for each 40-μm decrease. These results are consistent with those of the major prospective glaucoma clinical trials. The Early Manifest Glaucoma Trial (EMGT)6 found a 13% increased risk per each additional 1 mm Hg of IOP and a 25% increased risk per 40-μm decrease in CCT. The Diagnostic Innovations in Glaucoma Study10 also found a 7% increased risk of progression for each additional 1 mm Hg of IOP and a 62% increase for each 40-μm decrease in CCT in a group of patients with early glaucoma damage. The present study reemphasizes the role of IOP even in a treated population with statistically normal pressures.

Age was not a significant risk factor in the final multivariate model, suggesting that other factors, such as disease stage, treatment, and other covariates, may play stronger roles in predicting progression in this treated population. In its first report, the EMGT17 also found a positive association between age and progression that was not confirmed in a multivariate analysis. Unlike the EMGT,6,17 exfoliation syndrome was not a significant risk factor in the present study, which may be due to the lower IOPs in the cohort.

The nature of glaucoma pathogenesis and functional and structural associations in glaucoma may help explain the increased risk associated with VF loss in both hemifields. Glaucomatous functional damage usually respects the horizontal meridian and the anatomy of the retinal nerve fiber layer.11 In 1984, Mikelberg and Drance18 reviewed the pattern of VF progression using static and kinetic perimetry and found that 70% of eyes had initial damage limited to a single hemifield; at the completion of follow-up, 57% still had only single-hemifield involvement, whereas 13% had involvement of both hemifields. The most common pattern of field loss was deepening of an existing scotoma, which was later confirmed using static perimetry.19 Boden et al20 found that early glaucomatous field loss rarely crosses the horizontal midline. In a cross-sectional analysis that included patients with mild to severe glaucoma, they found a prevalence of 30% of VF defects across the horizontal meridian, 90% of which could be explained by changes at the optic nerve head (ONH) as assessed using stereophotography. The definition used in their study implied that the superior and inferior affected sectors should be adjacent to the horizontal midline (Figure, C). The present study did not require VF defects to be adjacent to the midline and contiguous, a clinical characteristic that may be found more commonly in practice (Figure, D).18 Although it has been suggested that worse functional damage (MD) is associated with an increased risk of progression,69 the present findings suggest that it is also possible to determine different levels of risk based on the extent and location(s) of the defect, even when the VF damage is mild. Despite initially having similar global field damage, damage to both hemifields suggests that more widespread structural and functional abnormality is present, which increases the susceptibility to progression.

Experimental models have been developed to try to clarify the pathogenesis of glaucomatous damage and progression. There is strong evidence that damage to the retinal ganglion cell axons, which ultimately converge to the ONH, is the key cause of vision loss in glaucoma.2123 Burgoyne and Downs24 reviewed this issue and proposed that alterations in ONH biomechanics underlie the clinical behavior and likely increased susceptibility of the ONH. That is, a more damaged optic nerve would be more susceptible to future damage. Quigley et al23 suggested that the structure of the lamina cribrosa is an important determinant of the degree of susceptibility to damage by elevated IOP. Jonas et al25 showed a correlation between the progression of VF defects and the morphologic features of the lamina cribrosa and suggested that a larger single pore area increased glaucoma susceptibility in the inferior and superior disc regions.26

We hypothesized that the presence of damage to both hemifields may reflect greater overall optic nerve susceptibility to glaucoma (in both the superior and inferior poles rather than localized to one location), which resulted in the accelerated rate of progression found in this study. Because we did not address this issue directly, further studies to assess structural characteristics of the ONH and lamina cribrosa in eyes with faster progression rates are necessary to confirm this hypothesis.

To support this hypothesis, Demirel et al27 recently assessed the role of baseline perimetry data in predicting future progression. They found that depressed VF locations close to the midline, mostly in the superior and inferior nasal sectors, are most predictive of future progression. If this is the case, eyes with abnormal points in both hemifields would have a summed effect of susceptibilities from different VF sectors. Similarly, Pascual et al28 showed a spatial relationship between initially defective locations found at baseline and those found on subsequent testing. The authors described superior defects related to progression in the superior field, resembling the nerve fiber bundle patterns, whereas the inferior defects did not show clearly specific patterns of progression. These studies may help explain why fewer eyes with baseline damage limited to the inferior hemifield reached a progression end point in the present study.

We chose to use PLR rather than event analysis in this study for several reasons. First, the commercially available software provides automated values that can be easily determined and reproduced at different medical centers. Second, in contrast to other methods that have been proposed for major clinical trials, PLR can determine the rate of VF loss globally, by sector, or at individual points with decreased subjectivity.29 Finally, the larger number of VFs required for PLR enhances specificity.30

This study has several limitations. Enrolling eyes with mild functional damage limits the conclusions to this specific population. However, eyes with moderate or severe VF damage often have damage to both hemifields, making identification of a comparable group with damage to one hemifield more difficult. The use of PLR may have provided a more sensitive method of progression than is typically used in clinical practice. As in most clinical studies, we analyzed the predictive value of baseline characteristics (level of damage, CCT, age, IOP, and exfoliation glaucoma).610 However, reassessment and reevaluation of risk factors during treatment (intercurrent risk factors) might provide more important information than the initial baseline risk factor assessment. In clinical practice, physicians constantly adjust risk profiles as information becomes available (eg, advancing age and a major cardiovascular event), and the use of a continuous and dynamic measure of progression (expressed as rates) may be particularly helpful in these circumstances. Last, the retrospective nature of this study design and the tertiary care setting create certain inherent biases in patient selection. The long-term follow-up and the similar characteristics among the study groups (age, IOP, CCT, and treatment) serve to mitigate potential bias and suggest that such bias likely did not significantly affect the results. Despite the retrospective nature of this study, the consonance of these results with the major prospective clinical trials serves to confirm the validity of the data set.

In a treated glaucoma population, assessing other variables that could be associated with faster rates of disease progression may help direct future management and aggressiveness of treatment. In these patients with early and similar baseline VF damage, eyes with defects involving both hemifields progressed more quickly and were more likely to reach a predefined end point than were those with a single affected hemifield. For the practicing physician, these findings suggest that a lower target IOP may be warranted for patients with initial, reproducible damage extending to both hemifields.

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Article Information

Correspondence: Jeffrey M. Liebmann, MD, 310 E 14th St, New York, NY 10003 (jml18@earthlink.net).

Submitted for Publication: December 24, 2008; final revision received January 26, 2009; accepted February 20, 2009.

Previous Presentation: This study was presented in part at the annual meeting of the American Glaucoma Society; March 6, 2009; San Diego, California.

Financial Disclosure: None reported.

Funding/Support: This study was supported by the Catherine and Ephraim Gildor Research Fund of the New York Glaucoma Research Institute.

References
1.
Medeiros  FAWeinreb  RN Predictive models to estimate the risk of glaucoma development and progression. Prog Brain Res 2008;17315- 24
PubMed
2.
Parrish  RK  IIGedde  SJScott  IU  et al.  Visual function and quality of life among patients with glaucoma. Arch Ophthalmol 1997;115 (11) 1447- 1455
PubMedArticle
3.
Jampel  HDFriedman  DSQuigley  HMiller  R Correlation of the binocular visual field with patient assessment of vision. Invest Ophthalmol Vis Sci 2002;43 (4) 1059- 1067
PubMed
4.
Bengtsson  BHeijl  A A visual field index for calculation of glaucoma rate of progression. Am J Ophthalmol 2008;145 (2) 343- 353
PubMedArticle
5.
Heijl  ABengtsson  BChauhan  BC  et al.  A comparison of visual field progression criteria of 3 major glaucoma trials in Early Manifest Glaucoma Trial patients. Ophthalmology 2008;115 (9) 1557- 1565
PubMedArticle
6.
Leske  MCHeijl  AHyman  LBengtsson  BDong  LYang  ZEMGT Group, Predictors of long-term progression in the Early Manifest Glaucoma Trial. Ophthalmology 2007;114 (11) 1965- 1972
PubMedArticle
7.
Miglior  STorri  VZeyen  TPfeiffer  NVaz  JCAdamsons  IEGPS Group, Intercurrent factors associated with the development of open-angle glaucoma in the European Glaucoma Prevention Study. Am J Ophthalmol 2007;144 (2) 266- 275
PubMedArticle
8.
Musch  DCGillespie  BWLichter  PRNiziol  LMJanz  NKCIGTS Study Investigators, Visual field progression in the Collaborative Initial Glaucoma Treatment Study: the impact of treatment and other baseline factors. Ophthalmology 2009;116 (2) 200- 207
PubMedArticle
9.
AGIS Investigators, The Advanced Glaucoma Intervention Study (AGIS), 12: baseline risk factors for sustained loss of visual field and visual acuity in patients with advanced glaucoma. Am J Ophthalmol 2002;134 (4) 499- 512
PubMedArticle
10.
Medeiros  FASample  PAZangwill  LMBowd  CAihara  MWeinreb  RN Corneal thickness as a risk factor for visual field loss in patients with preperimetric glaucomatous optic neuropathy. Am J Ophthalmol 2003;136 (5) 805- 813
PubMedArticle
11.
Anderson  DRPatella  VM Automated Static Perimetry. 2nd ed. St Louis, MO Mosby Inc1999;
12.
Viswanathan  ACFitzke  FWHitchings  RA Early detection of visual field progression in glaucoma: a comparison of PROGRESSOR and STATPAC 2. Br J Ophthalmol 1997;81 (12) 1037- 1042
PubMedArticle
13.
Crabb  DPFitzke  FW McNaught  AIEdgar  DFHitchings  RA Improving the prediction of visual field progression in glaucoma using spatial processing. Ophthalmology 1997;104 (3) 517- 524
PubMedArticle
14.
Strouthidis  NGScott  APeter  NMGarway-Heath  DF Optic disc and visual field progression in ocular hypertensive subjects: detection rates, specificity, and agreement. Invest Ophthalmol Vis Sci 2006;47 (7) 2904- 2910
PubMedArticle
15.
Viswanathan  ACCrabb  DP McNaught  AI  et al.  Interobserver agreement on visual field progression in glaucoma: a comparison of methods. Br J Ophthalmol 2003;87 (6) 726- 730
PubMedArticle
16.
Chauhan  BCGarway-Heath  DFGoñi  FJ  et al.  Practical recommendations for measuring rates of visual field change in glaucoma. Br J Ophthalmol 2008;92 (4) 569- 573
PubMedArticle
17.
Leske  MCHeijl  AHussein  MBengtsson  BHyman  LKomaroff  EEarly Manifest Glaucoma Trial Group, Factors for glaucoma progression and the effect of treatment: the Early Manifest Glaucoma Trial. Arch Ophthalmol 2003;121 (1) 48- 56
PubMedArticle
18.
Mikelberg  FSDrance  SM The mode of progression of visual field defects in glaucoma. Am J Ophthalmol 1984;98 (4) 443- 445
PubMedArticle
19.
Boden  CBlumenthal  EZPascual  J  et al.  Patterns of glaucomatous visual field progression identified by three progression criteria. Am J Ophthalmol 2004;138 (6) 1029- 1036
PubMedArticle
20.
Boden  CSample  PABoehm  AGVasile  CAkinepalli  RWeinreb  RN The structure-function relationship in eyes with glaucomatous visual field loss that crosses the horizontal meridian. Arch Ophthalmol 2002;120 (7) 907- 912
PubMedArticle
21.
Gaasterland  DTanishima  TKuwabara  T Axoplasmic flow during chronic experimental glaucoma, 1: light and electron microscopic studies of the monkey optic nervehead during development of glaucomatous cupping. Invest Ophthalmol Vis Sci 1978;17 (9) 838- 846
PubMed
22.
Minckler  DSBunt  AHJohanson  GW Orthograde and retrograde axoplasmic transport during acute ocular hypertension in the monkey. Invest Ophthalmol Vis Sci 1977;16 (5) 426- 441
PubMed
23.
Quigley  HAAddicks  EMGreen  WRMaumenee  AE Optic nerve damage in human glaucoma, II: the site of injury and susceptibility to damage. Arch Ophthalmol 1981;99 (4) 635- 649
PubMedArticle
24.
Burgoyne  CFDowns  JC Premise and prediction: how optic nerve head biomechanics underlies the susceptibility and clinical behavior of the aged optic nerve head. J Glaucoma 2008;17 (4) 318- 328
PubMedArticle
25.
Jonas  JBFernández  MCStürmer  J Pattern of glaucomatous neuroretinal rim loss. Ophthalmology 1993;100 (1) 63- 68
PubMedArticle
26.
Jonas  JBMardin  CYSchlötzer-Schrehardt  UNaumann  GO Morphometry of the human lamina cribrosa surface. Invest Ophthalmol Vis Sci 1991;32 (2) 401- 405
PubMed
27.
Demirel  SFortune  BFan  J  et al.  Predicting progressive glaucomatous optic neuropathy using baseline standard automated perimetry data. Invest Ophthalmol Vis Sci 2009;50 (2) 674- 680
PubMedArticle
28.
Pascual  JPSchiefer  UPaetzold  J  et al.  Spatial characteristics of visual field progression determined by Monte Carlo simulation: diagnostic innovations in glaucoma study. Invest Ophthalmol Vis Sci 2007;48 (4) 1642- 1650
PubMedArticle
29.
Nouri-Mahdavi  KHoffman  DGaasterland  DCaprioli  J Prediction of visual field progression in glaucoma. Invest Ophthalmol Vis Sci 2004;45 (12) 4346- 4351
PubMedArticle
30.
Vesti  EJohnson  CAChauhan  BC Comparison of different methods for detecting glaucomatous visual field progression. Invest Ophthalmol Vis Sci 2003;44 (9) 3873- 3879
PubMedArticle
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