Predictive factors for glaucomatous visual field progression in the Advanced Glaucoma Intervention Study☆

Article Outline

• Abstract
• Materials and methods
  • Statistical methods
• Results
• Discussion
• Acknowledgements
• References
• Copyright

Abstract 

Purpose

To investigate the risk factors associated with visual field (VF) progression in the Advanced Glaucoma Intervention Study (AGIS) with pointwise linear regression (PLR) analysis of serial VFs.

Design

Prospective, multicenter, randomized clinical trial.

Participants

Five hundred nine eyes of 401 patients from the AGIS with a baseline VF score of ≤16, ≥7 VF examinations, and ≥3 years of follow-up were selected.

Main outcome measure

Visual field progression.

Methods

This is a cohort study of patients enrolled in a prospective randomized clinical trial (AGIS). Worsening of a test location on PLR analysis was defined as a change of threshold sensitivity of ≥1.00 decibels a year, with P≤0.01. Visual field progression was defined as worsening of at least 2 test locations within a Glaucoma Hemifield Test cluster with PLR analysis. Multivariate logistic regression was used to determine risk factors associated with VF worsening. Intraocular pressure (IOP) fluctuation was defined as standard deviation of the IOP at all visits after the initial surgery.

Results

The mean (± standard deviation) follow-up time and baseline AGIS score were 7.4 (±1.7) years and 7.7 (±4.4), respectively. Visual field progression was detected with PLR analysis in 151 eyes (30%). Older age at the initial intervention (P = 0.0012; odds ratio [OR], 1.30; 95% confidence interval [CI], 1.11–1.50), larger IOP fluctuation (P = 0.0013; OR, 1.31; 95% CI, 1.12–1.54), increasing number of glaucoma interventions (P = 0.01; OR, 1.74; 95% CI, 1.14–2.64), and longer follow-up (P = 0.02; OR, 1.19; 95% CI, 1.03–1.38) were associated with increased odds of VF progression. When regression analyses were repeated in eyes with and without a history of cataract extraction, IOP fluctuation was the only variable to be consistently associated with VF progression.

Conclusion

Both increasing age and greater IOP fluctuation increase the odds of VF progression by 30% (for each 5-year increment in age and 1-mmHg increase in IOP fluctuation). The higher risk conferred by IOP fluctuation was consistently observed in eyes with and without a history of cataract extraction.

Over the last 2 decades a number of studies have addressed the issue of risk factors associated with or predictive for glaucoma progression.1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 A better understanding of clinical risk factors for worsening of glaucoma may help us develop new strategies to improve glaucoma care. A major obstacle has been the lack of a uniformly accepted and efficient approach to detect glaucoma progression. Evaluation of visual field (VF) series remains the clinical method most frequently used to assess the course of glaucoma and the efficacy of its treatment.

The Advanced Glaucoma Intervention Study (AGIS) used a single method for longitudinal evaluation of VFs. Due to the lack of a gold standard and only fair concordance among various analytic methods, this could cause important associations to be missed or spurious ones to be detected. We compared the results of an independent approach, pointwise linear regression (PLR) analysis, with the AGIS method in a subgroup of patients from that study.22 The 2 methods were concordant in two thirds of study eyes.

The primary objective of this report is to identify the risk factors associated with progression of VF damage in the AGIS with PLR analysis to evaluate sequential VFs for clinically and statistically significant change.

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Materials and methods 

The AGIS design and methods are described in detail elsewhere and are summarized here.2, 23 Thirty-five- to 80-year-old phakic patients with open-angle glaucoma no longer controlled by maximally tolerated medical treatment were recruited. Eligible eyes had a best-corrected visual acuity (VA) score of at least 56 letters (Early Treatment Diabetic Retinopathy Study) and met specified criteria for combinations of consistently elevated intraocular pressure (IOP), glaucomatous VF defect, and optic disc rim deterioration.2 Between 1988 and 1992, investigators at 12 participating AGIS clinical centers enrolled 789 eyes of 591 patients. Eyes were randomly assigned to 1 of 2 surgical intervention sequences: argon laser trabeculoplasty (ALT)–trabeculectomy–trabeculectomy (ATT) or trabeculectomy–ALT–trabeculectomy (TAT). Data in this report are based on a database closure of March 31, 2001. The institutional review boards at each of the participating centers approved the AGIS protocol, and all patients gave informed consent.

Visual field tests were conducted with a Humphrey Visual Field Analyzer I (Carl Zeiss Ophthalmic Systems, Inc., Dublin, CA) set for the central 24-2 threshold test, size III white stimulus, and full threshold strategy, with the foveal threshold test turned on. The 24-2 program of the Humphrey Visual Field Analyzer records data from 55 locations in the VF, all of which, except the locations above and below the blind spot and the foveal threshold, are used for calculating the AGIS VF score.3 Scoring is based on the number, pattern, and depth of depression of threshold sensitivities as found in the Humphrey total deviation plot. Points are awarded for the presence of a nasal defect (a cluster of ≥3 depressed locations in the nasal field), nasal step (≥1 depressed locations in the nasal field, in the absence of depression in any of the 3 locations on the opposite side of the horizontal midline), and hemifield defect (cluster of ≥3 depressed sites in a hemifield). The translation of an array of VF thresholds into a single number simplifies the comparison of test results and the determination of progression or stability. Visual field defect scores ranged from 0 (no defect) to 20 (advanced glaucoma). Visual field measurements were made at baseline, 3 months after initial intervention, and at each 6-month follow-up examination. Baseline or reference measurements were performed after the eligibility measurements but before the first surgical intervention.

From the original pool of the recruited patients (789 eyes of 591 patients), 509 eyes of 401 patients meeting the following criteria were selected for this study:

Statistical methods 

SPSS statistical software24 was used to perform PLR analysis. Our methodology is described in detail elsewhere.22 We used the two-omitting regression algorithm recently described by Gardiner and Crabb for definition of change versus stability at each point.4 In summary, in this technique a test location is considered to be progressing or improving during the follow-up period only if the regression slope is statistically and clinically significant (as defined below) in both of the following regression analyses: (1) after omitting the last threshold in a series and (2) after deleting the threshold before last for the same series. This approach has been shown, in simulation experiments, to be more specific than using all the data points for a single regression analysis, and it maintains a sensitivity comparable to other stringent algorithms used for the same purpose, such as two of two5 or three of four.4, 6, 7 Regression slopes were considered statistically and clinically significant if ≥1.00 decibels (dB)/year or ≤−1.0 dB/year in the presence of P≤0.01.

For evaluation of VF series, we used the most rigorous and clinically relevant set of criteria explored in the aforementioned investigation, the 2-point Glaucoma Hemifield Test change criterion. According to this, a VF series is considered to be changing if 2 test locations belonging to the same Glaucoma Hemifield Test cluster demonstrate change in the same direction. This set of criteria was found to be the most conservative among different PLR approaches. It yielded the smallest number of progressing VF series, minimized the number of improving VF series, and demonstrated the highest agreement with AGIS criteria.

Visual field progression according to AGIS criteria was defined as the first occurrence in an eye, at 3 consecutive 6-month visits, of worsening in the VF defect score of ≥4 from the baseline value. Changes in the AGIS VF defect score were measured from preintervention reference values.

Visual field outcomes from PLR were classified as progressing or nonprogressing. Improving and stable eyes were categorized as nonprogressing. Associations between VF progression and various preoperative and postoperative potential risk factors were evaluated with multivariate logistic regression.25

It has been shown that both eyes of the same patient are at least partially correlated with respect to progression of the VF.8 We used a generalized linear mixed model to account for the intereye correlation. The generalized linear mixed model is a commonly used random-effects model that permits the data to exhibit correlation and nonconstant variability and allows the response to come from several distributions such as binomial, Poisson, and γ.

Preoperative and postoperative factors that were associated with VF progression in univariate analyses (χ² test, unpaired t test, or Wilcoxon rank sum test, depending on the type of data) at a P value of ≤0.20 were included in the final model. In addition, we included all the variables that might potentially predict or confound detection of VF progression from a clinical point of view (Table 1). Mean IOP was calculated by averaging all the available IOPs starting at 3 and 6 months after the initial intervention and every 6 months thereafter. Standard deviation of the IOP at all visits after the initial surgery was used as a surrogate for IOP fluctuation. The cutoff point for classification by logistic regression was set at 0.50. Any variable with a P value of ≤0.05 was considered statistically significant.

Table 1. Final Independent Variables Explored in Logistic Regression Models

AGIS = Advanced Glaucoma Intervention Study; IOP = intraocular pressure; SD = standard deviation.

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Results 

A total of 151 eyes (29.9%) progressed according to the PLR criteria, whereas 138 eyes (27.1%) showed progression based on AGIS criteria (κ = 0.30, percentage agreement = 64%). The characteristics of the study sample are presented in Table 2 based on occurrence of progression according to PLR criteria. Four eyes were considered indeterminate based on our PLR criteria and were excluded from further analysis. Table 3 describes the results of the multivariate logistic regression. Four variables were associated with a higher probability of VF progression in decreasing magnitude: older age at the time of first intervention, greater IOP fluctuation, increasing number of glaucoma interventions, and longer follow-up. Additionally, 2 other variables, male gender and lower baseline IOP, demonstrated a possible association with VF progression (0.05<P<0.10). Excluding the variables related to glaucoma severity at baseline (AGIS VF score and cup/disc ratio at baseline) from the logistic regression analysis to determine risk factors resulted in the same 4 variables mentioned above being associated with increased odds of field progression. In addition, male gender (P = 0.0476, odds ratio [OR] = 1.596) was also associated with a statistically significant increase in the odds of VF progression.

Table 2. Characteristics of the Study Sample in Stable and Progressing Eyes with the 2-Point Glaucoma Hemifield Test Change Used as the Criterion for Progression of Visual Field Series

AGIS = Advanced Glaucoma Intervention Study; ATT = argon laser trabeculoplasty–trabeculectomy–trabeculectomy; IOP = intraocular pressure; SD = standard deviation; TAT = trabeculectomy–argon laser trabeculoplasty–trabeculectomy.

The data do not include 4 eyes that had indeterminate results on pointwise linear regression analysis.

Table 3. Results of Logistic Regression Using All the Variables Mentioned in Table 1

AGIS = Advanced Glaucoma Intervention Study; ATT = argon laser trabeculoplasty–trabeculectomy–trabeculectomy; CI = confidence interval; D = diopters; IOP = intraocular pressure.

We repeated the same analyses on eyes belonging to the ATT and TAT intervention sequences separately (Table 4). For the ATT intervention sequence, higher number of glaucoma interventions, older age at first intervention, greater IOP fluctuation, longer follow-up, and male gender were significantly associated with VF progression, in that order. For the TAT sequence, 3 covariates showed a possible association with VF progression (0.05<P<0.10): older age at first intervention (P = 0.08), presence of diabetes (P = 0.092), and greater IOP fluctuation (P = 0.097).

Table 4. Results of Logistic Regression Divided by Intervention Sequence

AGIS = Advanced Glaucoma Intervention Study; ATT = argon laser trabeculoplasty–trabeculectomy–trabeculectomy; CI = confidence interval; D = diopters; IOP = intraocular pressure; TAT = trabeculectomy–argon laser trabeculoplasty–trabeculectomy.

Development and removal of cataracts are important confounding variables to consider. To address this issue, we repeated the logistic regression analysis in the 2 groups of eyes with or without cataract surgery over the course of the study (Table 5). One hundred ninety-seven eyes (38.7%) had cataract surgery after the first intervention. In the group of eyes that did not undergo cataract surgery (312 eyes), older age, greater IOP fluctuation, lower baseline IOP, and longer follow-up were associated with VF worsening. In the group of eyes that had had cataract surgery, male gender and greater IOP fluctuation were associated with VF progression.

Table 5. Results of Logistic Regression Based on Performance of Cataract Surgery

AGIS = Advanced Glaucoma Intervention Study; ATT = argon laser trabeculoplasty–trabeculectomy–trabeculectomy; CI = confidence interval; D = diopters; IOP = intraocular pressure.

As a comparison, we performed the same analyses using the AGIS criteria for definition of VF outcomes. The following predictive factors were found on multivariate logistic regression: lower baseline AGIS score (P<0.0001), greater IOP fluctuation (P<0.0001), vertical cup/disc ratio > 0.60 (P = 0.001), greater number of glaucoma surgeries (P = 0.008), longer follow-up (P = 0.013), and older age at first intervention (P = 0.028). After exclusion of baseline factors related to glaucoma severity (cup/disc ratio and AGIS score at baseline), greater IOP fluctuation (P = 0.0017) and increasing number of glaucoma interventions (P = 0.0098) were the only statistically significant risk factors found to be associated with progression of VFs. Figure 1 shows the change of AGIS score over time according to IOP fluctuation. Eyes with an IOP fluctuation of <3 mmHg remained stable over the course of follow-up (P>0.05), whereas eyes with an IOP fluctuation of ≥3 mmHg demonstrated significant progression (P = 0.0006, regression slope, 0.026/month).

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• Figure 1. 

  This graph compares the change of Advanced Glaucoma Intervention Study (AGIS) score over follow-up in eyes with an intraocular pressure (IOP) fluctuation of <3 mmHg with that of those with an IOP fluctuation of ≥3 mmHg. In eyes with a lower IOP fluctuation, the AGIS score remained stable during follow-up, whereas eyes with a higher IOP fluctuation had a significant field progression (regression slope, 0.026/year, P = 0.0006).

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Discussion 

The baseline characteristics of our subgroup of AGIS patients are similar to those of the original cohort of patients described in previous AGIS reports.2 In this investigation, we used rigorous and clinically relevant PLR criteria to define the main outcome measure, VF worsening. We detected VF progression in approximately 30% of the eyes, which is consistent with the number of eyes showing progression in the same cohort according to the AGIS criteria (27%). We found that greater intervisit IOP fluctuation and older age at the time of first intervention were the most consistent predictors for VF progression. Each increased the odds for VF progression by approximately 30% for each 1-mmHg increase in IOP fluctuation and 5-year increment in age, respectively.

The AGIS is a multicenter randomized clinical trial designed to evaluate best management strategies after maximal effective medical treatment has failed to control IOP. A major outcome evaluated in the AGIS was the stability or progression of VFs as related to IOP control after the initial intervention.9 Eyes with IOPs of <18 mmHg at all visits during the first 6 years of follow-up were least likely to show worsening. A lower mean IOP during the 18 months after the initial intervention also predicted a better functional outcome. The covariates for which the regression models were corrected were age at randomization, gender, race, presence or absence of diabetes, intervention sequence, baseline IOP, and baseline VF score.

To date, all AGIS reports have used the AGIS scoring system for evaluating VF-related outcomes. The AGIS criteria for detection of VF progression are more conservative than alternative methods such as Glaucoma Change Probability Maps (used in the Early Manifest Glaucoma Trial), the Collaborative Initial Glaucoma Treatment Study criteria,10, 11 or PLR.12 Given the lack of a widely accepted external standard for evaluation of longitudinal field series, it seems advisable to assess such data with various analytical approaches. We have demonstrated, in a previous investigation, that PLR agrees with the AGIS scoring system in about two thirds of eyes.22 Although PLR has been criticized because of the long follow-up needed before progression can be demonstrated,12, 13, 14 this is not a major drawback in this study, because all the patients had at least 7 VFs and the mean follow-up was 7.7 years. Additionally, PLR has been proved to be highly specific in simulation experiments.12

In a complementary study, the AGIS investigators determined the predictive variables for a sustained reduction of the VF or VA after an initial intervention.15 About 30% of eyes had a sustained decrease of VF (SDVF), described as the first occurrence in an eye at 3 consecutive 6-month visits of either an increase in the VF defect score of ≥4 from the baseline value or a VF defect score of 19 or 20. Several associations were found to be important. Eyes with less of a baseline VF defect had an increased risk of subsequent SDVF. Male gender and worse baseline VA were additional significant risk factors for SDVF in the ATT sequence, and diabetes was an additional significant risk factor for SDVF in the TAT sequence.

In the present study, older age at the time of first intervention was 1 of the 2 risk factors demonstrating the strongest association with progression of VFs. Several other studies have reported a correlation of age with progression of glaucomatous damage,15, 16, 17, 18, 19, 20, 21 whereas others, including a report from the Collaborative Normal-Tension Glaucoma Study Group, have not confirmed such conclusions.26, 27, 28

An important finding of this study was that IOP fluctuation is 1 of 2 variables consistently associated with VF progression. Intraocular pressure fluctuation was not explored in previous AGIS reports. Our findings corroborate other reports regarding the significance of IOP fluctuation as a predictor for VF worsening.1, 18, 29, 30, 31, 32, 33 Werner et al pointed to IOP fluctuation as a risk factor for glaucoma progression after trabeculectomy.1 In a group of patients affected with mostly capsular glaucoma, Bergea et al found that IOP variation (range and peak) and mean IOP had a direct relationship with VF decay over 2 years of follow-up.32 Asrani et al found a strong relationship between large diurnal fluctuations of IOP, measured with home tonometry, and glaucoma progression.33 The mean office IOP had no predictive value, and mean home IOP showed a less significant association with glaucoma progression. Due to the design of the AGIS, we could only evaluate the effect of intervisit IOP fluctuation; therefore, our results cannot be compared directly with theirs. Stewart et al also reported findings similar to our results in a retrospective multicenter study.18 A higher number of second and third glaucoma interventions was observed in eyes with progressive glaucoma in this subset of AGIS patients (Table 2). This alone could have led to a higher IOP fluctuation. However, IOP fluctuation remained a significant predictor of VF worsening despite inclusion of the number of glaucoma interventions as an independent covariate in the regression models.

The length of follow-up proved to be the next important variable associated with worsening VFs. However, the length of follow-up could be an artifact of using PLR to define VF outcomes. Linear regression models are more likely to show a significant slope as the number of observations increases.34 Another explanation is that glaucomatous eyes are more likely to change the longer they are followed over time. Finding the length of follow-up as a statistically significant risk factor on logistic regression when the AGIS criteria were used as the outcome measure supports the latter hypothesis.

We did not find any relationship between mean IOP during follow-up and worsening of the VF, which is in contrast to the conclusion reached by the original analyses of the AGIS data9 and other randomized controlled trials21, 35 and retrospective studies.17, 18, 36 However, some other studies have similarly failed to show such a relationship.27, 37, 38, 39 Intraocular pressure fluctuation had a weak correlation with mean IOP during follow-up (r = 0.22, P<0.001) in this investigation. When multivariate logistic regression was repeated, excluding IOP fluctuation, the mean IOP reached statistical significance (P = 0.045, OR = 1.099) along with age, number of glaucoma surgeries, and male gender (data not shown). The low correlation between IOP fluctuation and mean IOP during follow-up and the less significant P value for the latter after exclusion of IOP fluctuation from the multivariate analysis suggest that IOP fluctuation is an independent and stronger predictor than mean IOP for VF progression in the AGIS. One plausible explanation has been suggested for the controversial findings regarding the role of IOP control in glaucoma progression in different studies.40 It is possible that tailoring management of glaucoma to glaucoma severity is the main reason some investigators have not found IOP control to be a risk factor for glaucoma progression.

The baseline AGIS VF score was not predictive of VF progression when PLR was used for definition of VF outcomes but was confirmed when AGIS criteria were used for this purpose. The finding of a relationship between a better baseline VF status and risk of subsequent VF worsening remains unexplained. Although a few smaller studies have reached similar conclusions,30, 41, 42 other reports have found either a positive correlation between the degree of field loss at baseline and VF worsening19, 21, 33, 43 or no correlation at all.26, 44 The above finding has been attributed, at least partially, to the nonlinear nature of the AGIS scoring system.15 It is also possible that the same criteria for worsening of VFs are not as sensitive for eyes already demonstrating advanced field loss at randomization. Detection of VF change may be easier when field loss is minimal at the onset. Whether or not the severity of baseline glaucomatous damage has any predictive power for subsequent progression of glaucoma remains debatable.

The AGIS is the only multicenter randomized study on glaucoma in which more than half of the enrolled patients are African American. However, none of the analyses reported so far, including the present one, have reported African American race as a significant risk factor for progression of VFs. This is in contrast to the Collaborative Initial Glaucoma Treatment Study, in which non-Caucasian race was found to be a predictor for VF worsening.19 Thirty-eight percent of the patients recruited in that study were African American. The Collaborative Normal-Tension Glaucoma Study did not reach a definitive conclusion regarding the effect of race on the risk of VF progression.28 However, the number of non-Caucasian patients enrolled was low. Although addressing a different question, the Ocular Hypertension Study Group also failed to confirm African American race as a risk factor for development of VF defects in multivariate analyses.45

A shortcoming of the current investigation and many others is the lack of an effective approach for taking into account the effect of cataract progression or its removal on the VF. One of the advantages of PLR is that it considers all the data during follow-up for detection of change. This should theoretically reduce the confounding effects of cataract extraction. However, inaccurate diagnosis of glaucomatous VF progression may have occurred due to unoperated advancing cataracts. This notwithstanding, analysis of different subgroups consistently showed IOP fluctuation to be associated with worsening VF.

In conclusion, using PLR analysis for evaluation of VF outcomes in AGIS, the 2 parameters consistently associated with VF progression were greater IOP fluctuation and older age at first glaucoma intervention. The fact that we found the same variables with both PLR and AGIS criteria strongly suggests that they are significant risk factors for predicting VF progression. Longer follow-up and a higher number of glaucoma interventions were other parameters that were, not unexpectedly, found to be risk factors for worsening of VF.

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Acknowledgements 

The authors thank all the AGIS investigators for their contributions.

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References 

1. Werner EB, Drance SM, Schulzer M. Trabeculectomy and the progression of glaucomatous visual field loss. Arch Ophthalmol. 1977;95:1374–1377
   • View In Article
   • MEDLINE
2. The Advanced Glaucoma Intervention Study (AGIS): 1. Study design and methods and baseline characteristics of study patients. Control Clin Trials 1994;15:299–325
   • View In Article
3. Advanced Glaucoma Intervention Study. 2. Visual field test scoring and reliability. Ophthalmology 1994;101:1445–55
   • View In Article
4. Gardiner SK, Crabb DP. Examination of different pointwise linear regression methods for determining visual field progression. Invest Ophthalmol Vis Sci. 2002;43:1400–1407
   • View In Article
   • MEDLINE
5. Noureddin BN, Poinoosawmy D, Fietzke FW, Hitchings RA. Regression analysis of visual-field progression in low tension glaucoma. Br J Ophthalmol. 1991;75:493–495
   • View In Article
   • MEDLINE
   • CrossRef
6. Membrey WL, Poinoosawmy DP, Bunce C, et al.  Comparison of visual field progression in patients with normal pressure glaucoma between eyes with and without visual field loss that threatens fixation. Br J Ophthalmol. 2000;84:1154–1158
   • View In Article
   • MEDLINE
   • CrossRef
7. Membrey WL, Bunce C, Poinoosawmy DP, et al.  Glaucoma surgery with or without adjunctive antiproliferatives in normal tension glaucoma (2. Visual field progression). Br J Ophthalmol. 2001;85:696–701
   • View In Article
   • MEDLINE
   • CrossRef
8. Chen PP. Correlation of visual field progression between eyes in patients with open-angle glaucoma. Ophthalmology. 2002;109:2093–2099
   • View In Article
   • Abstract
   • Full Text
   • Full-Text PDF (117 KB)
   • CrossRef
9. AGIS Investigators . The Advanced Glaucoma Intervention Study (AGIS) (7. The relationship between control of intraocular pressure and visual field deterioration). Am J Ophthalmol. 2000;130:429–440
   • View In Article
   • Abstract
   • Full Text
   • Full-Text PDF (361 KB)
   • CrossRef
10. Katz J, Congdon N, Friedman DS. Methodological variations in estimating apparent progressive visual field loss in clinical trials of glaucoma treatment. Arch Ophthalmol. 1999;117:1137–1142
    • View In Article
    • MEDLINE
11. Katz J. Scoring systems for measuring progression of visual field loss in clinical trials of glaucoma treatment. Ophthalmology. 1999;106:391–395
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (288 KB)
    • CrossRef
12. Vesti E, Johnson CA, Chauhan BC. Comparison of different methods for detecting glaucomatous visual field progression. Invest Ophthalmol Vis Sci. 2003;44:3873–3879
    • View In Article
    • MEDLINE
    • CrossRef
13. Katz J, Gilbert D, Quigley HA, Sommer A. Estimating progression of visual field loss in glaucoma. Ophthalmology. 1997;104:1017–1025
    • View In Article
    • Abstract
14. Spry PG, Bates AB, Johnson CA, Chauhan BC. Simulation of longitudinal threshold visual field data. Invest Ophthalmol Vis Sci. 2000;41:2192–2200
    • View In Article
    • MEDLINE
15. 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;134:499–512
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (210 KB)
    • CrossRef
16. Armaly MF, Krueger DE, Maunder L, et al.  Biostatistical analysis of the collaborative glaucoma study. I. Summary report of the risk factors for glaucomatous visual-field defects. Arch Ophthalmol. 1980;98:2163–2171
    • View In Article
    • MEDLINE
17. Mao LK, Stewart WC, Shields MB. Correlation between intraocular pressure control and progressive glaucomatous damage in primary open-angle glaucoma. Am J Ophthalmol. 1991;111:51–55
    • View In Article
    • MEDLINE
18. Stewart WC, Kolker AE, Sharpe ED, et al.  Factors associated with long-term progression or stability in primary open-angle glaucoma. Am J Ophthalmol. 2000;130:274–279
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (267 KB)
    • CrossRef
19. Lichter PR, Musch DC, Gillespie BW, et al.  Interim clinical outcomes in the Collaborative Initial Glaucoma Treatment Study comparing initial treatment randomized to medications or surgery. Ophthalmology. 2001;108:1943–1953
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (174 KB)
    • CrossRef
20. Landers J, Goldberg I, Graham SL. Analysis of risk factors that may be associated with progression from ocular hypertension to primary open angle glaucoma. Clin Experiment Ophthalmol. 2002;30:242–247
    • View In Article
    • MEDLINE
    • CrossRef
21. Leske MC, Heijl A, Hussein M, et al.  Factors for glaucoma progression and the effect of treatment (the Early Manifest Glaucoma Trial). Arch Ophthalmol. 2003;121:48–56
    • View In Article
    • MEDLINE
22. Nouri-Mahdavi K, Coleman AL, Hoffman D, et al. Pointwise linear regression for evaluation of visual field outcomes and comparison to the AGIS methodology. Arch Ophthalmol. In press
    • View In Article
23. The Advanced Glaucoma Intervention Study. Manual of Operations, 1993. Accession no. PB93-220192. Springfield, VA: National Technical Information Service; 1993
    • View In Article
24. SPSS [computer program]. Version 11.5. Chicago: SPSS Inc.; 2003
    • View In Article
25. SAS [computer program]. Version 8.2. Cary, NC: SAS Institute; 2001
    • View In Article
26. Wilson R, Walker AM, Dueker DK, Crick RP. Risk factors for rate of progression of glaucomatous visual field loss (a computer-based analysis). Arch Ophthalmol. 1982;100:737–741
    • View In Article
    • MEDLINE
27. Tezel G, Siegmund KD, Trinkaus K, et al.  Clinical factors associated with progression of glaucomatous optic disc damage in treated patients. Arch Ophthalmol. 2001;119:813–818
    • View In Article
    • MEDLINE
28. Collaborative Normal-Tension Glaucoma Study Group Drance S, Anderson DR, Schulzer M. Risk factors for progression of visual field abnormalities in normal-tension glaucoma. Am J Ophthalmol. 2001;131:699–708
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (254 KB)
    • CrossRef
29. Niesel P, Flammer J. Correlations between intraocular pressure, visual field and visual acuity, based on 11 years of observations of treated chronic glaucomas. Int Ophthalmol. 1980;3:31–35
    • View In Article
    • MEDLINE
    • CrossRef
30. O'Brien C, Schwartz B, Takamoto T, Wu DC. Intraocular pressure and the rate of visual field loss in chronic open-angle glaucoma. Am J Ophthalmol. 1991;111:491–500
    • View In Article
    • MEDLINE
31. Stewart WC, Chorak RP, Hunt HH, Sethuraman G. Factors associated with visual loss in patients with advanced glaucomatous changes in the optic nerve head. Am J Ophthalmol. 1993;116:176–181
    • View In Article
    • MEDLINE
32. Bergea B, Bodin L, Svedbergh B. Impact of intraocular pressure regulation on visual fields in open-angle glaucoma. Ophthalmology. 1999;106:997–1004 , discussion 1004–5
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (252 KB)
    • CrossRef
33. Asrani S, Zeimer R, Wilensky J, et al.  Large diurnal fluctuations in intraocular pressure are an independent risk factor in patients with glaucoma. J Glaucoma. 2000;9:134–142
    • View In Article
    • MEDLINE
34. Gardiner SK, Crabb DP. Frequency of testing for detecting visual field progression. Br J Ophthalmol. 2002;86:560–564
    • View In Article
    • MEDLINE
    • CrossRef
35. Collaborative Normal-Tension Glaucoma Study Group . Comparison of glaucomatous progression between untreated patients with normal-tension glaucoma and patients with therapeutically reduced intraocular pressures. Am J Ophthalmol. 1998;126:487–497
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (200 KB)
    • CrossRef
36. Vogel R, Crick RP, Newson RB, et al.  Association between intraocular pressure and loss of visual field in chronic simple glaucoma. Br J Ophthalmol. 1990;74:3–6
    • View In Article
    • MEDLINE
    • CrossRef
37. Schulzer M, Drance SM, Douglas GR. A comparison of treated and untreated glaucoma suspects. Ophthalmology. 1991;98:301–307
    • View In Article
    • Abstract
38. Martinez-Bello C, Chauhan BC, Nicolela MT, et al.  Intraocular pressure and progression of glaucomatous visual field loss. Am J Ophthalmol. 2000;129:302–308
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (318 KB)
    • CrossRef
39. Oliver JE, Hattenhauer MG, Herman D, et al.  Blindness and glaucoma (a comparison of patients progressing to blindness from glaucoma with patients maintaining vision). Am J Ophthalmol. 2002;133:764–772
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (166 KB)
    • CrossRef
40. Palmberg P. Risk factors for glaucoma progression (where does intraocular pressure fit in?). Arch Ophthalmol. 2001;119:897–898
    • View In Article
    • MEDLINE
41. Holmin C, Krakau CE. Trabeculoplasty and visual field decay (a follow-up study using computerized perimetry). Curr Eye Res. 1984;3:1101–1105
    • View In Article
    • MEDLINE
    • CrossRef
42. Suzuki Y, Shirato S, Adachi M, Hamada C. Risk factors for the progression of treated primary open-angle glaucoma (a multivariate life-table analysis). Graefes Arch Clin Exp Ophthalmol. 1999;237:463–467
    • View In Article
    • MEDLINE
    • CrossRef
43. Grant WM, Burke JF. Why do some people go blind from glaucoma?. Ophthalmology. 1982;89:991–998
    • View In Article
    • Abstract
44. Wilson MR, Kosoko O, Cowan CL, et al.  Progression of visual field loss in untreated glaucoma patients and glaucoma suspects in St. Lucia, West Indies. Am J Ophthalmol. 2002;134:399–405
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (101 KB)
    • CrossRef
45. Ocular Hypertension Treatment Study Group Gordon MO, Beiser JA, Brandt JD, et al.  The Ocular Hypertension Treatment Study (baseline factors that predict the onset of primary open-angle glaucoma). Arch Ophthalmol. 2002;120:714–720 , discussion 829–30
    • View In Article
    • MEDLINE