Visual field progression outcomes in glaucoma subtypes

Visual field progression outcomes in glaucoma subtypes Carlos Gustavo De Moraes, 1,2,3 Jeffrey M. Liebmann, 1,2 Craig A. Liebmann, 1 Remo Susanna Jr, 3 Celso Tello 1,4 and Robert Ritch 1,4 1 Einhorn Clinical Research Center, New York Eye and Ear Infirmary, New York, New York, USA 2 Department of Ophthalmology, New York University School of Medicine, New York, New York, USA 3 Department of Ophthalmology, University of Sao Paulo School of Medicine, Sao Paulo, Brazil 4 Department of Ophthalmology, New York Medical College, Valhalla, New York, USA ABSTRACT. Purpose: To determine whether glaucoma subtype is an independent risk factor for visual field (VF) progression. Methods: We reviewed the charts of glaucoma suspects and glaucoma patients seen in a referral practice between 1999 and 2009. Automated pointwise linear regression analysis determined the rates of VF change. A progression endpoint was determined when two or more adjacent test locations in the same hemifield showed a threshold sensitivity decline at a rate of 1.0 db year with p < 0.01. Results: We included 841 eyes (841 patients; mean age, 64.1 ± 12.6 years; mean number of VF tests, 10.8 ± 2.8; mean follow-up, 6.4 ± 1.7 years). The glaucomatous group consisted of angle-closure glaucoma (76 eyes), juvenile primary open-angle glaucoma (37 eyes), normal-tension glaucoma (81 eyes), pigmentary glaucoma (34 eyes), primary open-angle glaucoma (275 eyes) and exfoliative glaucoma (XFG, 84 eyes). Normal-tension glaucoma eyes were more likely to present with beta-zone parapapillary atrophy and disc haemorrhage (p < 0.01). Exfoliative glaucoma eyes had the fastest rates of global VF change ()0.65 db year), as well as the highest mean, fluctuation, and peak intraocular pressure during follow-up (16.5, 3.0 and 22.0 mmhg, respectively) and reached a progression endpoint more frequently (40%). After adjusting for all covariates, including the glaucoma phenotype, there was no difference among groups regarding global rates of VF change and the risk of reaching a progression endpoint. Conclusions: Despite different clinical features, epidemiology and genetics, glaucoma phenotype is not an independent risk factor for VF progression. Rather, variations in well-known, reported risk factors remain important disease parameters that affect progression. Key words: glaucoma intraocular pressure phenotype risk factors visual field progression Acta Ophthalmol. 2013: 91: 288 293 ª 2011 The Authors Acta Ophthalmologica ª 2011 Acta Ophthalmologica Scandinavica Foundation doi: 10.1111/j.1755-3768.2011.02260.x Introduction Glaucoma is an acquired, degenerative optic neuropathy characterized by a specific pattern of abnormalities of the optic nerve complex [optic nerve head, retinal nerve fibre layer (RNFL) and parapapillary region] and corresponding damage to the visual field (VF). Despite common optic nerve features, the glaucomas are not a single disease with a unique cause, but rather a group of ocular conditions that share the aforementioned features and which can arise by various mechanisms. Randomized clinical trials have investigated the role of intraocular pressure (IOP) reduction and different risk factors on the onset and progression of glaucoma (AGIS Investigators 2000; Drance et al. 2001; Gordon et al. 2002; Leske et al. 2007; Miglior et al. 2007; Musch et al. 2009; De Moraes et al. 2010). It remains uncertain whether different glaucomas progress at different rates and whether the underlying disorder leading to glaucoma should also be considered when estimating the risk of progression. Some evidence that certain glaucomas could progress at different rates was provided by the Early Manifest Glaucoma Trial (EMGT), in which the presence of exfoliation syndrome (XFS) at baseline was associated with a twofold 288

increased risk of reaching a progression endpoint (Leske et al. 2007). However, other glaucoma entities were not tested in this trial, which included a very homogeneous population randomized to a specific therapy that was atypical given the choices available at the time (De Moraes et al. 2010). We sought to determine whether glaucoma subtype, as assessed at baseline examination, could represent an additional risk factor for VF progression in clinical practice. Methods This retrospective observational cohort was approved by the New York Eye and Ear Infirmary Institutional Review Board and followed the tenets of the Declaration of Helsinki. The New York Glaucoma Progression Study (GAPS) is a longitudinal study designed to bridge the findings of the landmark glaucoma trials and clinical practice. We included GAPS subjects evaluated in the glaucoma referral practice of the authors from January 1999 to September 2009. The GAPS database has been described elsewhere (De Moraes et al. 2009; Prata et al. 2010; Folgar et al. 2010; Teng et al. 2010; De Moraes et al. 2011). Briefly, after an initial visit consisting of a complete ophthalmologic examination, standard achromatic perimetry (24-2 SITA-SAP, Humphrey Field Analyzer II; Carl Zeiss Meditec, Inc., Dublin, CA, USA) and optic disc stereophotographs, patients were reexamined, usually at 3- to 6-month intervals, and the same tests repeated within 6 12 months. To maximize sensitivity and specificity of VF analysis by pointwise linear regression (Spry et al. 2000; Chauhan et al. 2008), we selected all GAPS subjects with at least eight SITA-standard VF examinations. All eligible eyes were required to have best corrected visual acuity of 20 40 or better at baseline and spherical equivalent 6 dioptres. If both eyes of the same patient were eligible, the eye with the greatest number of reliable VF tests was enrolled. Clinical data We divided the eligible eyes into two groups: glaucoma suspects included eyes with normal baseline VF [glaucoma hemifield test (GHT) within normal limits and pattern SD > 0.05] with statistically elevated IOP (at least one measurement >22 mmhg by Goldmann applanation tonometry) with or without an optic nerve compatible with glaucoma and the glaucomatous group included eyes with baseline VF abnormalities (described below) and glaucomatous optic neuropathy (GON). The definition of GON was based on the clinical examination of the optic nerve complex (diffuse or localized neuroretinal rim thinning or RNFL loss, cup-to-disc ratio >0.6 or inter-eye asymmetry >0.2 in the absence of other retinal or neurological abnormality that could explain these findings). All glaucomatous eyes were treated with various forms of therapy (medical, laser, or surgical) at the discretion of the treating physician. We included in this study those glaucomas in one of the following categories: primary open-angle glaucoma (POAG); normal-tension glaucoma (NTG); exfoliative glaucoma (XFG); pigmentary glaucoma (PG); juvenile primary open-angle glaucoma (JPOAG); and angle-closure glaucoma (ACG), excluding neovascular glaucoma, and other secondary causes of angle closure. Eyes with POAG had gonioscopically open angles, no signs of pigment dispersion syndrome or exfoliation material, and no other secondary causes of IOP elevation (such as uveitis or trauma). Eyes with POAG that had no measured or known IOP >21 were classified as NTG. Eyes with XFG had characteristic exfoliation material on the pupillary border or anterior lens capsule. Eyes with PG had open angles and signs including Krukenberg spindle, iris transillumination defects and trabecular hyperpigmentation. Eyes with JPOAG were defined the same as POAG, except that the age of onset of the disease had to be between 10 and 35 years. Eyes with ACG had a history of iridotrabecular contact seen during gonioscopy and had undergone laser iridotomy. Intraocular pressure measurements between the baseline and last VF tests entered in the regression were used to calculate the IOP parameters. Details of the method have been described previously (De Moraes et al. 2011). Briefly, peak IOP was the highest measured IOP between the first and last VF entered in the regression analysis. The mean follow-up was calculated by averaging all pressure measurements obtained after the date of the first VF test entered in the regression. To avoid the undesired effect that numerous sequential IOP measurements during a short period of time would have on the final average, we used the average IOP for each 6-month period following the first VF entered in the analysis to calculate the mean follow-up IOP. IOP fluctuation was defined as the SD of these values. We excluded all IOP measurements 4 weeks following any type of incisional surgery or laser procedure to avoid the effect of transitory IOP changes that often occur in this period. Central corneal thickness (CCT) was measured using ultrasonic pachymetry (DGH-550; DGH Technology Inc., Exton, PA, USA). Disc photograph review Disc photographs of patients were reviewed by two masked glaucoma specialists searching for disc haemorrhage (DH) and beta-zone parapapillary atrophy (bppa). The definitions and process of DH and PPA review have been described in detail elsewhere (Airaksinen et al. 1981; Jonas & Iester 1995; Jonas et al. 1989, 1989 Prata et al. 2010; De Moraes et al. 2011). In cases in which the investigators disagreed, a third investigator was used for adjudication. Visual field analysis The definitions and process of VF review have been described in detail elsewhere (De Moraes et al. 2011). Briefly, a glaucomatous VF was defined as a GHT outside normal limits or if the pattern standard deviation was triggered at p < 0.05 on at two consecutive baseline VF tests. Automated pointwise linear regression (PLR) analysis was performed using ProgressorÔ software (Version 3.3; Medisoft, Inc., Leeds, UK) providing global and pointwise rates of change [decibels (db) year]. Details of the software have been described elsewhere (Fitzke et al. 1996). Two progressing points had to be adjacent and within the same hemifield to 289

denote the eye as progressing. Progression was defined as the presence of a test point with a slope of sensitivity over time >1.0 db loss year, with p < 0.01 (Gardiner & Crabb 2002; Nouri-Mahdavi et al. 2004). For edge points (nasal-most points of the 24-2), a stricter slope criterion of >2.0 db loss year (also with p < 0.01) was used. Two progressing points had to be adjacent and within the same hemifield to denote the eye as progressing. These same criteria were used in a previous publication by our group (De Moraes et al. 2010). Statistical analysis Categorical variables were compared using the chi-square test. Kruskal Wallis test was used for comparisons of continuous variables among groups. Logistic regression was used to investigate the association between glaucoma phenotypes and the risk of progression. First, each variable was tested independently in a univariable model, and then tested after adjusting for other clinical characteristics. Because greater follow-up time increases the likelihood of detecting progression using trend analysis (Chauhan et al. 2008), all analyses were time-adjusted. Variables with p < 0.25 in the univariable model were entered in a single step to the multivariable model. A generalized linear model was used to compare the rates of change among subgroups after adjusting for the covariates. Statistical significance was defined at p < 0.05. Computerized statistical analysis was performed using Med- CalcÔ software (MedCalc, Inc., Mariakerke, Belgium). Results We enrolled 841 eyes (841 patients, 60% women, 87% European ancestry). Mean age at baseline assessment was 64.1 ± 12.6 years. Mean followup was 6.4 ± 1.7 years, and the mean number of evaluated VF tests was 10.8 ± 2.8. Eyes with glaucoma had more progressing points [5.99 ± 7.4 (median = 3), versus 3.86 ± 3.6 (median = 2) points, p < 0.01] and faster rates of global VF change [)0.45 ± 0.7 (median = )0.32) versus )0.21 ± 0.4 (median = )0.13) db Table 1. Distribution of subgroups and their progression characteristics. n Global rate of VF change (db year)* year, p < 0.01] than glaucoma suspect eyes. The distribution of eyes based on their diagnoses and their progression data is presented in the Table 1. Risk factors for VF progression in this cohort have been previously reported (De Moraes et al. 2011). In the univariable analysis, IOP peak, mean, fluctuation, age, XFS, CCT, DH and bppa were significantly associated with progression. In the multivariable analysis, peak IOP, CCT, bppa, DH were significantly associated with progression (p < 0.05). The majority of glaucomatous eyes were diagnosed with POAG (n = 275). Their mean rate of global VF change was )0.48 ± 0.8 db year, with a mean follow-up and peak IOP of 15.28±2.9 and 20.07 ± 4.1 mmhg, respectively. Exfoliative glaucoma eyes (n = 84) were older than the other subtypes (72.36 ± 8.8 years), progressed at a mean rate of )0.65±0.7 db year, with mean and peak IOPs of 16.5 ± 2.9 and 21.95±5.2 mmhg, respectively. Normal-tension glaucoma eyes had a mean rate of VF change of )0.33 ± 0.3 db year and showed the lowest mean and peak IOPs during follow-up (13.34 ± 2.3 and 16.76±2.8 mmhg, respectively). Angle-closure glaucoma eyes progressed at a mean rate of )0.39 ± 0.5 db year with mean and peak IOPs of 16.16 ± 2.9 and 20.96 ± 4.2 mmhg, respectively. Juvenile primary open-angle glaucoma eyes progressed at a mean rate of )0.26 ± 0.5 db year with mean and peak IOPs of 14.96 ± 3.7 and 19.89 ± 5.2 mmhg, respectively. Pigmentary glaucoma eyes progressed at a mean rate of )0.28 ± 0.3 db year and had mean and peak IOPs of 14.40 ± 3.5 and 18.82 ± 4.5 mmhg, respectively (Fig. 1). Among eyes with established glaucoma, there were no significant differences among subtypes regarding follow-up time, number of VF tests, baseline mean deviaton (MD), or CCT. Suspect eyes were younger (62.0 ± 11.4 versus 64.9 ± 13.0 years, p < 0.01) and had thicker corneas (550.9 ± 35.5 versus 540.9 ± 37.3 microns, p < 0.01) than the glaucoma group. There were significantly more women in the NTG group (p < 0.01). Normal-tension glaucoma eyes also had a greater frequency of everdetected DH and bppa (16% and 71%, respectively, p < 0.05). Exfoliative glaucoma patients experienced higher mean, peak and IOP fluctuation than the other groups (Fig. 1). Exfoliative glaucoma eyes showed not only faster global rates of progression but also reached progression endpoints more often than the other groups (p < 0.01, Table 2). In the univariable logistic regression, XFG diagnosis was significantly associated with a progression outcome (OR = 1.79, p = 0.01), which became nonsignificant after adjusting for the other covariates in the multivariable model (OR = 1.64, p = 0.07). After adjusting for baseline and intercurrent clinical features (IOP, CCT, age, gender, DH, beta-ppa, follow-up time), there was no significant difference in global rates of VF change among diagnostic groups (p > 0.20). Progression endpoint (%) Number of progressing points eye* POAG 275 )0.48 ± 0.8 86 (31) 6.33 ± 7.3 JPOAG 37 )0.26 ± 0.5 7 (18) 3.66 ± 4.0 NTG 81 )0.33 ± 0.3 22 (27) 2.84 ± 2.7 XFG 84 )0.65 ± 0.7 34 (40) 9.68 ± 10.3 PG 34 )0.28 ± 0.3 7 (20) 3.68 ± 3.2 ACG 76 )0.39 ± 0.5 14 (18) 5.65 ± 8.2 Suspects 254 )0.21 ± 0.4 25 (9) 3.86 ± 3.6 * Data are shows as mean ± SD. Bonferroni post hoc correction shows significant difference between XFG and all other groups. CCT = central corneal thickness; IOP = intraocular pressure; VF = visual field; POAG = primary open-angle glaucoma; JPOAG = juvenile primary open-angle glaucoma; NTG = normal-tension glaucoma; XFG = exfoliative glaucoma; PG = pigmentary glaucoma; ACG = angle-closure glaucoma. 290

Peak IOP (mmhg) (A) Mean IOP (mmhg) (B) IOP fluctuation (mmhg) (C) 25 20 15 10 5 0 18 16 14 12 10 8 6 4 2 0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 Discussion ACG JOAG NTG PG POAG XFG Type of glaucoma ACG JOAG NTG PG POAG XFG Type of glaucoma ACG JOAG NTG PG POAG XFG Type of glaucoma Fig. 1. Intraocular pressure (IOP) characteristics among different types of glaucoma. Data are shown as mean and 95% confidence intervals. p-values refer to Kruskal Wallis test. (A) Peak IOP (p < 0.01). Normal-tension glaucoma (NTG) significantly different than angle-closure glaucoma (ACG), juvenile primary open-angle glaucoma (JPOAG), pigmentary glaucoma (PG), and primary openangle glaucoma (POAG). Pigmentary glaucoma significantly different than exfoliative glaucoma (XFG). Exfoliative glaucoma significantly different than NTG, PG, and POAG. (B) Mean follow-up IOP (p < 0.01). Angle-closure glaucoma significantly different than POAG. JPOAG significantly different than XFG. Normal-tension glaucoma significantly different than ACG, JPOAG, POAG, and XFG. Pigmentary glaucoma significantly different than ACG and XFG. (C) Intraocular pressure fluctuation (SD) (p < 0.01). Normal-tension glaucoma significantly different than ACG, JPOAG, POAG, and XFG. POAG significantly different than XFG. We have recently reported the risk factors associated with more rapid VF progression in a population with established, treated glaucoma (De Table 2. Rates of visual field change (db year) among groups after adjusting for age, central corneal thickness, peak intraocular pressure, beta-zone parapapillary atrophy and disc haemorrhage. Global rate of VF change 95% confidence interval POAG )0.46 ± 0.04 )0.54 to )0.37 JPOAG )0.37 ± 0.13 )0.63 to )0.12 NTG )0.45 ± 0.08 )0.61 to )0.29 XFG )0.55 ± 0.08 )0.71 to )0.39 PG )0.38 ± 0.12 )0.63 to )0.14 ACG )0.36 ± 0.08 )0.53 to )0.20 Values are shown as mean ± SE (db year). Bonferroni post hoc correction shows no significant difference among groups. POAG = primary open-angle glaucoma; JPOAG = juvenile primary open-angle glaucoma; NTG = normal-tension glaucoma; XFG = exfoliative glaucoma; PG = pigmentary glaucoma; ACG = angle-closure glaucoma; VF = visual field. Moraes et al. 2011). However, little is known whether different glaucoma subtypes tend to progress at different rates in clinical practice. Most RCTs have investigated populations with POAG and little information is available on rates of progression of other common glaucomas. Herein, we describe the risk factors and the rates of VF progression among patients with different glaucomas. In concordance with the major RCTs (AGIS Investigators 2000; Drance et al. 2001; Gordon et al. 2002; Leske et al. 2007; Miglior et al. 2007; Musch et al. 2009), we found a significant role of higher IOP, decreased CCT, presence of DH and older age in subjects with established glaucoma. These patients progressed more rapidly than those with normal baseline fields, which can be explained, at least in part, by the fact that they had higher IOP, smaller CCT and older age than suspects. Moreover, the confirmed presence of the disease may also increase the risk and rate of progression. One should be reminded that in our study, suspect patients (because of ocular hypertension or suspicious discs) were selected on the basis of IOP levels in addition to other variables; therefore, glaucoma suspects were expected to have thicker corneas than patients with glaucoma. This might imply that a subgroup of normal cases (i.e: normal IOP, normal fields and normal discs) with a very low risk of progression was probably included in the glaucoma suspects group. It is possible that these normal patients may have diluted the findings of our suspect group which may help explain different progression rates in glaucoma cases compared with glaucoma suspects. Among the glaucomas, XFG eyes had higher rates of VF progression, more rapid VF change and a greater number of progressing points using PLR analysis. However, the increased risk associated with XFS became nonsignificant after adjusting for baseline and intercurrent variables, suggesting that other ocular parameters, such as higher IOP peaks, perhaps more common in XFS eyes, are responsible for the additional risk found in this disorder. Glaucoma is a group of diseases characterized by progressive optic neuropathy in which IOP plays a major role regarding incidence, prevalence and progression. The phenotypic appearance differentiates the various subtypes. These categorizations have been helpful in better understanding the pathogenesis of glaucoma, its different forms of presentation, systemic and ocular associations, and provided treatment guidance. Our data support that these different glaucomas may differ regarding systemic (age and gender) and ocular (IOP parameters, incidence and prevalence of beta-ppa and detected DH, etc) features. However, when investigating the relationships between these glaucomas and their rates of progression, we observed that none of them was independently associated with a worse VF outcome in a treated population. In fact, our data support the concept that currently known ocular and systemic risk factors may be more important than the glaucoma subtype when estimating the risk of VF progression. This became particularly clear in the group with XFS, a systemic disorder with a genetic basis (Ritch 2008), that has been reported to be an independent risk factor for VF progression (Grødum et al. 2005; Leske et al. 2007) and is thought to be particularly aggressive. In our analysis, even though XFG patients sustained more rapid VF progression than the other groups, with more significantly progressing points and therefore reaching progression endpoints more frequently, such differences became nonsignificant in the multivariable 291

analysis that accounted for higher mean, SD and peak IOP and older age. Furthermore, our findings should only be applied to populations whose characteristics are similar to ours and hence should not be directly compared with other studies. For instance, differences between our study and the results of the EMGT results could be due to various reasons, including study design (ours was a retrospective cohort of patients seen in a referral practice), how VF endpoints were determined (trend versus event analysis), and different modalities of treatment. A relatively large proportion of our cohort (14%) had XFG. In the EMGT, which is the only large RCT to find an independent association between XFG and progression, only 6% (or nine patients) of the treated group had XFG. The way XFG is treated in our practice differs from that used in the EMGT (betaxolol and argon-laser trabeculoplasty). We not only use prostaglandin analogs as a first-choice therapy in this and other glaucomas, but we often prescribe pilocarpine 2% at bedtime to restrict pupillary movement and thus minimize both iris rubbing of exfoliation material from the lens surface and disruption of iris pigment epithelial cells by he exfoliation material, both of which may block aqueous outflow through the trabecular meshwork. In this study, we also found that NTG patients had more frequent beta-ppa and DH, which are also well-known risk factors associated with progression (Quigley et al. 1994; Jonas et al. 2004; Budenz et al. 2006; Bengtsson et al. 2008; Teng et al. 2010). However, their velocity of VF deterioration did not differ significantly from the other groups in the final multivariable analysis that controlled for these variables. Recently, Heijl et al. (2009) described the natural history of VF progression in patients initially randomized to observation in the EMGT. They divided their population into three groups: NTG, high-tension glaucoma and XFG. The overall median MD rate of VF change in the entire study was )0.40 db year in patients followed with a mean follow-up untreated IOP of 19 mmhg. In our study, the median global rate of VF change using PLR was )0.32 db year, with a mean follow-up treated IOP of 15 mmhg. In concert with our findings, the EMGT authors also found faster rates of MD change in older patients with XFG, whereas NTG eyes showed the lowest rates. We have previously reported that NTG eyes progressed more slowly than XFG eyes, but that this difference became nonsignificant after adjusting for CCT, IOP and age differences (Ahrlich et al. 2009). There is little information in the literature regarding rates of progression in different glaucomas. The major prospective RCT generally excluded patients with angle closure and secondary glaucomas, limiting the information available about these disorders. To our knowledge, this is the first large cohort to compare not only the clinical characteristics of different glaucomas but also their rates of progression. We used trend analysis to detect VF change, unlike the majority of the reported cohorts which used event analysis (AGIS Investigators 2000; Drance et al. 2001; Gordon et al. 2002; Leske et al. 2007; Miglior et al. 2007; Musch et al. 2009). We (De Moraes et al. 2009; Prata et al. 2010; Folgar et al. 2010; Teng et al. 2010) and others (Fitzke et al. 1996; Gardiner & Crabb 2002; Nouri-Mahdavi et al. 2004) have previously described the ability of trend analysis to assess the velocity of past progression and estimate future VF loss, assuming linearity of progression. The present study validates the important roles of previously reported risk factors (IOP, CCT, age). A potential caveat for our study is whether there was any difference between groups regarding the frequency of filtering surgeries. Nevertheless, analysis of our data suggested that subjects with more advanced disease received more aggressive therapy and achieved lower IOP (Forchheimer et al. 2011), even though their was no tendency to perform more filtering surgeries in any particular glaucoma phenotype. The fact that the final multivariable model did not identify XFS as an independent risk factor is analogous to one of the results of the OHTS trial (Gordon et al. 2002). In the OHTS univariable model, the investigators found that African ancestry was a significant risk factor for the conversion to glaucoma from ocular hypertension. In the multivariable model, after adjusting for CCT, IOP, MD and other covariates, the influence of ethnicity became nonsignificant. Individuals of African descent, in parallel to XFG patients, may progress faster than the other groups because of intrinsic disease characteristics of these populations. For instance, they have thinner corneas than individuals of European ancestry and higher IOP when evaluated cross-sectionally. In the OHTS study, thinner CCT and disc parameters likely accounted for the more rapid rate of loss in this population and the elimination of ethnicity as a risk factor in the multivariable model (Higginbotham et al. 2004). Likewise, XFG patients, as supported by our data and the literature, have higher mean and peak IOP and fluctuation than other types of glaucoma. They also present at an older age, and age is an important risk factor for glaucoma onset and progression. In our multivariable model, XFS was likely no longer an independent risk factor for progression because the increased progression risk could be explained by the increased risk in all IOP parameters and their older age. We hypothesize that its borderline significance would diminish as more IOP peaks are identified with longer follow-up or more intensive IOP monitoring (particularly outside of normal office hours). In a treated population from a referral practice, we found that even though different glaucomas vary regarding their clinical features and rates of progression, glaucoma subtype by itself may not be useful for estimating the risk of future progression without accounting for the particular risk factors known to be associated with VF progression. Careful assessment of ocular and systemic risk factors is critically important regardless of glaucoma subtype. Whether the genotype will be more important than phenotype remains to be demonstrated. Acknowledgement The James Cox Chambers Research Fund of the New York Glaucoma Research Institute, New York, NY. References AGIS Investigators (2000): The Advanced Glaucoma Intervention Study (AGIS) 7: 292

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Teng CC, De Moraes CG, Prata TS, Tello C, Ritch R & Liebmann JM (2010): Beta-zone parapapillary atrophy and the velocity of glaucoma progression. Ophthalmology 117: 909 915. Received on December 8th, 2010. Accepted on July 29th, 2011. Correspondence: Carlos Gustavo V. De Moraes, MD 310 East 14th Street New York New York 10003, USA Tel: + 1 212 477 7540 Fax: + 1 212 420 0067 Email: demoraesmd@gmail.com 293