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Epidemiology |

The Association of Primary Open-angle Glaucoma With Mortality A Meta-analysis of Observational Studies FREE

Mona Akbari, MPH; Sara Akbari, MD; Louis R. Pasquale, MD
[+] Author Affiliations

Author Affiliations: Harvard University School of Public Health, Boston, Massachusetts (Ms M. Akbari); Columbia University College of Physicians & Surgeons, New York, New York (Ms M. Akbari); University of Michigan Kellogg Eye Center, Ann Arbor (Dr S. Akbari); and the Department of Ophthalmology, Massachusetts Eye and Ear Infirmary and Harvard Medical School, Boston (Dr Pasquale).


Section Editor: Leslie Hyman, PhD

More Author Information
Arch Ophthalmol. 2009;127(2):204-210. doi:10.1001/archophthalmol.2008.571.
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Published online

Objective  To conduct a meta-analysis to estimate the relationship between primary open-angle glaucoma (POAG) and mortality.

Methods  A systematic search of the PubMed, Embase, and Web of Science databases yielded 9 cohort studies with relative risk (RR) estimates for all-cause mortality. The studies were critically reviewed by an expert in the field. The data were extracted and analyzed in a pooled analysis by the random-effects model. Meta-regression to assess for heterogeneity by several covariates and subgroup analysis on cardiovascular mortality were performed.

Results  A significant risk was not detected in the final pooled analysis (RR, 1.13; 95% confidence interval [CI], 0.97-1.31) for all-cause mortality. A meta-regression across mean follow-up time, age, and sex was not significant. A meta-regression across diabetes status in 3 of the 9 studies did not demonstrate significant results (P = .94). Subgroup analysis on cardiovascular mortality from 4 of the 9 studies was marginally significant (RR, 1.20; 95% CI, 1.00-1.43; P = .05), but insignificant after removal of a study in which POAG was ascertained by self and proxy report (RR, 1.12; 95% CI, 0.87-1.46).

Conclusion  This meta-analysis does not demonstrate an association between POAG and all-cause or cardiovascular mortality.

Figures in this Article

Primary open-angle glaucoma (POAG) is a multi-factorial, chronic, progressive disease that results in damaged structural integrity of the optic nerve and diminished visual function. The exact etiology of POAG remains unknown, and it is unclear whether POAG is an ocular process in the context of a diseased host predisposed to a shortened life span. Understanding the relationship between POAG and mortality is critical, with an estimated 44.7 million people affected worldwide by the year 2010.1If true mortality rates in patients with POAG differ from those of the general population, this information may provide insight into the underlying disease etiology.

It is difficult to infer the relationship between POAG and mortality based on an analysis of known determinants of mortality in middle-aged adults. Primary open-angle glaucoma may not produce excess mortality simply because the disease prevalence increases dramatically with age.2Mean arterial pressure as well as other blood pressure indices are risk factors for all-cause mortality,3,4yet lower blood pressure in the context of higher intraocular pressure (IOP) resulting in low perfusion pressure is a strong risk factor for POAG.58Obesity is associated with cardiovascular mortality,9,10and several studies show a positive correlation between body mass index (calculated as weight in kilograms divided by height in meters squared) and IOP1116; however, the association between body mass index and POAG may be null or inverse in nature.17,18Finally, diabetes mellitus, a risk factor for cardiovascular and all-cause mortality,1922is positively associated with POAG in some,2329but not all, studies.17,3034

A limitation in studies assessing POAG and mortality is the small number of POAG cases. Epidemiologic studies with a limited number of participants may lack sufficient study power to detect a small to moderate relationship between POAG and mortality. Furthermore, studies may have variable accounting of important covariates that affect mortality. The primary aim of this study is to conduct a meta-analysis to estimate the relationship between POAG and mortality and to evaluate for sources of heterogeneity.

LITERATURE SEARCH

Two independent reviewers (M.A. and S.A.) completed a systematic search of the PubMed, Embase, and Web of Science databases without date restrictions for articles related to mortality in patients with POAG. A combination of text words and Medical Subject Headings of the National Library of Medicine or subject headings was used in the database search. The terms included were glaucoma, glaucoma open angle, primary open angle glaucoma, hazard rate, mortality, and survival.

The titles of all articles were read and the relevant abstracts evaluated. The bibliographies were cross-referenced, and pertinent papers were extracted in this manner. Authors were contacted for supplemental information. Manual searches for articles found electronically and/or referenced, but not available online, were completed at the institutional library. The electronic and hand searches were completed in March 2008.

SELECTION CRITERIA AND DATA EXTRACTION

Studies were included if they (1) reported POAG or IOP status, (2) excluded secondary glaucoma, (3) reported all-cause mortality relative risks (RR) with 95% confidence intervals (CI), (4) included a control group, and (5) were written in English. Study quality was assessed using the suggested framework from Egger et al.35The variables examined included adequate explanation of study sampling and diagnostic criteria for POAG, outcome results for a high proportion of the population, and appropriate statistical adjustment of the outcome. In the primary analysis, the definition of POAG included diagnosis based on optic nerve and/or visual field criteria from standardized examinations as well as cases diagnosed by elevated IOP measurements or based on self and proxy report of glaucoma. However, not all patients with elevated IOP develop POAG, and not all POAG patients have high IOP. Similarly, self and family reporting may not be a reliable estimate of glaucoma, has a potential for recall bias, and may lead to overreporting and/or underreporting. To account for the reservations associated with the latter definitions, we performed a secondary analysis excluding these studies.36,37

We excluded 2 studies that were not published in English.38,39Their abstracts were not available for review, and we could not determine if they met the inclusion criteria. We excluded studies that were limited to nongeneralizable patients, including a study of mortality in blind40and in diabetic41patients with POAG. Finally, because exfoliation syndrome is thought to be of different genetic etiology4245and possibly associated with excess morbidity,46we eliminated one study with an overrepresentation of exfoliation syndrome.47

Reviewers independently extracted the following information from included articles: (1) names of the first author and publication date, (2) methods of POAG and mortality assessment, (3) mean follow-up time, (4) total number of patients with glaucoma, (5) mean age and sex distribution, (6) the maximally- and minimally-adjusted risk estimates, (7) confounders considered in the final analysis, and (8) distribution of systemic and ophthalmic comorbidities such as diabetes, if reported. Two studies offered multiple definitions of POAG.37,48In the Rotterdam Study,48we used cases in the definite category because this highly specific definition is least likely to affect RR data.49In the National Health Interview Survey,37estimates from the glaucoma group without visual impairment were used because visual impairment may be an independent predictor of mortality.50An expert in the field (L.P.) reviewed the studies to resolve inconsistencies in the extracted data.

STATISTICAL ANALYSIS

We used the Qtest to evaluate study heterogeneity and the I2statistic to estimate the proportion of total variability of the pooled estimate due to between-study variation.51We calculated pooled estimates with a random-effects model that accounted for variability between study populations.35The fully-adjusted risk ratios from studies were used in the pooled analyses. We included 2 studies that assessed IOP and self- or proxy-reported POAG in the primary analysis but excluded them in secondary analysis.36,37We performed a meta-regression to assess heterogeneity in length of follow-up and sex, age, and diabetes status across studies. In a subgroup analysis we assessed the relationship between POAG and cardiovascular mortality using 4 studies in which such data were available.37,5254A sensitivity analysis was performed to assess the robustness of the pooled estimates of all-cause and cardiovascular mortality. We used the Begg funnel plot and Egger publication bias plot to detect publication bias. The statistical software used was STATA version 9 (StataCorp LP, College Station, Texas), and the significance level was set to P< .05.

The search revealed 844 articles, 792 of which were excluded after first-pass review of titles because they were not relevant to the subject of POAG and mortality. Forty of the remaining 52 articles did not meet inclusion criteria after review of the abstracts. Four of the 40 articles related to glaucoma and mortality used population life tables for comparison and thus did not meet the inclusion criteria of a control group.5558Articles that met the a priori inclusion criteria (n = 12) were further evaluated. Three articles were excluded and 9 included in the final analysis (Figure 1).

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Figure 1.

Search and study selection process.

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STUDY CHARACTERISTICS

The characteristics of included studies are outlined in Table 1and Table 2. One study was a population-based, annual, cross-sectional study,37while the others were prospective cohorts. The mean time to follow-up ranged from 4.5 to 16 years. Collectively, the sample size was 146 848, with 2811 classified as having POAG. While studies varied on their exact criteria for POAG, most were independent of IOP measurement. Many studies included presence of glaucomatous visual field defects48,5254,59,60and assessment of the optic disc in their definition of POAG.48,5254,5961

Table Graphic Jump LocationTable 1. Characteristic of Included Studies
Table Graphic Jump LocationTable 2. Results of Included Studies

Mortality was assessed using multiple sources (Table 1), but one study did not detail the tools used to assess mortality outcomes.61Several studies reported crude mortality analysis (not shown). Univariate analyses and age- and sex-adjusted analyses showed significant mortality risk among patients with POAG in some studies.36,48,53,59,61These results, with the exception of those in the National Health Interview Survey, became insignificant in multivariate analyses. All studies adjusted for age and sex in the final analysis but differed in the additional covariates adjusted for. A detailed list of confounders adjusted for is outlined in Table 1.

Several studies listed estimates for mortality by cardiovascular disease,36,37,5254cancer,36,37,53or stroke.36,53In the Blue Mountains Eye Study,52stratified analysis demonstrated increased cardiovascular mortality risk in patients previously diagnosed with glaucoma, but not in those who were newly diagnosed. There was an insignificant increase in cardiovascular mortality for the POAG group as a whole. Table 3lists the relative risks for cardiovascular mortality and POAG used in the subgroup analysis. In the Framingham Study,36the proportions of death by coronary artery disease and cancer were similar in the cases and controls. The authors, however, found a significant difference in the proportion of cerebrovascular accidents.

Table Graphic Jump LocationTable 3. Results of Subgroup Analysis
SUMMARY ESTIMATES

There was no relationship between POAG and all-cause mortality in the primary pooled analysis (RR, 1.13; 95% CI, 0.97-1.31). A forest plot summarizing the results of the component studies and combined estimate is provided in Figure 2. Only 7 studies with physician diagnosis of POAG were included in secondary analysis (Figure 3). This estimated a smaller insignificant risk (RR, 1.02; 95% CI, 0.90-1.16). A Qtest for heterogeneity was significant in the primary analysis (P = .04), but insignificant for the secondary analysis (P = .41). The I2statistic failed to show significant heterogeneity in both primary and secondary analyses.

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Figure 2.

Forest plot for primary analysis. The relative risk for primary open-angle glaucoma and all-cause mortality with 95% confidence intervals for each study and pooled analysis from a random-effects model are depicted on a logarithmic scale. The size of each square is proportional to the study's weight. The lateral points of the diamond provide the confidence interval for the combined estimate.

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Figure 3.

Forest plot for secondary analysis. The relative risk for primary open-angle glaucoma and all-cause mortality with 95% confidence intervals for each study and pooled analysis for 7 of the 9 studies are depicted on a logarithmic scale. The size of each square is proportional to the study's weight. The lateral points of the diamond provide the confidence interval for the combined estimate.

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A meta-regression conducted to assess heterogeneity across mean follow-up time, age, or sex was not statistically significant (data not shown). A meta-regression across diabetes status failed to demonstrate significant results (P = .94). Subgroup analysis on cardiovascular mortality estimated a marginally significant increased risk with a RR of 1.20 (95% CI, 1.00-1.43; P = .05). This estimate was attenuated in a sensitivity analysis, removing the study with patients with self- or proxy-reported glaucoma (RR, 1.12; 95% CI, 0.87-1.46).37Forest plots of the subgroup analyses are provided in Figure 4and Figure 5.

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Figure 4.

Forest plot for subgroup analysis of cardiovascular mortality. The relative risk for primary open-angle glaucoma and cardiovascular mortality with 95% confidence intervals for each study and pooled analysis of the 4 studies are depicted on a logarithmic scale. The size of each square is proportional to the study's weight. The lateral points of the diamond provide the confidence interval for the combined estimate.

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Place holder to copy figure label and caption
Figure 5.

Forest plot for sensitivity analysis of cardiovascular mortality. Excluding the National Health Survey, the relative risks with 95% confidence intervals for each study and pooled analysis are depicted on a logarithmic scale. The size of each square is proportional to the study's weight. The lateral points of the diamond provide the confidence interval for the combined estimate.

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The Begg test failed to demonstrate publication bias. Furthermore, the Egger plot and the Begg funnel plot (Figure 6) failed to show significant signs of publication bias with no signs of asymmetry.

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Figure 6.

Begg funnel plot assessing for publication bias in the primary analysis. The relative risks and standard errors are on a logarithmic scale and presented with pseudo–95% confidence intervals.

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In this systematic literature review, we did not find an association between POAG and risk of all-cause mortality. All studies (with the exception of the National Health Interview Survey37) that contributed to the pooled estimate of the relationship between POAG and all-cause mortality reported insignificant results. Four of the 9 studies with moderate weighting described fairly tight CIs around the estimate of the effect and probably had the biggest influence on the combined result.5254,60Three studies that had broad CIs for the estimate of the effect carried less weight than the other studies.48,59,61

In our analysis, meta-regression did not detect heterogeneity by age, sex, or follow-up time, although we were likely limited by the effective range of each covariate. Studies tended to be similar in the distribution of these factors. Many studies did not report the distribution of participants by ethnicity, limiting inclusion of this attribute in the meta-regression. The Barbados Eye Study was conducted in a population predominately of African descent,54while the Beaver Dam Eye Study53comprised mostly white persons of European descent. The Beijing Eye Study61included Asian participants from rural communities in the south of Beijing. Ethnicity could introduce variability when pooling study estimates. Nonetheless, we failed to find significant heterogeneity in the secondary analysis. A meta-regression on the 3 studies with information regarding diabetes status in the glaucoma population did not demonstrate any heterogeneity. Caution must be exercised in interpreting a meta-regression on such a small sample because it may fail to provide sufficient power in analysis.

The relationship between POAG and cardiovascular mortality is of particular interest. In the Blue Mountains Eye Study,52the authors found an increased risk of cardiovascular mortality in patients previously diagnosed with POAG. This risk was primarily seen in patients with POAG who were taking timolol. In the Barbados Eye Study,54the authors also found a positive association between mortality and previously-treated POAG that was not statistically significant (P = .07). This relationship became stronger among subjects treated with timolol (P = .04). In our study, a pooled analysis demonstrated a marginally statistically significant association between POAG and cardiovascular mortality. Not surprisingly, this result was attenuated and insignificant when the largest study published by Lee et al (National Health Interview Survey)37was excluded. Our analysis was limited to few studies, and issues of reporting bias in the National Health Interview Survey should be considered during interpretation. Also, even if a positive relation between POAG and cardiovascular mortality exists, one must consider that this relationship may be owing to the side effects of glaucoma medications (as suggested in the Blue Mountains Eye Study52and the Barbados Eye Study54) or the adverse effects of systemic medications used to treat cardiovascular disease.

Given the paucity of research in POAG incidence, incident estimates are typically derived from prevalence data.62,63Deriving incidence estimates from prevalence data are based on the assumption that mortality in patients with POAG is similar to that in the general population. Our study supports this assumption.

This study is useful because prior epidemiologic research in this area had little power to reject the null hypothesis of no association between POAG and mortality. A limitation in the meta-analysis of observational studies is that residual sources of bias or confounding in the original studies may exist in the pooled analysis. In the pooled analysis, the fully-adjusted estimates were aggregated to account for known confounders such as age and sex. Although several studies sampled from predominantly ethnically uniform populations,53,54,61only 1 of the remaining studies adjusted for ethnicity, an important risk factor for POAG,64in the multivariate analysis.37Furthermore, the studies included in the pooled estimate of the relationship between POAG and mortality did not completely account for blood pressure, body mass index, and diabetes mellitus status, attributes known to independently influence mortality (Table 1).3,4,9,10,1922

Disease misclassification is another potential source of bias that may alter the relationship between POAG and mortality. Inconsistent diagnostic criteria may have underestimated or overestimated the sample size of patients with POAG. Evidence suggests that subtle changes in diagnostic standards affect the estimated prevalence of POAG.65It is difficult to estimate the direction and magnitude of this bias in our pooled analysis. In the secondary analysis, all studies used qualitative and/or quantitative criteria for glaucoma diagnosis. Qualitative measures such as pathological thinning of the neuroretinal rim introduce the potential of interreviewer variability. Quantitative measures such as the assessment of cup-to-disc ratio, may introduce misclassification by arbitrary cutoff points for the categorization of abnormal or normal. There is no reason to assume that any source of misclassification would be differential across those who died or survived. If the misclassification is truly nondifferential, then the effect estimates of individual studies are likely to be attenuated toward the null. Several studies described the use of physician panels to determine diagnosis or the use of consecutive test results, potentially limiting this source of misclassification.36,5961

We did not find any signs of publication bias. We found limited heterogeneity in primary analysis that was no longer observable in secondary analysis. Interstudy variability could potentially introduce heterogeneity and limit the effectiveness of pooled analysis to estimate associations. Although there was no uniform diagnostic criterion for glaucoma across aggregated studies, there was overlap in diagnostic criteria, including both quantitative and qualitative measures. All of the studies included were published in 1990s and later, and the design and analysis characteristics were similar across studies.

Our meta-analysis did not demonstrate an association between POAG and all-cause mortality. Although we did not find an association in a subgroup analysis of cardiovascular mortality, this study highlights the importance of evaluating specific causes of mortality. These data do not support the notion that POAG is a disease consisting of a sick eye in a body predisposed to excess mortality. This review, however, does not exclude the possibility that POAG is part of an underlying systemic process with subtle manifestations that do not necessarily lead to premature death.

Correspondence: Louis R. Pasquale, MD, Massachusetts Eye and Ear Infirmary, 243 Charles St, Boston, MA 02114 (Louis_Pasquale@meei.harvard.edu).

Submitted for Publication: June 9, 2008; final revision received October 2, 2008; accepted October 20, 2008.

Author Contributions: Ms M. Akbari had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Additional Contributions: Harry A. Quigley, MD, A. Edward Maumenee Professor, Ophthalmology, Wilmer Institute, Johns Hopkins University School of Medicine; and Michael D. Knudtson, Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health (grant EY06594 from the National Institutes of Health).

Financial Disclosure: None reported.

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Tournier  MMoride  YDucruet  TMoshyk  ARochon  S Depression and mortality in the visually-impaired, community-dwelling, elderly population of Quebec [published online ahead of print September 21, 2007]. Acta Ophthalmol 2008;86 (2) 196- 201
PubMed Link to Article
Higgins  JPThompson  SG Quantifying heterogeneity in a meta-analysis. Stat Med 2002;21 (11) 1539- 1558
PubMed Link to Article
Lee  AJWang  JJKifley  AMitchell  P Open-angle glaucoma and cardiovascular mortality: the Blue Mountains Eye Study. Ophthalmology 2006;113 (7) 1069- 1076
PubMed Link to Article
Knudtson  MDKlein  BEKlein  R Age-related eye disease, visual impairment, and survival: the Beaver Dam Eye Study. Arch Ophthalmol 2006;124 (2) 243- 249
PubMed Link to Article
Wu  SYNemesure  BHennis  ASchachat  APHyman  LLeske  MC Open-angle glaucoma and mortality: the Barbados Eye Studies. Arch Ophthalmol 2008;126 (3) 365- 370
PubMed Link to Article
Bengtsson  B Survival of elderly ophthalmic out-patients. Acta Ophthalmol (Copenh) 1984;62 (5) 725- 730
PubMed Link to Article
Bennett  G Mortality rates in glaucomatous subjects. AMA Arch Ophthalmol 1955;54 (5) 637- 640
Link to Article
Belloc  NB Expectation of life for persons with glaucoma. J Chronic Dis 1963;16163- 171
PubMed Link to Article
Thorburn  WLindblom  B Survival time among patients with glaucomatous visual field defects. Acta Ophthalmol (Copenh) 1983;61 (4) 728- 730
PubMed Link to Article
McCarty  CANanjan  MBTaylor  HR Vision impairment predicts 5 year mortality. Br J Ophthalmol 2001;85 (3) 322- 326
PubMed Link to Article
Grødum  KHeijl  ABengtsson  B Glaucoma and mortality. Graefes Arch Clin Exp Ophthalmol 2004;242 (5) 397- 401
PubMed Link to Article
Xu  LWang  YXJonas  JB Glaucoma and mortality in the Beijing Eye Study. Eye 2008;22 (3) 434- 438
PubMed Link to Article
Leske  MCEderer  FPodgor  M Estimating incidence from age-specific prevalence in glaucoma. Am J Epidemiol 1981;113 (5) 606- 613
PubMed
Quigley  HAVitale  S Models of open-angle glaucoma prevalence and incidence in the United States. Invest Ophthalmol Vis Sci 1997;38 (1) 83- 91
PubMed
Tielsch  JMSommer  AKatz  JRoyall  RMQuigley  HAJavitt  J Racial variations in the prevalence of primary open-angle glaucoma: the Baltimore Eye Survey. JAMA 1991;266 (3) 369- 374
PubMed Link to Article
Wolfs  RCBorger  PHRamrattan  RS  et al.  Changing views on open-angle glaucoma: definitions and prevalences: the Rotterdam Study. Invest Ophthalmol Vis Sci 2000;41 (11) 3309- 3321
PubMed

Figures

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Figure 1.

Search and study selection process.

Graphic Jump Location
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Figure 2.

Forest plot for primary analysis. The relative risk for primary open-angle glaucoma and all-cause mortality with 95% confidence intervals for each study and pooled analysis from a random-effects model are depicted on a logarithmic scale. The size of each square is proportional to the study's weight. The lateral points of the diamond provide the confidence interval for the combined estimate.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.

Forest plot for secondary analysis. The relative risk for primary open-angle glaucoma and all-cause mortality with 95% confidence intervals for each study and pooled analysis for 7 of the 9 studies are depicted on a logarithmic scale. The size of each square is proportional to the study's weight. The lateral points of the diamond provide the confidence interval for the combined estimate.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 4.

Forest plot for subgroup analysis of cardiovascular mortality. The relative risk for primary open-angle glaucoma and cardiovascular mortality with 95% confidence intervals for each study and pooled analysis of the 4 studies are depicted on a logarithmic scale. The size of each square is proportional to the study's weight. The lateral points of the diamond provide the confidence interval for the combined estimate.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 5.

Forest plot for sensitivity analysis of cardiovascular mortality. Excluding the National Health Survey, the relative risks with 95% confidence intervals for each study and pooled analysis are depicted on a logarithmic scale. The size of each square is proportional to the study's weight. The lateral points of the diamond provide the confidence interval for the combined estimate.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 6.

Begg funnel plot assessing for publication bias in the primary analysis. The relative risks and standard errors are on a logarithmic scale and presented with pseudo–95% confidence intervals.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Characteristic of Included Studies
Table Graphic Jump LocationTable 2. Results of Included Studies
Table Graphic Jump LocationTable 3. Results of Subgroup Analysis

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Tournier  MMoride  YDucruet  TMoshyk  ARochon  S Depression and mortality in the visually-impaired, community-dwelling, elderly population of Quebec [published online ahead of print September 21, 2007]. Acta Ophthalmol 2008;86 (2) 196- 201
PubMed Link to Article
Higgins  JPThompson  SG Quantifying heterogeneity in a meta-analysis. Stat Med 2002;21 (11) 1539- 1558
PubMed Link to Article
Lee  AJWang  JJKifley  AMitchell  P Open-angle glaucoma and cardiovascular mortality: the Blue Mountains Eye Study. Ophthalmology 2006;113 (7) 1069- 1076
PubMed Link to Article
Knudtson  MDKlein  BEKlein  R Age-related eye disease, visual impairment, and survival: the Beaver Dam Eye Study. Arch Ophthalmol 2006;124 (2) 243- 249
PubMed Link to Article
Wu  SYNemesure  BHennis  ASchachat  APHyman  LLeske  MC Open-angle glaucoma and mortality: the Barbados Eye Studies. Arch Ophthalmol 2008;126 (3) 365- 370
PubMed Link to Article
Bengtsson  B Survival of elderly ophthalmic out-patients. Acta Ophthalmol (Copenh) 1984;62 (5) 725- 730
PubMed Link to Article
Bennett  G Mortality rates in glaucomatous subjects. AMA Arch Ophthalmol 1955;54 (5) 637- 640
Link to Article
Belloc  NB Expectation of life for persons with glaucoma. J Chronic Dis 1963;16163- 171
PubMed Link to Article
Thorburn  WLindblom  B Survival time among patients with glaucomatous visual field defects. Acta Ophthalmol (Copenh) 1983;61 (4) 728- 730
PubMed Link to Article
McCarty  CANanjan  MBTaylor  HR Vision impairment predicts 5 year mortality. Br J Ophthalmol 2001;85 (3) 322- 326
PubMed Link to Article
Grødum  KHeijl  ABengtsson  B Glaucoma and mortality. Graefes Arch Clin Exp Ophthalmol 2004;242 (5) 397- 401
PubMed Link to Article
Xu  LWang  YXJonas  JB Glaucoma and mortality in the Beijing Eye Study. Eye 2008;22 (3) 434- 438
PubMed Link to Article
Leske  MCEderer  FPodgor  M Estimating incidence from age-specific prevalence in glaucoma. Am J Epidemiol 1981;113 (5) 606- 613
PubMed
Quigley  HAVitale  S Models of open-angle glaucoma prevalence and incidence in the United States. Invest Ophthalmol Vis Sci 1997;38 (1) 83- 91
PubMed
Tielsch  JMSommer  AKatz  JRoyall  RMQuigley  HAJavitt  J Racial variations in the prevalence of primary open-angle glaucoma: the Baltimore Eye Survey. JAMA 1991;266 (3) 369- 374
PubMed Link to Article
Wolfs  RCBorger  PHRamrattan  RS  et al.  Changing views on open-angle glaucoma: definitions and prevalences: the Rotterdam Study. Invest Ophthalmol Vis Sci 2000;41 (11) 3309- 3321
PubMed

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