Recent meta-analyses demonstrate that individuals with hypertension are also more likely to have open-angle glaucoma (OAG), with a pooled relative risk of 1.16  and an odds ratio of 1.22 . However, the quality of evidence in available studies necessarily limits the quality of evidence provided by meta-analysis. In one of the two recent meta-analysis, only two out of 27 studies employed longitudinal designs, and in those two studies, the relative risk of OAG associated with hypertension was small (1.05) and not statistically significant . Furthermore, in the two longitudinal studies, one had a small sample size of about 3000 with a 9-year follow-up , and the other had a large sample size of more than 2 million, but hypertension and OAG were based solely on insurance claims data and it had a shorter, 6-year follow-up .
In this issue of Journal of Hypertension, Rim et al.  report the results of a study testing whether hypertension is a risk factor for the development of OAG. They leveraged a nationwide database of results from a general health screen linked with a nationwide health insurance claims database to study the incidence of OAG in more than 200 000 adults over an 11-year follow-up. The study by Rim et al.  strengthens the current quality of evidence in critical ways.
Due to the low prevalence of OAG, studies without a large sample size will have insufficient cases to yield precise estimates. Insurance claims databases provide the necessary sample sizes, yet are often limited by the quality of available information. Compared with health records, identification of hypertension from insurance claims yielded a sensitivity of 71–76%, depending on the algorithm used . The study by Rim et al.  advances on the previous, large, longitudinal study  by linking insurance claims with health screening data to identify hypertension based on the prescription of antihypertensive medication or high blood pressure measurements, capturing those who may have untreated hypertension. Estimates of the accuracy of insurance claims for identifying presence of OAG are not available. However, given the general concordance rates between health records and insurance claims, basing incidence of OAG on insurance claims along with medical records or biomarker measurements would strengthen future studies.
The observational nature of cohort studies renders them susceptible to confounding bias. Rim et al.  mitigated confounding bias by using propensity score matching  to select a sample matched on sociodemographic factors, the burden of comorbidity, and specific conditions that are comorbid with hypertension and risk factors for OAG (e.g. diabetes ). Propensity score matching does not eliminate the risk of bias due to confounding, but it can reduce the impact of bias to yield more accurate estimates of the effect of an exposure. Although use of propensity scores is not uncommon in cardiovascular research , the field would benefit from more studies following the example of Rim et al.  by carefully considering likely confounding factors and using propensity scores to adjust estimates.
In summary, results by Rim et al.  of a hazard ratio of 1.16 and relative risk of 1.18 point to substantially greater risk than results from the previous longitudinal studies with a pooled relative risk of 1.05 . Considering the large sample size, long follow-up period, high-quality assessment of hypertension and careful adjustment for plausible confounding factors, the results of the study by Rim et al.  provide some of the strongest evidence to date that hypertension is a risk factor for the development of OAG. Although their data are representative of South Korea, future research is needed that examines these effects in other populations and using health records or another measurement to identify the presence of OAG. Considering that both hypertension and diabetes emerged as risk factors for OAG [4,5], future studies may benefit from comparing the effects of commonly clustering risk factors individually and in combination, such as by calculating the presence/absence  or severity  of the metabolic syndrome.
The study by Rim et al.  highlights the value of linking nationwide databases of health screening with insurance claims databases. Such longitudinal, nationwide databases provide the infrastructure needed for high-quality, epidemiological research and facilitate studies on conditions with low incidence rates. Although logistical and policy hurdles exist, future work developing national research databases with electronic health records in addition to insurance claims will enable future epidemiological studies to better estimate the effects of exposure to risk factors and control for a wider array of potential confounding factors.
Conflicts of interest
The author declares no conflicts of interest.
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