Introduction

Primary angle closure glaucoma (PACG) in s a leading cause of irreversible blindness, affecting about 23 million people worldwide. By 2040, this number may rise to 32 million due to an increase in the aging population. [1-2]

A meta-analysis encompassing 23 population-based studies determined that the prevalence of blindness associated with PACG is 27.0%. [3-4] The loss of vision-particularly bilateral blindness-substantially diminishes quality of life, encompassing physical health, comfort, and overall well-being. Furthermore, blindness poses considerable challenges for the global economy. Therefore, it is essential to thoroughly investigate the underlying causes and risk factors of blindness related to treatable eye diseases, such as PACG, across different patient populations and normal individuals. The considerable visual impairment observed in primary angle-closure glaucoma (PACG) is primarily due to severely obstructed aqueous outflow and increased intraocular pressure (IOP), which lead to rapid and significant glaucomatous damage. Laser and surgical procedures are employed to alleviate angle closure, thereby effectively delaying or even preventing the onset of elevated IOP and primary angle-closure disease (PACD). [5]

In India, primary angle-closure glaucoma (PACG) usually affects between 0.5% and 4.3% of the population, with the southern parts of the country showing the highest prevalence. [6] Recent studies indicate that angle closure develops due to both anatomical and dynamic factors affecting different anterior segment structures. These include a smaller anterior chamber—its area, width, and volume-a thicker, more curved iris, and a greater lens vault. [7]

The purpose of this study was to compare anterior segment optical coherence tomography (AS-OCT) parameters of patients with various PACD subtypes at a tertiary care teaching hospital in the subcontinent to those found in the general population. It also investigated whether changes in lens-related biometric measurements increased the likelihood of developing acute angle-closure disease.

Material and Methods

A controlled study was conducted at three eye centers in northern India from Jan 2025 to Feb 2026, with approval from ethics committees. All patients provided written informed consent in compliance with the Declaration of Helsinki.

Patient selection

The study population comprised 170 individuals diagnosed with primary angle closure disease. Classification of PACD was performed based on the guidelines established by the International Society of Geographical & Epidemiological Ophthalmology (ISGEO). Of these participants, 50 were identified as primary angle closure suspects (PACS), 60 as primary angle closure (PAC), and 60 as primary angle closure glaucoma (PACG). The control group comprised 60 individuals matched for age and gender, all presenting with minor ocular conditions. Each subject exhibited a normal anterior chamber and had unremarkable findings on gonioscopy.

Patients exhibiting apposition or closure of the anterior chamber angle exceeding 270° in all three quadrants were enrolled in the study. Asymptomatic individuals were classified as primary angle-closure suspects (PACS). Patients presenting with elevated intraocular pressure (IOP) greater than 21 mmHg were categorized as having primary angle closure (PAC). [8]

Diagnostic criteria for PACG

PACG was diagnosed by identifying narrow angles according to Shaffer’s grading system, together with glaucomatous optic neuropathy (GON), defined as a vertical cup-to-disc ratio (CDR) of ≥0.7, CDR asymmetry >0.2, and/or focal notching, accompanied by visual field loss detected through static automated perimetry (SITA Standard algorithm, 24-2 test pattern, Humphrey Visual Field Analyzer III; Carl Zeiss Meditec, Dublin, CA). Diagnosis required that the Glaucoma Hemifield Test yield results outside normal limits; identification of a cluster comprising three or more contiguous, non-edge points on the pattern deviation plot—these did not cross the horizontal meridian and demonstrated a probability of less than 5% of being present in age-matched normals, including at least one point with a probability <1%. An abnormal pattern standard deviation (PSD) with a P value below 5% relative to healthy controls was also necessary, while meeting established test reliability standards (fixation losses <20%, false positives <33%, and/or false negatives <33%). The analysis additionally included the fellow eyes of the patients in this study.

Exclusion criteria:

Individuals with other types of glaucoma, eye conditions like microcornea, coloboma, or aniridia, age-related cataracts, previous eye surgeries (including cataract surgery), eye injuries, or additional ocular problems—including current infections—were excluded from the study. The study also did not include anyone who had received interventions for PACD, such as miotic therapies or laser peripheral iridotomy (YAG PI).

Ocular examination

Sociodemographic information was gathered from each patient, including their name, age, gender, medical history, and previous attacks. Comprehensive eye assessments followed: visual acuity was checked using Snellen’s chart, refraction measurements were taken and slit-lamp exams included van-Hericks and gonioscopy methods to look for acute angle-closure signs. Intraocular pressure was recorded via Goldmann Applanation tonometry. Gonioscopy used a Volk four-mirror lens to evaluate the anterior chamber angle according to Schaffer’s classification, applying minimal corneal pressure to detect subtle PACS cases. Additional tests—such as visual field evaluations and optic disk analysis—were performed to distinguish between PACG and PAC patients. These procedures are essential both for tracking disease progression and providing patient guidance.

Swept source OCT and A -scan

Swept source OCT is an emerging technology for IOL calculation. SS-OCT uses a tuneable light source with a beam splitter, directing one beam to the eye and another to a reference mirror. The reflected beams undergo Fourier transformation at a point detector to measure ocular dimensions. IOL Master700 applies a 1050 nm light source with 2,000 A scan/sec, capturing scan depth of 44 mm and axial resolution of 22 microns. Parameters measured included lens thickness (LT), lens vault (LV), axial length (AL), anterior chamber depth (ACD), and central corneal thickness (CCT). These values were used to calculate the lens AL factor and relative lens position (RLP). Figure 1 displays anterior segment linear parameters measured by SS-ASOCT.

Figure 1: Linear parameters of the anterior segment measured by swept-source anterior segment optical coherence tomography (SS-ASOCT).

The lens axial factor (LAF) was calculated by using the formula LAF = (LT/AL) × 10. The lens position was defined as the sum of ACD and one‑half LT, that is, (ACD + 1/2 LT). RLP was calculated by using the formula LP divided by AL. [9-10]

In swept-source OCT (SS-OCT), lens vault (LV) refers to the maximum vertical distance between the front tip of the crystalline lens and a straight line drawn between the two scleral spurs. This measurement serves as an important quantitative marker for evaluating how far the lens protrudes forward-a factor closely linked to the risk of angle closure. A higher LV value suggests an increased risk. [11]

Statistical Analysis

The data was collected in an Excel sheet and then exported to statistical software for further analysis. Statistical analyses were carried out using IBM SPSS Statistics version 30 (IBM Inc.). The normality of the data was assessed with the Shapiro-Wilk test. Data that followed a normal distribution were presented as mean ± standard deviation (SD). Outliers were detected by visually examining box plots. The association between two categorical variables was analyzed with Chi-square tests. Dichotomous variables were expressed as frequencies and percentages (%). A one-way ANOVA was performed to evaluate significant differences in mean test values across two or more continuous variables. Multivariate logistic regression was used to identify independent factors associated with the development of PACG, adjusting for confounders such as age and gender. Only factors found to be significant in univariate analysis (CCT, AL, LT, LV, ACD, LAF, RLP) were included in the model. To reduce the risk of type I errors, statistical significance was set at P < 0.05.

Results

Among 170 patients diagnosed with PACD, 50 were classified as primary angle closure suspects (PACS), 60 as primary angle closure (PAC), and 60 as primary angle closure glaucoma (PACG). The control group consisted of 60 age- and gender-matched subjects, all presenting with minor ocular conditions. Table 1 provides a detailed comparison of the demographic characteristics within the study population. The average ages are similar across groups, ranging from 61 to 64 years, with a predominance of females in each category. The uncorrected (UCVA) and best-corrected visual acuity (BCVA) are both poorer in the PACG group, indicating more severe vision impairment. Regarding refractive status, most patients in the PACS, PAC, and PACG groups exhibit hypermetropia, while emmetropia and myopia are more common among controls. Anterior chamber depth (ACD) follows a similar trend, being shallower in PACG and deeper in controls. Most parameters show statistically significant differences between groups, as reflected by the ANOVA P values, particularly for UCVA, refractive status, CCT, axial length, and ACD.

Table 2 presents the ocular biometric parameters of the study population. The data reveal a progressive increase in lens vault, lens thickness, and lens axial factor from PACS to PAC and PACG, while control eyes consistently show the lowest values for these parameters. Relative lens position, however, is slightly higher in PAC (6.34±0.6) and PACG (6.3±0.57) than in PACS (5.9±0.6) and controls (5.7±0.5). All comparisons report P values less than 0.001, indicating statistically significant differences among the groups for each parameter. This indicates that eyes with PACS, PAC, and especially PACG tend to have a thicker and more anteriorly positioned lens (higher lens vault and axial factor), which may contribute to the pathogenesis of angle closure. The statistically significant differences reinforce the hypothesis that lens characteristics play a crucial role in the development and progression of angle closure spectrum diseases compared to normal eyes.

Table 3 compares uncorrected visual acuity between PACD patients and controls. Each Log MAR value (0, 0.18, 0.3, 0.48, 0.6, and 1) is accompanied by the number and percentage of individuals in each group who fall within that acuity range. The data indicate that individuals in the PACG and PAC groups tend to have poorer uncorrected visual acuity compared to PACS and controls. Most controls have good UCVA (Log MAR 0.18), while PACG and PAC patients are clustered at higher (worse) Log MAR values (0.48 and 0.6). This pattern suggests a progressive decline in visual acuity from PACS to PAC to PACG. In contrast, the control group exhibits significantly better UCVA overall, with no members falling into the poorest vision categories. This underscores the impact of angle closure disease progression on uncorrected visual acuity.

Multiple Logistic regression

A binomial logistic regression was performed to ascertain the effects of CCT, AL, LT, LV, ACD, LAF, and RLP (after adjusting for age and gender) on the likelihood that participants have PACG. The logistic regression model was statistically significant, χ²(7) = 121.823, P < .0001. The model explained 78% (Nagelkerke R²) of the variance in PACG and correctly classified 90% of cases. Sensitivity was 97.5%, specificity was 85%, positive predictive value was 92.8% and negative predictive value was 94.4%. Of the seven predictor variables only three were statistically significant: ACD, LV and RLP (as shown in Table 4). Increased lens vault (Odds ratio=3.321), increasing RLP (OR=7.073), and lower AL (OR=5.90) were associated with an increased likelihood of exhibiting PACG.

Discussion

This cross-sectional study examined the biometric features of patients between different subtypes of PACD (PACS, PAC, and PACG) who visited the outpatient clinic of a tertiary care hospital in the northern part of the subcontinent. The objective was to determine whether variability in any lens-related biometric parameters contributed to an elevated risk of progression to angle-closure glaucoma. The study also aimed to identify independent risk factors have increased likelihood of progression to angle closure glaucoma. The present study found that Vision impairment was most severe in PACG patients, as shown by poor UCVA and BCVA scores. Hypermetropia was common in PACS, PAC, and PACG groups, while controls exhibited more emmetropia and myopia. PACG patients had the shallowest ACD; controls had the deepest. Significant differences (P < 0.001) were observed among groups for UCVA, refractive status, CCT, axial length, and ACD. Lens vault, thickness, and axial factor increased progressively from PACS to PAC to PACG, with controls showing the lowest values. Relative lens position was slightly higher in PAC and PACG. All parameters showed significant group differences (P < 0.001). Eyes with PACS, PAC, and especially PACG featured thicker, more anteriorly positioned lenses, supporting their role in angle closure pathogenesis. Disease progression correlated with declining visual acuity, with PACG and PAC patients exhibiting worse vision than PACS and controls. Multiple Logistic regression revealed that increased lens vault (Odds ratio=3.321), increasing RLP (OR=7.073), and lower AL (OR=5.90) were associated with an increased likelihood of exhibiting PACG.

Foster et al. classified angle closure disease into three types: primary angle closure suspect (PACS), primary angle closure (PAC), and primary angle closure glaucoma (PACG). [12] Primary angle closure glaucoma (PACG) is a serious ophthalmic disorder and constitutes a significant contributor to irreversible blindness worldwide. The global prevalence of PACG is currently estimated at approximately 23 million cases, with projections suggesting this number will rise to around 32 million by 2040 due to an aging population. [13]

Recent ASOCT research has identified anatomical factors associated with angle closure, including decreased anterior chamber area, width, and volume, increased iris thickness and curvature, and higher lens vault. With limited understanding of how these features differ among subtypes, this study used ASOCT to compare anterior segment measurements in patients at different stages of angle closure disease and to identify factors related to PAC.

This study demonstrated that hyperopia is associated with a higher risk of PACD. In every subgroup of angle-closure disease, the axial length (AL) was shorter, and patients diagnosed with PACG had the shortest AL-1.1 mm less than those who were only suspected of having the disease. ANOVA analysis showed a highly significant difference (P<0.001) in AL between various PACD subtypes. Although multiple studies have observed comparable outcomes for AL, Mohamed-Noor et al. and Razeghinejad et al. reported no significant differences in AL among PACD subtypes. [14-17]

Thapa et al. reported that each 1 mm decrease in axial length raises the odds of angle‑closure glaucoma (OR: 0.49; 95% CI: 0.36–0.67). [18] Our study confirmed this with logistic regression, showing that reduced AL was strongly associated with higher odds (OR=5.9, P<0.001) of developing PACG.

In the present study, PACG patients had a significantly higher vault than PACS and PAC groups (P<0.001). Elevated LV was strongly linked to PACD development (P < 0.01) on univariate analysis. LT and LV were positively correlated (r=0.575, P<0.001). A thicker lens with increased anterior vaulting may be a major factor in angle closure. Among PACD subtypes, PACG showed the greatest lens vault and multivariate analysis revealed that had significantly (P<0.001) higher odds (OR=3,32) of developing PACG. Elevated LV and LT increase the risk of angle closure by enhancing pupillary block, with lens forward movement especially affecting older adults, women, and certain ethnic groups. [19-20]

The study observed a significant variation in LAF among PACS, PAC, and PACG patients (P<0.001). Nevertheless, logistic regression analysis indicated that LAF was not associated with an increased risk of developing PAGC. Chakarbarti et al.'s research also noted a statistically significant difference in LAF between PACD subtypes and control groups; however, their study did not conduct regression analysis with adjustments. [21]

This study found that RLP was significantly more anterior in subjects with PACG, and a higher RLP increased the odds of PACG (OR=7.073, P<0.001). Chen et al. reported that PACG eyes with long AL had lower keratometry, longer ACD, and both LP and RLP located closer to the anterior. The proximity of RLP to the cornea may explain angle closure in eyes with long AL, even when ACD is long. [22]

Study Limitations

While this study provides valuable insights into lens-related biometric features across the spectrum of primary angle closure disease (PACD), several limitations should be acknowledged: The study took place at three tertiary care centres, which may restrict how widely its findings apply to other populations or regions. Because of the study's design (controlled study), it cannot establish cause-and-effect relationships or track changes in biometric parameters over time. Longitudinal research is needed to better understand how lens-related factors influence the development and progression of PACD. Selection bias: Recruiting participants directly from clinic attendees introduces potential selection bias, since these individuals may not reflect the broader population at risk for PACD. Lack of randomisation and masking: The absence of both randomisation and masking during recruitment and assessment may have resulted in observer bias affecting clinical and biometric measurements. Exclusion of treated cases: Patients who had already received treatment for PACD—such as laser iridotomy or medication—were omitted, leading to an incomplete picture of the disease that does not include more advanced or treated cases. Measurement variability: Even with advanced imaging techniques like swept-source OCT and A-scan, differences between and within operators, plus device limitations, could impact the reliability and consistency of biometric measurements. Confounding factors: Although the analysis adjusted for age and gender, other possible confounders—including systemic health conditions, medications, or genetic background—were not fully accounted for, which might have influenced the associations found in the study. A controlled study design was our strength.

In conclusion, this study highlights the significant role of lens-related biometric parameters—specifically, lens vault (LV), relative lens position (RLP), and axial length (AL)—in the development and progression of primary angle closure disease (PACD), including its subtypes: PACS, PAC, and PACG. Patients with PACD, especially those diagnosed with PACG, were found to have a thicker and more anteriorly positioned lens, as evidenced by higher LV and RLP values, and a shorter AL compared to controls. These anatomical differences were associated with an increased risk of angle closure and vision impairment, with the severity of visual loss progressing from PACS to PAC and being most pronounced in PACG.

Multivariate logistic regression confirmed that increased LV and RLP, along with reduced AL, were independently associated with a higher likelihood of PACG, even after adjusting for age and gender. These findings reinforce the importance of comprehensive anterior segment evaluation, including lens biometrics, in identifying individuals at risk for disease progression. The results suggest that early recognition and monitoring of lens-related parameters could facilitate timely intervention, potentially reducing the burden of irreversible blindness due to PACG. Further longitudinal and multicentric studies are recommended to validate these findings and to explore the impact of preventive strategies targeting lens anatomy in high-risk populations.

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