Risk prediction in primary angle closure suspects: current perspectives

Primary angle closure glaucoma (PACG) is a leading cause of irreversible blindness worldwide and is projected to affect more than 32 million individuals by 2040 (1). Primary angle closure suspect (PACS) is defined by the presence of two or more quadrants in which the trabecular meshwork is not visible on gonioscopy (2). In primary angle closure (PAC), contact between the peripheral iris and the trabecular meshwork leads to impaired aqueous outflow, elevated intraocular pressure, and, ultimately, glaucomatous optic neuropathy.

Laser peripheral iridotomy (LPI) and lens extraction are known to widen the anterior chamber angle and may delay or prevent progression from PACS to PAC and PACG (3-5). However, there are currently no consensus guidelines supporting routine prophylactic treatment in PACS (6,7). The Zhongshan Angle Closure Prevention (ZAP) trial demonstrated that the risk of progression from untreated PACS to PAC was less than 1% per eye-year, leading to recommendations against widespread prophylactic LPI. Nonetheless, a subset of patients ultimately progresses to PAC or acute angle closure, often with substantial visual morbidity, underscoring the importance of identifying individuals at higher risk.

Traditionally, biometric risk factors associated with angle closure progression include anterior chamber depth, axial length, lens thickness, and baseline angle width (8-10). Although these parameters provide clinically relevant prognostic information, their predictive performance has been only moderate, with concordance indices ranging from 0.48 to 0.68. This limitation likely reflects the dynamic nature of anterior segment anatomy and age-related structural changes, such as progressive lens thickening and anteriorization, which increase susceptibility to angle closure (8,11).

We have read with interest the study published by Hong et al. That represents an important conceptual advance by demonstrating that short-term longitudinal changes in ocular biometrics provide independent prognostic value beyond static baseline measurements. By focusing on 18-month changes in lens vault (LV) and trabecular-iris space area at 750 µm (TISA750), the authors move toward a more dynamic risk stratification framework that better reflects the underlying pathophysiology of angle closure (12).

The study also highlights the growing clinical relevance of anterior segment optical coherence tomography (AS-OCT), which allows objective and reproducible quantification of subtle anatomic changes over time and supports more refined clinical decision-making in patients with PACS (13).

The central role of the crystalline lens in angle-closure pathophysiology is further reinforced. Short-term increases in LV and reductions in TISA750 were associated with a higher risk of progression, reflecting progressive lens anteriorization and angle crowding. Although intuitive, these associations had not been formally tested in earlier ZAP analyses, which primarily focused on baseline biometric data (9).

It is also important to recognize that angle-closure disease is not exclusively driven by pupillary block or lens-related mechanisms. Plateau iris configuration, characterized by anteriorly positioned ciliary processes leading to angle crowding despite a relatively deep central anterior chamber, has been reported in up to one-third of eyes with angle closure after laser iridotomy (14) and may be underdiagnosed when relying solely on anterior segment OCT imaging. In parallel, increasing evidence supports a role for choroidal expansion in angle closure pathophysiology, whereby increased choroidal thickness or uveal effusion contributes to anterior displacement of the lens-iris diaphragm and secondary angle narrowing (15). These posterior segment-related mechanisms are not captured by standard anterior segment biometric parameters and require complementary imaging modalities such as ultrasound biomicroscopy or enhanced-depth imaging OCT. Consequently, predictive models based predominantly on anterior segment measurements may not fully reflect the heterogeneity of angle-closure mechanisms across individuals.

Beyond LV, the peripheral iris may contribute to angle closure risk through its dynamic behavior during physiologic or pharmacologic mydriasis, which can increase iridotrabecular apposition. In the ZAP Trial, reduced iris-volume loss from light to dark—and paradoxical volume increase in a higher proportion of progressors—was independently associated with progression from PACS to PAC (16). In contrast, baseline peripheral iris thickness and cross-sectional area were not consistently greater in progressors, suggesting that static iris measurements alone may be insufficient. Although iris dynamic behavior reflects an important pathophysiological mechanism, its incremental predictive value appears limited once established angle parameters are incorporated, indicating that it may act more as an upstream contributor than as an independent prognostic marker.

Not all angle parameters behaved similarly. While baseline angle opening distance at 500 µm (AOD500) retained prognostic significance, its longitudinal change was not independently predictive (9). In contrast, longitudinal change in TISA750 emerged as a robust marker of progression, suggesting that area-based metrics may better capture clinically meaningful remodeling of the angle recess.

Another notable finding is the diminished independent contribution of chronological age once dynamic biometric variables are incorporated into multivariable models. This observation suggests that biological aging of the anterior segment may be more accurately reflected by serial imaging metrics than by demographic age alone.

The methodological choice of an 18-month interval is well justified. Prior studies indicate that early anatomic changes tend to follow relatively linear trajectories, whereas longer follow-up periods are influenced by nonlinear processes such as age-related pupillary constriction (11). Focusing on this intermediate window likely reduces confounding and improves interpretability.

Several limitations merit consideration. Exclusion of eyes with visually significant cataract in both the ZAP and ANA-LIS studies may have biased the cohorts toward individuals with more stable lens biometry, potentially underestimating progression rates. The predominance of East Asian participants may also limit generalizability to other populations. Additional constraints include the moderate predictive performance of the proposed models, the limited number of progression events, and the exclusive use of horizontal scans.

An additional and clinically relevant limitation concerns model reproducibility and external validation. The predictive framework relies on biometric parameters derived from a proprietary, non-publicly available segmentation software (the Zhongshan Angle Assessment Program) applied to time-domain AS-OCT images acquired with the Visante system. This restricts transparency and prevents independent verification of how key predictors are defined, extracted, and quality-controlled. Importantly, peer-reviewed interdevice comparisons have demonstrated that angle metrics obtained with Visante-based software and swept-source platforms such as CASIA II show limited agreement and should not be used interchangeably without device-specific recalibration (17). In contrast, CASIA II enables highly repeatable quantitative assessment using standardized, high-density imaging protocols and supports serial monitoring of parameters central to angle-closure pathophysiology, including TISA and lens-related metrics (18). Differences between software ecosystems underscore that matching variable names does not ensure equivalence in computation. Consequently, predictive models developed using closed, device-specific feature extraction may have limited portability to widely used swept-source systems, emphasizing the need for transparent, cross-platform definitions or openly shareable algorithms to facilitate robust replication and clinical adoption.

Beyond software limitations, the imaging strategy itself warrants consideration. Although Visante AS-OCT allows acquisition of individual radial scans, the analysis was restricted to the horizontal meridian, without systematic multi-meridian or circumferential assessment. Given that angle narrowing often develops earlier or more prominently in superior and inferior quadrants, sectoral progression outside the horizontal plane may have been underestimated. In this context, swept-source platforms such as CASIA II, which enable rapid, standardized 360° imaging, may provide a more comprehensive characterization of angle dynamics and further refine risk stratification.

Looking forward, integration of dynamic biometric data with emerging analytical approaches offers substantial opportunities for innovation. Machine learning methods may enable the incorporation of multimodal imaging, genetic susceptibility markers, and longitudinal clinical data into comprehensive predictive models, allowing more precise identification of high-risk individuals and earlier preventive interventions.

Advances in AS-OCT technology further support longitudinal monitoring in routine clinical practice (19,20), particularly in resource-limited settings where early identification of high-risk PACS eyes may yield significant public health benefits.

In summary, the work by Hong et al. (12) underscores the value of incorporating short-term dynamic anatomic changes into risk stratification models for PACS. Continued efforts toward transparent methodology, external validation, and technological integration are essential to advance preventive, personalized, and data-driven care in angle-closure disease.

Acknowledgments

None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Annals of Translational Medicine. The article has undergone external peer review.

Peer Review File: Available at https://atm.amegroups.com/article/view/10.21037/atm-2026-1-0023/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://atm.amegroups.com/article/view/10.21037/atm-2026-1-0023/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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