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Subspecialties Glaucoma, Retina

Advancing Glaucoma Care

Rishikesh Gandhewar (Credit: Headshot supplied by author)

William Osler paved the path of patient-centered care; we now leap towards personalized medicine. Patient-centered medicine is an integral philosophy of contemporary medical practices. Osler – a Canadian-born physician and one of the founders of Johns Hopkins Hospital – is credited with its early conception by emphasizing the importance of physicians caring more for the individual patient than for the disease (1). In the present day, this philosophy translates into active patient involvement in their treatment, with management options tailored accordingly. And yet, evolving medical technologies promise further optimization – most prominently through the burgeoning field of personalized medicine. Personalized (or precision) medicine allows us to integrate patient choices with robust genetic, molecular, and environmental data to generate a truly individualized treatment regimen. Though the realization of such a utopia is laudable, it is not only within reach but, in certain cases, increasingly necessary.

Glaucoma is a chronic debilitating condition and remains the leading cause of irreversible blindness worldwide (2). Despite recent advances, concerted efforts are needed to improve patient outcomes. A recent Lancet seminar (3) underscored the imperative for personalized treatment in glaucoma, owing to its diverse pathophysiology, heterogenous manifestation, and emergent myriad treatment options. Often termed the “silent thief of sight,” glaucoma manifests asymptomatically and is increasingly being identified through routine screening by optometrists and opticians. Consequently, patients may receive a diagnosis at any point during the disease course, ranging from asymptomatic detection to late-stage irreversible sight loss. It’s clear that accurate prediction of the disease state, progression, and associated risks is crucial to tailor management effectively.

Currently, intraocular pressure (IOP) remains the only widely accepted modifiable risk factor for disease progression, so it is the target to which all treatment options are directed (3,4). However, many patients may progress despite normal pressures, prompting the need for further predictive markers through genetic profiling and therapy (3,4). Presently, when considering management, an array of pharmacological, laser, and surgical options must be navigated, each with specific benefits and limitations. This potential decision paralysis has been made worse through the innovation of minimally invasive glaucoma surgeries (MIGS), which offer the potential of periods of drop-free care. It is clear that patient-specific modeling would greatly help both clinicians and their patients navigate this complex condition.

Personalized medicine operates on three foundational pillars: genetics, big data, and artificial intelligence (AI) (5), each playing a pivotal role in glaucoma. Some 542 genes have been associated with open-angle glaucoma, dubbed the “POAGome,” exemplifying the varied disease pathophysiology (6). The majority of genes are implicated in inflammation and senescence and should be considered in the context of ethnic variations and environmental modification, through epigenetics (6). This genetic profiling is ever more relevant when addressing diverse populations and environments, underscoring initiatives such as Australia’s Genetics of Glaucoma Study (GOGS), one of the largest genetic studies of glaucoma worldwide (7). Such endeavors will be crucial in the pursuit of genetic risk profiling.

In addition to risk stratification, treatment is equally pertinent. A notable avenue of benefit lies in pharmacogenomics, a potent tool aimed at predicting individual responses to specific medications. For instance, varied responses to latanoprost have been associated with genetic polymorphisms associated with seven different genes (8). Looking ahead, the pursuit of neuroprotective gene therapies in an intraocular pressure (IOP)-independent manner stands as a promising goal in the quest for more effective and tailored interventions.

The dynamic interplay between big data and AI continues to transform the landscape of ophthalmology. Serial high-resolution imaging coupled with data-rich electronic health records provide an extensive repository for machine learning and deep learning technologies to develop predictions. Several assistive technologies, primarily rooted in OCT scans and visual field measurements, have emerged; however, the absence of rigorous diagnostic and progression definitions has resulted in heterogeneous data (9). Consequently, no autonomous AI models specific to glaucoma have secured FDA approval thus far (9).

Future advancements in predicting individual disease trajectory, patient outcomes, and treatment responses holds the promise of optimizing personalized treatment options. Pioneering efforts, exemplified by the work of Giovanni Montesano at Moorfields Eye Hospital, aim to map clinical trials and real-world outcomes to individuals. Such research is vital in data refinement and subsequent model enhancement, earning recognition through research awards from Glaucoma UK and The Royal College of Ophthalmologists (10).

Despite the considerable promise that personalized medicine holds, certain challenges that extend beyond the aforementioned complexities must be acknowledged. Glaucoma management grapples with issues of therapeutic intolerance and suboptimal adherence. Treatments, such as MIGS, are novel but have a limited evidence base, with variation in surgeon experience, availability, and affordability. Moreover, with improving detection, patient desired outcomes are a balance of treatment burden and disease progression (11). Precision models built upon these limitations may prove inaccurate predictors, outdated predictors, or predict outcomes that are not a priority to the individual.

Overall, personalized glaucoma therapy presents an immense opportunity to tailor treatment with increased potential efficacy for the individual. However, precision models must be evidence based, diligently developed, and, most importantly, created with the patient as the focal point. It is essential we keep Osler’s essence at the forefront – treating the patient, not just the disease.

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  1. J. Cordova, “The ‘good’ physician: Oslerian aphorisms in the 21st century,” Baylor University Medical Center Proceedings, 34, 325.
  2. RRA Bourne et al., “Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: The Right to Sight: An analysis for the Global Burden of Disease Study, “The Lancet Global Health,” 9, e144 (2021).
  3. H Jayaram et al., “Glaucoma: now and beyond,” The Lancet, 402, 1788–1801.
  4. SD Vold, “Personalized Glaucoma Care,” Glaucoma Today (Nov/Dec/ 2014).
  5. G Sunaric Megevand, AM Bron, “Personalizing surgical treatments for glaucoma patients,” Progress in Retinal and Eye Research, 81, 100879 (2021).
  6. ID Danford et al., “Characterizing the ‘POAGome’: A bioinformatics-driven approach to primary open-angle glaucoma,” Progress in Retinal and Eye Research, 58, 89 (2017).
  7. P Gharahkhani et al., “Study profile: the Genetics of Glaucoma Study,” BMJ Open, 13 (2023).
  8. L Zhou et al., “Clinical pharmacology and pharmacogenetics of prostaglandin analogues in glaucoma,” Frontiers in Pharmacology, 13, 1015338 (2022).
  9. S Yousefi, “Clinical Applications of Artificial Intelligence in Glaucoma,” Journal of Ophthalmic and Vision Research, 18, 97 (2023).
  10. Association of British Dispensing Opticians. Funding for glaucoma care project.
  11. A Safitri et al., “Treatment expectations in glaucoma: what matters most to patients?” Eye, 37, 3446 (2023).
About the Author
Rishikesh Gandhewar

Rishikesh Gandhewar is an Academic Foundation Year 2 Doctor at Imperial College NHS Trust, Imperial College London.

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