Glaucoma Service, Moorfields Eye Hospital NHS Foundation Trust.
Ocular Informatics Group, Population and Data Sciences Research Theme, University College London Institute of Ophthalmology.
J Glaucoma. 2024 Aug 1;33(Suppl 1):S15-S20. doi: 10.1097/IJG.0000000000002426. Epub 2024 Aug 19.
While glaucoma is a leading cause of irreversible vision loss, it presents technical challenges in the design and implementation of screening. New technologies such as PRS and AI offer potential improvements in our ability to identify people at high risk of sight loss from glaucoma and may improve the viability of screening for this important disease.
To review the current evidence and concepts around screening for glaucoma.
METHODS/RESULTS: A group of glaucoma-focused clinician scientists drew on knowledge and experience around glaucoma, its etiology, and the options for screening. Glaucoma is a chronic progressive optic neuropathy affecting around 76 million individuals worldwide and is the leading cause of irreversible blindness globally. Early stages of the disease are asymptomatic meaning a substantial proportion of cases remain undiagnosed. Early detection and timely intervention reduce the risk of glaucoma-related visual morbidity. However, imperfect tests and a relatively low prevalence currently limit the viability of population-based screening approaches. The diagnostic yield of opportunistic screening strategies, relying on the identification of disease during unrelated health care encounters, such as cataract clinics and diabetic retinopathy screening programs, focusing on older people and/or those with a family history, are hindered by a large number of false-positive and false-negative results. Polygenic risk scores (PRS) offer personalized risk assessment for adult-onset glaucoma. In addition, artificial intelligence (AI) algorithms have shown impressive performance, comparable to expert humans, in discriminating between potentially glaucomatous and non-glaucomatous eyes. These emerging technologies may offer a meaningful improvement in diagnostic yield in glaucoma screening.
While glaucoma is a leading cause of irreversible vision loss, it presents technical challenges in the design and implementation of screening. New technologies such as PRS and AI offer potential improvements in our ability to identify people at high risk of sight loss from glaucoma and may improve the viability of screening for this important disease.
青光眼是导致不可逆视力丧失的主要原因,但在筛查的设计和实施方面存在技术挑战。PRS 和人工智能等新技术可能会提高我们识别高风险青光眼致盲人群的能力,并可能提高这种重要疾病筛查的可行性。
回顾青光眼筛查的当前证据和概念。
方法/结果:一组专注于青光眼的临床科学家利用了他们在青光眼及其病因以及筛查选择方面的知识和经验。青光眼是一种影响全球约 7600 万人的慢性进行性视神经病变,是全球致盲的主要原因。该疾病的早期阶段无症状,这意味着很大一部分病例未被诊断出来。早期发现和及时干预可降低青光眼相关视觉发病率的风险。但是,不完善的检测和相对较低的患病率目前限制了基于人群的筛查方法的可行性。依靠在白内障诊所和糖尿病视网膜病变筛查计划等与健康护理无关的情况下发现疾病的机会性筛查策略的诊断效果,重点关注老年人和/或有家族病史的人,受到大量假阳性和假阴性结果的阻碍。多基因风险评分 (PRS) 可针对成人发病型青光眼进行个性化风险评估。此外,人工智能 (AI) 算法在区分潜在青光眼和非青光眼眼中的表现可与专家人类相媲美。这些新兴技术可能会显著提高青光眼筛查的诊断效果。
虽然青光眼是导致不可逆视力丧失的主要原因,但在筛查的设计和实施方面存在技术挑战。PRS 和人工智能等新技术可能会提高我们识别高风险青光眼致盲人群的能力,并可能提高这种重要疾病筛查的可行性。