Shen Ru Yue, Zhang Yuqiao, Chen Li Jia, Cheung Carol Y, Liang Yuanbo, Tham Clement C, Chan Poemen P
Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China.
Lam Kin Chung, Jet King-Shing Ho Glaucoma Treatment and Research Centre, The Chinese University of Hong Kong, Hong Kong SAR, China.
Invest Ophthalmol Vis Sci. 2025 Sep 2;66(12):35. doi: 10.1167/iovs.66.12.35.
To synthesize and evaluate the quality of evidence from existing meta-analyses on ocular and systemic factors and biomarkers associated with primary glaucoma.
Systematic reviews with meta-analysis evaluating ocular and systemic factors or biomarkers of glaucoma were included. Searches of PubMed, Embase, and Cochrane Library were conducted from inception to June 25, 2023, without language restrictions. Two researchers independently conducted screening, data extraction, and quality appraisal. The summary effect size, 95% confidence interval, and 95% prediction interval were estimated by random-effect models. The between-study heterogeneity (I2), evidence of small-study effects, and evidence of excess significance bias were reported. The equivalent standardized mean differences or odds ratios were calculated from original study estimates.
Thirty-six systematic reviews and meta-analyses were included, examining 87 factors related to ocular biometrics, lifestyle habits, diets, ocular and systemic disorders, and biomarkers from ocular imaging, serum, plasma, and aqueous humor. Three ocular factors (intraocular pressure, myopia, and corneal hysteresis) and one peripheral biomarker (total antioxidant status) were graded as highly suggestive evidence. Among the 41 factors, 8 (20%) were classified as suggestive evidence, while 3 (7%) of the 46 biomarkers received the same classification. Additionally, 29 of 54 (54%) factors and 18 of 33 (55%) biomarkers were graded as weak evidence.
This umbrella review highlights the evidence hierarchy of various ocular and systemic risk factors and biomarkers associated with glaucoma. Further high-quality studies are essential to strengthen the evidence base.
综合并评估现有关于与原发性青光眼相关的眼部和全身因素及生物标志物的荟萃分析的证据质量。
纳入了进行荟萃分析以评估青光眼的眼部和全身因素或生物标志物的系统评价。从数据库建库至2023年6月25日,对PubMed、Embase和Cochrane图书馆进行检索,无语言限制。两名研究人员独立进行筛选、数据提取和质量评估。采用随机效应模型估计汇总效应量、95%置信区间和95%预测区间。报告研究间异质性(I²)、小研究效应证据和过度显著性偏差证据。从原始研究估计值计算等效标准化均数差或比值比。
纳入了36项系统评价和荟萃分析,研究了87个与眼部生物特征、生活习惯、饮食、眼部和全身疾病以及来自眼部成像、血清、血浆和房水的生物标志物相关的因素。三个眼部因素(眼压、近视和角膜滞后)和一个外周生物标志物(总抗氧化状态)被评为高度提示性证据。在41个因素中,8个(20%)被归类为提示性证据,而46个生物标志物中有3个(7%)得到相同分类。此外,54个因素中的29个(54%)和33个生物标志物中的18个(55%)被评为弱证据。
本伞状综述突出了与青光眼相关的各种眼部和全身危险因素及生物标志物的证据层次。进一步的高质量研究对于加强证据基础至关重要。