Department of Ophthalmology and Visual Sciences, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
Computational Optometry, Atarfe, Spain.
PLoS One. 2020 Jul 1;15(7):e0235255. doi: 10.1371/journal.pone.0235255. eCollection 2020.
While many tests and indices are available to identify glaucoma progression, using them in combinations may decrease overall specificity. The aim of this study was to develop a framework for assessing glaucoma progression using structural and functional indices jointly for a fixed specificity.
The study included 337 eyes of 207 patients with ocular hypertension or primary open-angle glaucoma selected from the Diagnostic Innovations in Glaucoma Study or the African Descent and Glaucoma Evaluation Study. All patients had at least 9 visits. Each visit had retinal nerve fiber layer thickness (RNFLT) and mean sensitivity from static automated perimetry (SAP MS) measured within a one-month window. Simple linear regression was applied to assess deterioration in each index for series of 5 to 9 visits. To identify progression using the two indices jointly, marginal significance levels set at a specificity of 95% were derived for two criteria: ANY (worsening on either RNFLT or SAP MS) and ALL (worsening on both RNFLT and SAP MS). Positive rate (percentage of eyes flagged as progressing) was determined individually for each index, as well as for the ANY and ALL criteria.
Compared to SAP MS, RNFLT had higher positive rates (15% to 45%) for all series lengths. For the joint analyses, the positive rate was on average 12% higher for the ANY criterion compared to the ALL criterion. While RNFLT-alone had comparable positive rates and time-to-detection as the ANY criterion, each uniquely identified a subset of eyes (Kappa = 0.55 to 0.75).
This study provides a simple framework for assessing glaucoma progression with data from two tests jointly, without compromising specificity. This framework can be extended to include two or more parameters, can accommodate global or regional indices, and can eventually be used with novel parameters identified as predictive of glaucoma progression.
虽然有许多测试和指标可用于识别青光眼进展，但联合使用它们可能会降低整体特异性。本研究旨在开发一种使用结构和功能指标联合评估青光眼进展的框架，以保持固定的特异性。
该研究纳入了来自诊断性青光眼创新研究或非裔美国人青光眼评估研究的 207 例患者的 337 只眼，这些患者患有眼压升高或原发性开角型青光眼。所有患者均至少接受了 9 次就诊。每次就诊时，均在一个月的窗口内测量视网膜神经纤维层厚度（RNFLT）和静态自动视野计（SAP MS）的平均敏感度。应用简单线性回归评估每个指数在 5 至 9 次就诊的系列中恶化情况。为了使用两个指数联合识别进展，根据特异性为 95%的两个标准得出了边际显著水平：ANY（RNFLT 或 SAP MS 恶化）和 ALL（RNFLT 和 SAP MS 均恶化）。为每个指数以及 ANY 和 ALL 标准分别确定了进展的阳性率（被标记为进展的眼的百分比）。
与 SAP MS 相比，RNFLT 在所有系列长度上的阳性率（15%至 45%）均较高。对于联合分析，与 ALL 标准相比，ANY 标准的阳性率平均高 12%。虽然 RNFLT 单独与 ANY 标准具有可比的阳性率和检测时间，但它可以分别识别出一部分眼（Kappa=0.55 至 0.75）。
本研究提供了一种使用两种测试联合评估青光眼进展的简单框架，而不会降低特异性。该框架可以扩展到包括两个或更多参数，可以适应全局或区域指数，最终可以与被识别为预测青光眼进展的新参数一起使用。
