Sabouri Samaneh, Haem Elham, Masoumpour Masoumeh, Vermeer Koenraad A, Lemij Hans G, Yousefi Siamak, Pourahmad Saeedeh
Department of Biostatistics.
Department of Ophthalmology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
J Glaucoma. 2023 May 1;32(5):355-360. doi: 10.1097/IJG.0000000000002155. Epub 2023 Mar 30.
Irregular visual field test frequency at relatively short intervals initially and longer intervals later on in the disease provided acceptable results in detecting glaucoma progression.
It is challenging to maintain a balance between the frequency of visual field testing and the long-term costs that may result from insufficient treatment of glaucoma patients. This study aims to simulate real-world circumstances of visual field data to determine the optimum follow-up scheme for the timely detection of glaucoma progression using a linear mixed effects model (LMM).
An LMM with random intercept and slope was used to simulate the series of mean deviation sensitivities over time. A cohort study including 277 glaucoma eyes that were followed for 9.0±1.2 years was used to derive residuals. Data were generated from patients with early-stage glaucoma having various regular and irregular follow-up scenarios and different rates of visual field loss. For each condition, 10,000 series of eyes were simulated, and one confirmatory test was conducted to identify progression.
By doing one confirmatory test, the percentage of incorrect progression detection decreased considerably. The time to detect progression was shorter for eyes with an evenly spaced 4-monthly schedule, particularly in the first 2 years. From then onward, results from twice-a-year testing were similar to results from examinations scheduled 3 times per year.
Irregular visual field test frequency at relatively short intervals initially and longer intervals later on in the disease provided acceptable results in detecting glaucoma progression. This approach could be considered for improving glaucoma monitoring. Moreover, simulating data using LMM may provide a better estimate of the disease progression time.
在疾病初期以相对较短的间隔进行不规则视野检查,后期间隔时间延长,在检测青光眼进展方面可获得可接受的结果。
在视野检查频率与青光眼患者治疗不足可能导致的长期成本之间保持平衡具有挑战性。本研究旨在模拟视野数据的真实情况,使用线性混合效应模型(LMM)确定用于及时检测青光眼进展的最佳随访方案。
使用具有随机截距和斜率的LMM来模拟随时间变化的一系列平均偏差敏感度。一项队列研究纳入了277只随访9.0±1.2年的青光眼患眼,用于得出残差。数据来自患有早期青光眼且有各种定期和不定期随访方案以及不同视野损失率的患者。对于每种情况,模拟10,000系列患眼,并进行一次确认性测试以确定进展情况。
通过进行一次确认性测试,错误进展检测的百分比大幅下降。对于每4个月进行一次等间隔检查的患眼,检测进展的时间较短,尤其是在最初2年。从那时起,每年两次检查的结果与每年三次检查的结果相似。
在疾病初期以相对较短的间隔进行不规则视野检查,后期间隔时间延长,在检测青光眼进展方面可获得可接受的结果。这种方法可考虑用于改善青光眼监测。此外,使用LMM模拟数据可能会更好地估计疾病进展时间。