Incorporating Risk Factors to Improve the Assessment of Rates of Glaucomatous Progression

被引:42
作者
Medeiros, Felipe A. [1 ]
Zangwill, Linda M. [1 ]
Mansouri, Kaweh [1 ]
Lisboa, Renato [1 ]
Tafreshi, Ali [1 ]
Weinreb, Robert N. [1 ]
机构
[1] Univ Calif San Diego, Hamilton Glaucoma Ctr, Dept Ophthalmol, La Jolla, CA 92093 USA
基金
美国国家卫生研究院;
关键词
VISUAL-FIELD PROGRESSION; FIBER LAYER THICKNESS; OPEN-ANGLE GLAUCOMA; OCULAR HYPERTENSION; INTRAOCULAR-PRESSURE; SENSITIVITY; PREDICTION; FRAMEWORK; MODEL;
D O I
10.1167/iovs.11-8639
中图分类号
R77 [眼科学];
学科分类号
100212 ;
摘要
PURPOSE. To present and evaluate a new method of integrating risk factors into the analysis of rates of visual field progression in glaucoma. METHODS. The study included 352 eyes of 250 glaucoma patients followed up for an average of 8.1 +/- 3.5 years. Slopes of change over time were evaluated by the mean deviation (MD) from standard automated perimetry. For each eye, the follow-up time was divided into two equal periods: the first half was used to obtain the slopes of change and the second period was used to test the predictions. Slopes of change were calculated with two methods: the conventional approach of ordinary least squares (OLS) linear regression and a Bayesian regression model incorporating information on risk factors and presence of progressive optic disc damage on stereophotographs. The mean square error (MSE) of the predictions was used to compare the predictive performance of the different methods. RESULTS. Higher mean IOP, thinner central corneal thickness (CCT), and presence of progressive optic disc damage were associated with faster rates of MD change. Incorporation of risk factor information into the calculation of individual slopes of MD change with the Bayesian method resulted in better prediction of future MD values than with the OLS method (MSE: 4.31 vs. 8.03, respectively; P < 0.001). CONCLUSIONS. A Bayesian regression model incorporating structural and risk factor information into the estimation of glaucomatous visual field progression resulted in more accurate and precise estimates of slopes of functional change than the conventional method of OLS regression. (ClinicalTrials.gov number, NCT00221897.) (Invest Ophthalmol Vis Sci. 2012; 53: 2199-2207) DOI:10.1167/iovs.11-8639
引用
收藏
页码:2199 / 2207
页数:9
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