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Measuring and predicting visual field progression with longitudinal-survival CART

使用纵向生存 CART 测量和预测视野进展

基本信息

批准号：
7878627
负责人：
RICHARD A LEVINE
金额：
$ 18.71万
依托单位：
SAN DIEGO STATE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-07-01 至 2011-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7878627
关键词：
Accounting Address Caring Classification Clinical Clinical Data Clinical Trials Data Databases Defect Detection Deterioration Development Diagnostic Disease Early Diagnosis Equipment Evaluation Eye Eye diseases Glaucoma Goals Individual Joints Lead Location Mainstreaming Markov Chains Measurement Measures Medical Methods Modeling Monitor Monte Carlo Method Ocular Hypertension Office Visits Optic Disk Outcome Outcome Measure Patients Pattern Perimetry Philosophy Prevention Primary Open Angle Glaucoma Procedures Prognostic Factor Protocols documentation Psychophysics Public Health Research Research Personnel Research Project Grants Risk Risk Factors Sensitivity and Specificity Series Severities Societies Statistical Methods System Test Result Testing Time Treatment Protocols Trees Variant Visual Fields Work base cost data mining evidence base expectation follow-up frailty high risk interest meetings novel optic nerve disorder physical conditioning prognostic indicator research clinical testing secondary outcome slow potential tool treatment planning

项目摘要

DESCRIPTION (provided by applicant): Detection and prediction of visual field progression has been recognized as a crucially needed development for glaucoma management and care. Characterization of visual field progression will allow for directed follow-up of high risk eyes, early detection and treatment of glaucoma, better potential for slowing progression of diseased eyes, and a protocol for delaying visual field damage. As a secondary outcome, it will also provide a justifiable and valid progression outcome measure for clinical trials and studies of glaucoma. However, it is equally well recognized that characterization of progression is one of the most challenging aspects of glaucoma research and clinical evaluation but perhaps a finding with high impact on management strategies/philosophies. The primary aims of this research project are to develop clinical indicators and prognostic factors for detecting and predicting glaucomatous visual field progression. These aims will be met through applications of novel classification and regression tree (CART) methods to data from the perimetry and psychophysics in glaucoma (PPIG) study. The PPIG study consists of 168 individuals with moderate to high risk ocular hypertension or early glaucoma followed for up to eleven years with annual visual field examinations. The data includes a measure of progressive glaucomatous optic neuropathy (pGON), standard automated perimetry visual field test patterns and summaries, optic disc summaries, and other clinical and sociodemographic observations. The new CART methods developed account for correlations between fellow eyes and spatial variability in the temporal series of visual field measurements in assimilating visual field data. The CART analyses thus take full advantage of the PPIG study data in creating glaucomatous visual field progression classification systems, definitive measures for detecting visual field progression from follow-up visual fields and for predicting visual field progression from baseline observations.

描述（由申请人提供）：视野进展的检测和预测已被认为是青光眼管理和护理的关键发展。视野进展的特征将允许高风险眼睛的直接随访，早期发现和治疗青光眼，更好地减缓患病眼睛的进展，以及延迟视野损害的协议。作为次要结局，它也将为青光眼的临床试验和研究提供一个合理和有效的进展结局指标。然而，同样公认的是，进展特征是青光眼研究和临床评估中最具挑战性的方面之一，但可能是对管理策略/理念具有重要影响的发现。本研究项目的主要目的是发展临床指标和预后因素，以检测和预测青光眼的视野进展。这些目标将通过应用新的分类和回归树（CART）方法来处理青光眼（PPIG）研究的视野和心理物理学数据。PPIG研究包括168名中度至高风险高眼压或早期青光眼患者，随访长达11年，每年进行视野检查。数据包括进行性青光眼视神经病变（pGON）的测量，标准的自动视野测试模式和总结，视盘总结，以及其他临床和社会人口学观察。新的CART方法在吸收视野数据时考虑了同伴眼睛与视野测量时间序列中的空间变异性之间的相关性。CART分析因此充分利用了PPIG研究数据来创建青光眼视野进展分类系统，从随访视野中检测视野进展的明确措施以及从基线观察中预测视野进展。