Personalized Forecasting of Disease Trajectory for Patients with Open Angle Glaucoma

开角型青光眼患者疾病轨迹的个性化预测

• 批准号: 9769756
• 负责人: Mariel Sofia Lavieri-Williams
• 金额: $ 56.52万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9769756
• 关键词: Address; Affect; American; Blindness; Brain; Clinical; Clinical Data; Clinical Trials; Data; Decision Aid; Development; Diagnostic tests; Disease; Disease Progression; Engineering; Eye; Foundations; Funding; Future; Glaucoma; Goals; Government; Intervention Studies; Knowledge; Mathematics; Measurement; Medical; Methodology; Methods; Mission; Modeling; Monitor; National Eye Institute; Nature; Nerve Fibers; Ocular Hypertension; Open-Angle Glaucoma; Operations Research; Operative Surgical Procedures; Ophthalmologist; Optic Nerve; Optical Coherence Tomography; Optometrist; Outcome; Output; Patient Care; Patients; Patterns of Care; Perimetry; Physiologic Intraocular Pressure; Prevalence; Probability; Process; Provider; Public Health; Randomized Controlled Trials; Recommendation; Research; Risk; Science; Severities; Statistical Methods; Structure; Suggestion; System; Techniques; Test Result; Testing; Therapeutic; Time; Tissues; Update; Vision; Work; advanced disease; base; care providers; data modeling; experience; high risk; hypertension treatment; improved; individual patient; innovation; overtreatment; patient subsets; personalized care; personalized predictions; preservation; prevent; retinal nerve fiber layer; targeted treatment; tonometry; tool; treatment trial; unnecessary treatment

Project Summary The primary objective of this project is to integrate principles and methods of operations research and systems engineering with data from NEI-funded clinical trials to develop an innovative approach to personalize the care of patients with open-angle glaucoma (OAG) and ocular hypertension (OHTN) to prevent avoidable blindness and vision loss. The outcomes sought will assist clinicians by (a) producing personalized forecasts of the probability of progressing from OHTN to OAG and less severe to more advanced disease states, (b) determining the optimal timing of specific diagnostic tests to monitor for glaucomatous progression for each patient, (c) identifying those at highest risk for irreversible vision loss from OAG (i.e., “fast progressors”), and (d) generating recommended target treatment goals of intraocular pressure (IOP). To achieve these objectives, this project integrates an understanding of glaucoma progression trajectory from NEI-funded clinical trials (including OHTS, CIGTS, and AGIS) with an individual patient's past and current test results from perimetry, tonometry and optical coherence tomography to generate personalized forecasts of glaucoma progression dynamics. Prior work by our group has shown that a preliminary forecasting tool we developed could accurately identify instances of OAG progression 57% sooner (p=0.02) and 29% more efficiently (p<0.0001), compared with the current practice for many patients of fixed 1-year intervals for patient assessment and testing. In this proposal, we look to greatly enhance the forecasting tool in several ways. In Aim 1 we will develop, parameterize, calibrate, and validate an advanced tool using data from the OHTS trial, to forecast if a patient with OHTN will develop OAG and the timing of progression to OAG. While our sophisticated state space Kalman filtering methodology appears to perform very well on patients with moderate to severe OAG, in this aim we plan to apply this methodology to study disease progression dynamics for patients with OHTN using data from OHTS. In Aim 2 we plan to extend the inputs to the forecasting tool beyond data from tonometry and perimetry to now also include data from structural testing including optical coherence tomography. In addition, this aim proposes to expand the output of the tool to include personalized predictions of which patients will become fast progressors, allowing clinicians to intervene before vision is irreversibly lost. In this aim, we also plan to forecast and graphically display the patient's likely OAG progression trajectory given a menu of different possible levels of IOP control, aiding the eye-care provider and patient in choosing how aggressive the treatment should be. By fulfilling the aims of this proposal, we hope to develop an advanced forecasting tool that will provide clinicians and patients with personalized, dynamically-updated, real time forecasts of OAG progression dynamics for each eye, which will greatly aid with decreasing avoidable vision loss and blindness from OAG.

项目概要 该项目的主要目标是将运筹学和系统的原理和方法整合起来 利用 NEI 资助的临床试验数据进行工程设计，开发个性化护理的创新方法 开角型青光眼 (OAG) 和高眼压症 (OHTN) 患者预防可避免的失明 和视力丧失。寻求的结果将通过以下方式帮助临床医生：(a) 生成个性化的预测 从 OHTN 进展为 OAG 以及较轻疾病状态进展为更晚期疾病状态的概率，(b) 确定特定诊断测试的最佳时机，以监测每个患者的青光眼进展情况 患者，(c) 确定 OAG 造成不可逆视力丧失风险最高的患者（即“快速进展者”），以及 (d) 生成眼压 (IOP) 的推荐目标治疗目标。为了实现这些目标， 该项目整合了 NEI 资助的临床试验对青光眼进展轨迹的理解 （包括 OHTS、CIGTS 和 AGIS）以及单个患者过去和当前的视野检查结果， 眼压测量和光学相干断层扫描可生成青光眼进展的个性化预测 动力学。我们小组之前的工作表明，我们开发的初步预测工具可以 准确识别 OAG 进展实例的时间缩短 57% (p=0.02)，效率提高 29% (p<0.0001)， 与目前许多患者每隔一年进行一次患者评估的做法相比 测试。在本提案中，我们希望通过多种方式大大增强预测工具。在目标 1 中，我们将 使用 OHTS 试验的数据开发、参数化、校准和验证高级工具，以预测是否 OHTN 患者将发生 OAG 以及进展为 OAG 的时间。虽然我们的复杂状态 空间卡尔曼滤波方法似乎对中度至重度 OAG 患者表现良好， 为了实现这一目标，我们计划应用这种方法来研究 OHTN 患者的疾病进展动态 使用来自 OHTS 的数据。在目标 2 中，我们计划将预测工具的输入扩展到以下数据之外： 眼压测量和视野测量现在​​还包括来自结构测试的数据，包括光学相干性 断层扫描。此外，该目标还建议扩展该工具的输出以包括个性化预测 其中患者将成为快速进展者，允许临床医生在视力不可逆转地丧失之前进行干预。 为此，我们还计划预测并以图形方式显示患者可能的 OAG 进展轨迹 给出不同可能的眼压控制水平的菜单，帮助眼保健提供者和患者进行选择 治疗应该有多积极。通过实现本提案的目标，我们希望开发一个 先进的预测工具，将为临床医生和患者提供个性化、动态更新、真实的预测 每只眼睛的 OAG 进展动态的时间预测，这将极大地帮助减少可避免的情况 OAG 导致视力丧失和失明。