Use of Correlated Data Methods in Ophthalmology

相关数据方法在眼科中的应用

• 批准号: 10364917
• 负责人: Bernard A Rosner
• 金额: $ 54.67万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10364917
• 关键词: Acute; Adrenal Cortex Hormones; Adverse effects; Affect; Age related macular degeneration; Area; Bilateral; Blindness; Cataract; Categories; Chronic; Cicatrix; Clinical; Communities; Cox Models; Cox Proportional Hazards Models; Data; Development; Diabetic Retinopathy; Dietary intake; Discrimination; Dose; Elderly; Environmental Risk Factor; Epidemiology; Event; Eye; Eye diseases; Eyedrops; Genetic; Goals; Grant; Individual; Inflammation; Literature; Longitudinal cohort study; Lutein; Manuscripts; Measures; Methods; Modeling; Morbidity - disease rate; Omega-3 Fatty Acids; Ophthalmology; Outcome; Paper; Patients; Pharmacoepidemiology; Probability; Publishing; ROC Curve; Randomized; Research; Research Personnel; Risk; Risk Assessment; Risk Factors; Sample Size; Sampling; Severities; Severity of illness; Statistical Methods; Survival Analysis; Time; Topical Corticosteroids; Training Programs; Translations; Uveitis; Vision; Visit; Visual impairment; Work; analytical method; base; cohort; dietary; longitudinal analysis; macula; programs; protective factors; reduce symptoms; risk prediction; simulation; symposium; zeaxanthin

Project Summary / Abstract Some exposures in ophthalmology may not have an immediate effect, but instead a lag is necessary. For example, there is a literature on possible cataractogenic effects of corticosteroid eyedrops (CS) among uveitis patients. However, the precise impact of dose and/or duration of use are unknown. Also, the lag between CS administration and development of cataract is unknown. Another possible application is to study the effects of dietary and/or supplement use on development of AMD, where a lag effect is also likely to occur. The goal of specific aim 1 is to use latency analysis methods for ophthalmological endpoints. Latency methods have been used in pharmacoepidemiology, but to our knowledge, have never been used for ophthalmologic endpoints. The AREDS study was a landmark study in the epidemiology of AMD. A byproduct of this study was the development of the AREDS severity scale which is an ordinal scale ranging from 1 for no AMD to 9+ for advanced AMD (AAMD). The usual analysis for risk factors is a time-to-event analysis based on the Cox Proportional Hazards Model, where the event is reaching grade 9+. This is a valid, but inefficient analysis. There are many eyes (about 40%) which show changes (either an increase or decrease), but which don't develop AAMD. There are risk factors which are associated with these changes, but all such changes are treated as censored data and are considered “non-events”. In Aim 2, we propose to use an ordinal regression model for changes between successive visits which would provide a more efficient use of the data. There have been previous multi-state ordinal models proposed, but separate models are fit for each possible transition and are not integrated into an overall assessment of risk for specific covariates. This has application not only for AMD, but also for other ordinal scales used for other ophthalmologic conditions, such as diabetic retinopathy. For Aim 3, we propose to continue our work on applying correlated data methods to risk prediction for endpoints such as AUC. We will specifically compare methods for estimating AUC for small samples, extensive numbers of tied prediction scores and presence of both bilateral and unilateral subjects. In addition, we will incorporate clustered data methods for estimation of NRI, which to our knowledge, has never been done before. In Aim 4, we will continue our work on translation of clustered data methods for the eye research community including (a) correlated data methods in survival analysis, (b) analysis of longitudinal binary ocular data, and (c) sample size/power calculations based on the eye as the unit of analysis.

项目总结/摘要 眼科中的一些暴露可能不会立即产生影响，而是需要滞后。为 例如，有文献报道葡萄膜炎患者使用皮质类固醇滴眼液（CS）可能导致白内障 患者然而，剂量和/或使用持续时间的确切影响尚不清楚。此外，CS之间的滞后 白内障的施用和发展是未知的。另一个可能的应用是研究 饮食和/或补充剂的使用对AMD发展的影响，其中也可能发生滞后效应。的目标 具体目标1是使用眼科终点的潜伏期分析方法。延迟方法已经 用于药物流行病学，但据我们所知，从未用于眼科终点。 AREDS研究是AMD流行病学的一项里程碑式研究。这项研究的副产品是 开发了AREDS严重程度量表，该量表是一个顺序量表，范围从1（无AMD）到9+（无AMD）。 高级AMD（AAMD）。风险因素的通常分析是基于考克斯的至事件时间分析 比例风险模型，其中事件达到9+级。这是一个有效但低效的分析。 有许多眼睛（约40%）显示变化（增加或减少），但没有 开发AAMD。有风险因素与这些变化有关，但所有这些变化都是 视为删失数据，并视为“非事件”。在目标2中，我们建议使用有序回归 这将有助于更有效地利用数据。已经 以前提出的多状态有序模型，但单独的模型适合于每个可能的过渡， 未纳入特定协变量的风险总体评估。这不仅适用于 AMD，但也适用于其他眼科疾病，如糖尿病视网膜病变的其他顺序量表。 对于目标3，我们建议继续我们的工作，将相关数据方法应用于风险预测， 例如AUC。我们将专门比较用于估计小样本AUC的方法， 并列预测分数的数量以及双侧和单侧受试者的存在。此外，我们会 结合聚类数据方法估计NRI，据我们所知，这是从来没有做过的 以前 在目标4中，我们将继续为眼科研究社区翻译聚类数据方法的工作 包括（a）生存分析中的相关数据方法，（B）纵向二元眼数据的分析，和 (c)基于眼睛作为分析单位的样本量/功效计算。