Use of Correlated Data Methods in Ophthalmology

基本信息

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
项目类别：
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

项目摘要

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.

项目概要/摘要眼科领域的一些暴露可能不会立即产生效果，而是需要一个滞后时间。例如，有一篇关于皮质类固醇滴眼液（CS）对葡萄膜炎可能导致白内障的文献然而，剂量和/或使用持续时间的确切影响尚不清楚，而且 CS 之间的滞后性也是未知的。白内障的治疗和发展尚不清楚。另一个可能的应用是研究白内障的影响。饮食和/或补充剂的使用对 AMD 的发展也可能产生滞后效应。具体目标1是使用潜伏期分析方法来确定眼科终点的潜伏期方法。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 流行病学领域的一项里程碑式研究。制定 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+（有 AMD）高级 AMD (AAMD) 风险因素的通常分析是基于 Cox 的事件发生时间分析。比例危险模型，其中事件达到 9+ 级。这是有效但效率低下的分析。有许多眼睛（大约 40%）显示出变化（增加或减少），但没有发展 AAMD 存在与这些变化相关的风险因素，但所有这些变化都是作为审查数据并被视为“非事件”。在目标 2 中，我们建议使用序数回归。连续访问之间的变化模型，这将提供更有效的数据利用。之前提出了多状态序数模型，但是单独的模型适用于每种可能的转变，并且未纳入特定协变量的总体风险评估中。这不仅适用于。 AMD，还适用于其他眼科疾病的其他序数量表，例如糖尿病视网膜病变。对于目标 3，我们建议继续将相关数据方法应用于风险预测的工作我们将专门比较小样本、大样本的 AUC 估计方法。此外，并列预测分数的数量以及双边和单边受试者的存在。结合聚类数据方法来估计 NRI，据我们所知，这从未完成过前。在目标 4 中，我们将继续为眼科研究界转化聚类数据方法包括（a）生存分析中的相关数据方法，（b）二元纵向眼数据分析，以及 (c) 以眼睛为分析单位的样本量/功效计算。