Statistical Methods for chronic Disease Research

慢性病研究的统计方法

• 批准号: 7149564
• 负责人: YIJIAN HUANG
• 金额: $ 10.68万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-04-01 至 2009-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7149564
• 关键词: AIDS; chronic disease /disorder; computer simulation; data collection methodology /evaluation; extended care; health care cost /financing; human data; neoplasm /cancer; statistics /biometry

DESCRIPTION (provided by applicant): A single time-to-event, e.g., overall survival time, has been the typical primary endpoint in longitudinal cancer and HIV/AIDS studies. However, this outcome alone is generally inadequate to capture all the impacts, clinical and economic, that a treatment (and/or other covariates) might have. Comprehensive assessment of treatments has been increasingly advocated in recent years, and this effort has posed many unique statistical challenges. The broad objective of this research is to address some of these challenges in chronic disease research and develop new statistical methods. Major efforts will be directed toward (1) cost and cost-effectiveness analyses with incomplete follow-up data and (2) marginal analysis'^ time-between- events in multi-state processes and recurrent events. Current developments in these two areas are inadequate and substantial gaps of knowledge exist. Given that our health care system is increasingly constrained with limited resources, nowadays cost evaluation is becoming an important component in medical research and has been integrated in many studies. This work will focus on developing semiparametric estimation and regression procedures that accommodate right-censored data. The second area of research concerns the analysis of disease processes represented by multiple clinical states or recurrent events. Existing statistical methods largely target at time-to-events. This research will address time-between-events, which are of direct scientific interest in many circumstances. Despite the challenges of these long-standing problems, preliminary investigations have shown considerable promise for elegant and practical solutions. Large-sample properties of the proposed estimators will be rigorously investigated. Extensive simulation studies will be performed to validate these proposals under practical sample sizes. The proposed methods will be applied to a number of clinical studies. User-friendly computer programs will be developed and made available to the research community.

描述（由申请人提供）：单一事件发生时间，如总生存时间，一直是纵向癌症和艾滋病毒/艾滋病研究中典型的主要终点。然而，仅凭这一结果通常不足以捕捉治疗（和/或其他协变量）可能产生的所有临床和经济影响。近年来，越来越多的人提倡对治疗进行综合评估，这一努力提出了许多独特的统计挑战。这项研究的广泛目标是解决慢性病研究中的一些挑战，并开发新的统计方法。主要工作将集中在(1)不完整后续数据的成本和成本效益分析和(2)多状态过程和重复事件的边际分析。这两个领域目前的发展是不充分的，存在着巨大的知识差距。鉴于我国卫生保健系统日益受到有限资源的制约，成本评估已成为医学研究的重要组成部分，并已被纳入许多研究。这项工作将侧重于开发半参数估计和回归程序，以适应右审查数据。第二个研究领域涉及对由多种临床状态或复发事件所代表的疾病过程的分析。现有的统计方法主要针对事件时间。这项研究将处理事件之间的时间，这在许多情况下具有直接的科学意义。尽管存在这些长期存在的问题的挑战，初步的调查已经显示出相当大的希望优雅和实用的解决方案。提出的估计器的大样本性质将被严格研究。将进行广泛的模拟研究，以在实际样本量下验证这些建议。所提出的方法将应用于许多临床研究。将开发用户友好的计算机程序并提供给研究界。