Statistical Issues in AIDS Research

艾滋病研究中的统计问题

• 批准号: 8816027
• 负责人: JAMES P HUGHES
• 金额: $ 57.49万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-09-30 至 2019-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8816027
• 关键词: AIDS prevention; AIDS/HIV problem; Accounting; Acquired Immunodeficiency Syndrome; Address; Adherence; Algorithms; Anti-Retroviral Agents; Area; Biological Assay; Biological Markers; Biometry; Complex; Data; Data Analyses; Developing Countries; Development; Disease; Documentation; Epidemic; Epitope Mapping; Failure; HIV; HIV Infections; HIV prevention trial; HIV vaccine; Health; Healthcare; Individual; Infection; Lead; Measures; Meta-Analysis; Methods; Monitor; Oral; Pattern; Performance; Pharmaceutical Preparations; Phase; Prevention; Procedures; Process; Property; Prophylactic treatment; Research; Research Personnel; Resources; Risk; Sampling; Scheme; Solutions; Source; Staging; Statistical Methods; Testing; Vaccines; Work; causal model; cost; design; drug efficacy; improved; innovation; microbicide; novel; prevent; simulation; theories; tool; user friendly software; vaccine development

DESCRIPTION: Thirty years after identification of HIV, the AIDS epidemic continues with an estimated 34 million individuals currently infected worldwide and 2.5 million new infections each year. Research to prevent and treat HIV infection has grown increasingly sophisticated and the analytic challenges have become correspondingly complex. This application is intended to address timely and important statistical issues in HIV/AIDS research. In particular, novel statistical methods will be developed for (i) analysis of data from studies of pre-exposure prophylaxis (PrEP), (ii) optimal design and analysis of studies with complex sampling and observation schemes, and (iii) optimal design of pooling studies. First, statistical methods are proposed that address key challenges in PrEP studies, namely, inferring drug efficacy in the face of incomplete adherence, combining disparate sources of information to estimate adherence and summarizing adherence patterns. The approaches include causal modeling, Bayesian synthesis of information and functional data analysis. The proposed methods have the potential to provide clarity in a field which is hindered by disparate trial results. Second, becaue HIV studies often utilize expensive tests and assays, the proposed research will explore optimal sampling designs and efficient semiparametric and nonparametric methods for studies that use such two-phase or multi-phase sampling. The problems of multi-phase sampling and competing risks in the context of interval censored data will also be studied. These methods will provide critical guidance for optimizing the use of resources and minimizing costs in studies that utilize expensive assays. Finally, the proposed research will investigate statistical methods for the analysis of pooled data with specific applications to epitope mapping and monitoring for virologic failure in resource constrained settings. The former is a critical component of HIV vaccine development and the latter has the potential to greatly improve health care of HIV-infected individuals in developing countries. The proposed research reflects the extensive and ongoing involvement of the investigators in the field of HIV/AIDS research. The statistical problems addressed are motivated by applications in key areas of HIV research. The solutions outlined are highly innovative and directly applicable to current scientific research in vaccine development, trials of pre-exposure prophylaxis, and other HIV/AIDS trials and studies.

描述：鉴定艾滋病毒的三十年后，艾滋病流行持续，目前估计有3400万人在全球感染了3400万人，每年有250万个新感染。预防和治疗艾滋病毒感染的研究越来越复杂，分析挑战变得相应复杂。该应用程序旨在解决艾滋病毒/艾滋病研究中及时且重要的统计问题。特别是，将开发新的统计方法，以（i）分析暴露前预防的研究（PREP），（ii）具有复杂采样和观察方案的最佳设计和研究，以及（iii）合并研究的最佳设计。首先，提出了统计方法，即面对不完整的依从性，可以解决PREP研究中的关键挑战，即推断药物疗效，结合了不同信息来源以估算依从性并总结依从性模式。这些方法包括因果建模，贝叶斯综合信息和功能数据分析。所提出的方法有可能在被不同的试验结果阻碍的领域提供清晰度。其次，因为艾滋病毒研究经常利用昂贵的测试和测定，拟议的研究将探讨最佳的采样设计以及有效的半参数和非参数方法，用于使用这种两相或多相抽样的研究。还将研究间隔审查数据的多相抽样和竞争风险的问题。这些方法将为优化资源使用并最大程度地减少利用昂贵测定的研究的成本提供关键指导。最后，拟议的研究将调查用于分析汇总数据的统计方法，并在资源受限设置中使用特定应用程序进行表位映射和监测病毒学故障。前者是艾滋病毒疫苗开发的关键组成部分，后者有可能大大改善发展中国家艾滋病毒感染者的医疗保健。 拟议的研究反映了研究人员在艾滋病毒/艾滋病研究领域的广泛参与。解决的统计问题是由艾滋病毒研究关键领域的应用激发的。概述的解决方案具有高度创新性，直接适用于疫苗开发中当前的科学研究，暴露前预防试验以及其他HIV/AIDS试验和研究。