Statistical Designs and Methods for Double-Sampling for HIV/AIDS

HIV/艾滋病双重抽样的统计设计和方法

• 批准号: 8604137
• 负责人: CONSTANTINE E FRANGAKIS
• 金额: $ 38.89万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-01-15 至 2016-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8604137
• 关键词: AIDS/HIV problem; Accounting; Acquired Immunodeficiency Syndrome; Address; Africa; Ambulatory Care; Caring; Characteristics; Clinical; Congresses; Data; Dropout; Emergency Situation; Enrollment; Ensure; Epidemic; Evaluation; Funding; Goals; HIV; Letters; Life; Malaria; Measures; Methods; Modeling; Monitor; Outcome; Patient Dropouts; Patients; Performance; Physicians; Program Evaluation; Public Health; Publications; Recording of previous events; Research; Research Personnel; Resources; Risk; Sampling; Stratification; Surveys; Tuberculosis; Work; base; cohort; design; experience; fighting; follow-up; improved; mortality; novel; programs; public health relevance; success; treatment program

DESCRIPTION (provided by applicant): Accurate evaluation of programs that treat and monitor HIV/AIDS patients around the world is central for fighting the epidemic. A major obstacle for program evaluation is patient dropout. An important such program is the President's Emergency Plan for AIDS Relief (PEPFAR). The US has been sponsoring PEPFAR ($63 billion for 2004-2013), and methods to accurately estimate patient survival are central to guide US management of the program. However, PEPFAR experiences high dropout rates (e.g., 39% in two years). Standard survival methods use only the observed non-dropout data, with no objective information for the dropouts. Such methods can be severely biased when dropout patients differ from nondropouts after accounting for observed information. To provide valid evaluation, in earlier work we have used a richer design known as "double-sampling". This design re-allocates increased resources to target, intensively pursue and find a subset of the dropouts. These double-sampled dropouts are intended to represent the non-double-sampled dropouts, and to provide objective information for the entire cohort. Although standard methods have been known for double-sampling in surveys, we have shown earlier that standard survival methods fail when double-sampling is used in continuous enrollment programs such as PEPFAR. Also, we have shown earlier that standard evaluation without double-sampling can dramatically underestimate mortality in PEPFAR by a factor of 5. The proposed methods will build on our earlier work with the framework of "principal stratification". The success of that framework increases the potential impact of this proposal. The proposed new methods are developed for three specific aims, motivated by PEPFAR in East Africa. (Aim 1). Develop methods to estimate the performance of follow-up programs by using data from a given double- sampling design. In this aim we will develop methods to estimate survival from double-sampling designs that select patients based on their history characteristics before dropout. This is also important for the next two aims. (Aim 2). Develop methods to create double-sampling designs that produce most accurate estimation of a pro- gram's performance given fixed resources. Evidence shows that information specific to a patient is important for what double-sampling designs provide best information about a program. Here, we will create patient-dependent double-sampling designs that maximize the accuracy given resources to estimate survival in such programs. (Aim 3). Develop double-sampling designs to best target clinical goals. Aim 1 can use the dropout patients' clinical history to predict those with highest mortality risk. These predictions can constrain the design to ensure to double-sample all such patients to better serve them medically. In Aim 3, we will create designs that maximize the accuracy of estimation and best benefit patients.

描述（由申请人提供）：对治疗和监测世界各地艾滋病毒/艾滋病患者的计划的准确评估对于与流行病作斗争至关重要。计划评估的主要障碍是患者辍学。一个重要的计划是总统的紧急艾滋病救济计划（PEPFAR）。美国一直在赞助PEPFAR（2004 - 2013年为630亿美元），准确估计患者生存的方法是指导美国管理计划的核心。但是，Pepfar的辍学率很高（例如，两年内为39％）。标准生存方法仅使用观察到的非抛弃数据，而没有客观的辍学信息。考虑到观察到的信息后，当辍学患者与非漏斗不同时，这种方法可能会严重偏见。为了提供有效的评估，在较早的工作中，我们使用了一种称为“双重采样”的富裕设计。这种设计重新分配了更多的资源，以实现目标，进行深入追求并找到辍学的子集。这些两次采样的辍学旨在代表非双重采样的辍学，并为整个队列提供客观信息。尽管在调查中已知标准方法已知标准方法，但我们早些时候已经证明，当在诸如PEPFAR等连续入学计划中使用双重采样时，标准生存方法失败了。同样，我们早些时候已经表明，没有重新采样的标准评估可以大大低估PEPFAR的死亡率5倍。拟议的方法将以“主分层”的框架为基础。该框架的成功增加了该提案的潜在影响。拟议的新方法是针对三个特定目标的三个特定目标开发的，由pepfar在东非的动机。 （目标1）。通过使用来自给定的双重抽样设计的数据来开发方法来估计后续程序的性能。在此目标中，我们将开发方法来估算双重采样设计的生存，这些设计根据患者在辍学前的历史特征选择。这对于接下来的两个目标也很重要。 （目标2）。开发方法来创建双重采样设计，从而在给定固定资源的情况下最准确地估算了计划的性能。有证据表明，特定于患者的信息对于双重采样设计提供有关程序的最佳信息很重要。在这里，我们将创建依赖于患者的双重采样设计，从而最大程度地提高给定资源以估计此类程序中生存的资源。 （目标3）。开发双重采样设计以最佳目标临床目标。 AIM 1可以使用辍学患者的临床病史来预测死亡率最高的人。这些预测可以限制设计，以确保将所有此类患者的所有样本双样本更好地在医学上更好地服务。在AIM 3中，我们将创建设计，以最大程度地提高估计的准确性和最佳好处患者。