ANALYTIC METHODS FOR HIV-TREATMENT AND COFACTOR EFFECTS

HIV 治疗和辅助因子效应的分析方法

• 批准号: 3147580
• 负责人: JAMES M ROBINS
• 金额: $ 16.74万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-08-01 至 1995-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3147580
• 关键词: AIDS; AIDS therapy; computer program /software; disease /disorder proneness /risk; epidemiology; human immunodeficiency virus 1; human therapy evaluation; mathematical model; model design /development; pentamidine; statistics /biometry; zidovudine

The principal aim of this project is to further develop and implement new epidemiologic methods developed by and author for analyzing observational data bases and randomized trials of HIV-infected persons. The proposed approach is to a large extent based on the estimation of the parameters of a new class of causal models, the structural nested models using a new class of estimators - the G-estimators. The new methods are fundamentally "epidemiologic" in that they require data on time-independent and time- dependent confounding factors - that is, risk factors for the outcome of interest that also predict subsequent treatment with or exposure to the drug or co-factor under study. The proposed methods of analysis will improve upon previous methods in the following ways. First, the new methods are the only methods available to estimate the effect of a treatment (e.g., mortality, time to AIDS, or CD4-count level) from data available in an observational data base, whenever symptoms of HIV disease (e.g., thrush, fever) are simultaneously confounders and intermediate variables on the causal pathway from the treatment or co- factor under study to the outcome of interest. We shall use the new methods of analyze the effect of marijuana, alcohol, cocaine, cigarette smoking, continued high-risk sexual behavior, aerosolized pentamidine, and AZT on the evolution of CD4-counts and on time to progression of HIV- disease, AIDS and death among the HIV-infected subjects in the San Francisco Men's Health Study (SFMHS), an observational longitudinal study of HIV-infected gay men. Results will be compared with those obtained using standard methods. Second, the new methods are the only methods available that can appropriately adjust for the concurrent effect of additional non-randomized treatments in randomized clinical trials. For example, in the AIDS Clinical Trial Unit (ACTU) trial 002 of the effect of high dose versus low- dose AZT on the survival of AIDS patients, patients in the low-dose arm had improved survival, but they also took more aerosolized pentamidine (a non- randomized treatment). We shall use our methods to adjust for the differential pentamidine usage. The new methods are the only methods available that efficiently incorporate information on surrogate markers (e.g., CD4-count) in order to stop, at the earliest possible moment, randomized trials of the effects a treatment on a survival time outcome (e.g., time to AIDS). Specifically, these methods allow one to construct a valid alpha-level test of the null hypothesis of no effect of treatment on survival that incorporates data on the evolution of the surrogate marker, e.g., CD4-count whose power may greatly exceed that of the log-rank test. We shall reanalyze ACTU randomized trials 019 and 016 to determine whether the proposed methods could have led to earlier stoppage of either trial.

该项目的主要目的是进一步开发和实施新的 由和作者开发的流行病学方法，用于分析观察性 艾滋病毒感染者的数据库和随机试验。 拟议 这种方法在很大程度上是基于参数的估计， 一类新的因果模型，即使用新的结构嵌套模型 一类估计量-G-估计量。 新方法从根本上 “流行病学”，因为它们需要与时间无关的数据， 依赖性混杂因素-即， 感兴趣，也预测随后的治疗或暴露于 研究中的药物或辅助因子。 拟议的分析方法将 从以下几个方面改进以前的方法。 首先，新方法是唯一可用的方法来估计 治疗的效果（例如，死亡率、艾滋病时间或CD 4计数水平） 根据观察数据库中的可用数据， 疾病（例如，鹅口疮、发热）同时是混杂因素， 中间变量的因果途径，从治疗或共同 研究中的因素与关注的结果之间的关系。 我们将使用新的 分析大麻、酒精、可卡因、香烟的作用 吸烟，持续的高风险性行为，雾化喷他脒， AZT对CD 4计数的变化和HIV进展时间的影响- 疾病，艾滋病和死亡的艾滋病毒感染者在圣 弗朗西斯科男性健康研究（SFMHS），一项观察性纵向研究 感染艾滋病的男同性恋者 结果将与获得的结果进行比较 使用标准方法。 其次，新方法是唯一可用的方法 适当调整额外非随机化的并发效应 随机临床试验中的治疗。 例如，在艾滋病 临床试验单位（ACTU）试验002高剂量与低剂量的影响 剂量AZT对艾滋病患者生存期的影响，低剂量组患者有 提高生存率，但他们也采取了更多的雾化喷他脒（一种非 随机化治疗）。 我们将使用我们的方法来调整 不同的喷他脒使用。 这些新方法是唯一有效地结合了 关于替代标记的信息（例如，CD 4计数），以停止，在 尽可能早的时刻，随机试验的影响，治疗对 存活时间结果（例如，艾滋病时间）。 具体来说，这些方法 允许一个人构建一个有效的阿尔法水平测试的零假设， 结合进化数据的治疗对生存没有影响 替代标记物，例如，CD 4-计数，其功效可能大大超过 log-rank检验的结果。 我们将重新分析ACTU随机试验019 和016，以确定所提出的方法是否可以导致更早的 停止任何审判。