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: 2457747
• 负责人: JAMES M ROBINS
• 金额: $ 31.4万
• 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 1998-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2457747
• 关键词: AIDS; AIDS therapy; CD4 molecule; Pneumocystis carinii; Pneumocystis pneumonia; computer program /software; disease /disorder proneness /risk; epidemiology; health behavior; human data; human immunodeficiency virus 1; human therapy evaluation; male; marijuana abuse; opportunistic infections; pathologic process; pentamidine; statistics /biometry; zidovudine

My principal aim is further development of new methods for analyzing observational data bases and randomized trials of HIV-infected persons. The proposed approaches are based either on (i) the estimation of a new class of causal models, the structural nested models using a new class of estimators, the G-estimators, or (ii) new methods for analyzing semi- or non-parametric models in the presence of both informative and non- informative missing data. Many of the new methods are fundamentally "epidemiologic" in that they require data on time-dependent confounding factors, that is, risk factors for outcomes that also predict subsequent treatment with 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 best methods available to estimate the effect of a treatment (e.g., AZT) or a co-factor (e.g., marijuana) on an outcome of interest (e.g., time to AIDS or CD4-count level) from observational data available, when symptoms of HIV disease (e.g., thrush, fever) are simultaneously confounders and intermediate variables. We shall use the new methods to estimate treatment and co-factor effects on the evolution of CD4-counts and on time to progression of HIV-disease among subjects in the San Francisco Men's Health Study (SFMHS), and the Multicenter AIDS Cohort Study (MACS). Results will be compared with results obtained using standard methods. Second, the new methods are the best methods available to adjust for dependent censoring, non-random non-compliance, treatment cross-over or termination, and the concurrent effect of additional non-randomized treatments in randomized clinical trials. For example, in ACTG trial 002 of the effect of high-dose versus low-dose AZT on the survival of AIDS patients, patients in the low-dose arm took more aerosolized pentamidine (a non-randomized treatment). The new methods are the best methods available to efficiently incorporate information on surrogate markers (e.g., CD4-count) in order to stop, at the earliest possible moment, randomized trials of the effect of a treatment on a survival time outcome (e.g., time to AIDS). Specifically, we 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 multivariate surrogate markers, e.g., (CD4-count and HIV antigen level), with power exceeding that of the log rank test. We shall use our new methods to further analyze ACTG trial 0002 as well as ACTG trials 021 and 081. These latter two trials compare the effects of various chemotherapeutic agents on the opportunistic infection and survival experience of HIV-infected subjects.

我的主要目标是进一步发展新的分析方法， 观察数据库和艾滋病毒感染者的随机试验。 所提出的方法是基于（i）估计一个新的 一类因果模型，结构嵌套模型使用一类新的 估计，G-估计，或（ii）分析半或 非参数模型在信息和非信息的存在下， 信息缺失数据。许多新方法从根本上 “流行病学”，因为它们需要时间依赖性混杂的数据 也就是说，风险因素的结果，也预测随后的 用研究中的药物或辅因子治疗。建议的方法 分析将在以下方面改进先前的方法。 第一，新方法是估计 治疗的效果（例如，AZT）或辅因子（例如，大麻）在一个 感兴趣的结果（例如，至艾滋病或CD 4计数水平的时间） 现有的观察数据，当艾滋病毒疾病的症状（例如，鹅口疮， 发热）同时是混杂因素和中间变量。我们将 使用新的方法来估计治疗和辅因子对 CD 4计数的变化和HIV疾病进展的时间 受试者在旧金山弗朗西斯科男性健康研究（SFMHS），和 多中心艾滋病队列研究（MACS）。结果将与 使用标准方法获得的结果。 第二，新方法是最好的方法， 相关删失、非随机不依从、治疗交叉或 终止，以及额外的非随机化 随机临床试验中的治疗。例如，ACTG试验002 高剂量和低剂量AZT对艾滋病患者存活率的影响 低剂量组的患者使用了更多的喷他脒气雾剂 （非随机治疗）。新方法是最好的方法 可用于有效地结合替代标记物的信息 (e.g., CD 4计数），以便尽早停止， 治疗对生存时间结果影响的随机试验 (e.g.,艾滋病时间）。具体地说，我们需要构建一个有效的alpha水平 治疗对生存期无影响的零假设检验， 结合了关于多变量替代标志物的演变的数据， 例如，在一个实施例中，（CD 4计数和HIV抗原水平），功效超过 对数秩检验我们将使用我们的新方法进一步分析ACTG试验 0002以及ACTG试验021和081。 后两项试验比较 各种化疗药物对机会性 HIV感染者的感染和生存经验。