ANALYTIC METHODS FOR HIV-TREATMENT AND COFACTOR EFFECTS

该项目的主要目标是进一步开发和实施新的 由作者和作者开发的用于分析观察性疾病的流行病学方法 艾滋病毒感染者的数据库和随机试验。建议数 这种方法在很大程度上是基于对参数的估计 一类新的因果模型，结构嵌套模型使用了一种新的 估计量类--G-估计量。新的方法从根本上说是 “流行病学”，因为他们需要与时间无关的数据和时间- 依存性混杂因素--即导致以下结果的风险因素 兴趣也预示着随后的治疗或暴露于 正在研究的药物或辅助因素。拟议的分析方法将 在以下方面对以前的方法进行了改进。 首先，新方法是唯一可用的方法来估计 一种治疗的效果(例如，死亡率、艾滋病发作时间或CD4计数水平) 从观察数据库中可用的数据，每当艾滋病毒的症状 疾病(如鹅口疮、发烧)同时也是混杂因素 来自治疗或辅助性疾病的因果途径的中间变量 正在研究的因素对感兴趣的结果的影响。我们将使用新的 大麻、酒精、可卡因、香烟作用的分析方法 吸烟、持续的高危性行为、喷雾剂喷雾剂，以及 AZT对CD4细胞数量的演变和HIV进展的影响 旧金山地区HIV感染者的疾病、艾滋病和死亡情况 弗朗西斯科男性健康研究(SFMHS)，一项观察性纵向研究 感染艾滋病毒的男同性恋者。结果将与所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，可以 适当调整以适应额外的非随机化的同时影响 随机临床试验中的治疗。例如，在艾滋病方面 临床试验单位(ACTU)对高剂量与低剂量的效果进行了试验002 AZT剂量对艾滋病患者生存的影响，患者在低剂量手臂上有 提高了存活率，但他们也服用了更多雾化的五味子胺(一种非 随机治疗)。我们将使用我们的方法来调整 五烷双胺的不同用法。 新的方法是唯一可以有效地结合 有关代理标志物(例如，CD4计数)的信息，以便在 对一种治疗方法的影响进行尽可能早的随机试验 生存时间结果(例如，感染艾滋病的时间)。具体来说，这些方法 允许对以下零假设构建有效的阿尔法水平测试 结合进化数据的治疗对存活率没有影响 例如，其能力可能大大超过的CD4计数 对数列检验的结果。我们将重新分析ACTU随机试验019 和016来确定所提出的方法是否可能导致更早 停止任何一项审判。

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.