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挽救性治疗对按指征治疗的纵向研究中生存的影响。

The effect of salvage therapy on survival in a longitudinal study with treatment by indication.

机构信息

Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.

出版信息

Stat Med. 2010 Nov 10;29(25):2569-80. doi: 10.1002/sim.4017.

Abstract

We consider using observational data to estimate the effect of a treatment on disease recurrence, when the decision to initiate treatment is based on longitudinal factors associated with the risk of recurrence. The effect of salvage androgen deprivation therapy (SADT) on the risk of recurrence of prostate cancer is inadequately described by the existing literature. Furthermore, standard Cox regression yields biased estimates of the effect of SADT, since it is necessary to adjust for prostate-specific antigen (PSA), which is a time-dependent confounder and an intermediate variable. In this paper, we describe and compare two methods which appropriately adjust for PSA in estimating the effect of SADT. The first method is a two-stage method which jointly estimates the effect of SADT and the hazard of recurrence in the absence of treatment by SADT. In the first stage, PSA is predicted in the absence of SADT, and in the second stage, a time-dependent Cox model is used to estimate the benefit of SADT, adjusting for PSA. The second method, called sequential stratification, reorganizes the data to resemble a sequence of experiments in which treatment is conditionally randomized given the time-dependent covariates. Strata are formed, each consisting of a patient undergoing SADT and a set of appropriately matched controls, and analysis proceeds via stratified Cox regression. Both methods are applied to data from patients initially treated with radiation therapy for prostate cancer and give similar SADT effect estimates.

摘要

我们考虑使用观察性数据来估计治疗对疾病复发的影响,当治疗决策是基于与复发风险相关的纵向因素时。 salvage 雄激素剥夺疗法 (SADT) 对前列腺癌复发风险的影响在现有文献中描述不足。此外,由于有必要调整前列腺特异性抗原 (PSA),标准 Cox 回归会产生 SADT 效果的有偏估计,因为 PSA 是一个时变混杂因素和中间变量。在本文中,我们描述并比较了两种方法,这些方法通过适当调整 PSA 来估计 SADT 的效果。第一种方法是两阶段方法,它通过同时估计 SADT 的效果和在没有 SADT 治疗的情况下的复发风险来进行调整。在第一阶段,在没有 SADT 的情况下预测 PSA,在第二阶段,使用时变 Cox 模型来估计 SADT 的益处,同时调整 PSA。第二种方法称为序贯分层,将数据重新组织为类似于一系列实验,其中治疗是根据时变协变量有条件随机分配的。形成分层,每个分层都由接受 SADT 的患者和一组适当匹配的对照组组成,并且通过分层 Cox 回归进行分析。这两种方法都应用于最初接受放射治疗的前列腺癌患者的数据,并且给出了相似的 SADT 效果估计。

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