Kaplan-Meier curves for survivor causal effects with time-to-event outcomes
Kaplan-Meier curves for survivor causal effects with time-to-event outcomes
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DOI：
10.1177/1740774513483601
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发表时间：
2013-08-01
期刊：
影响因子：
2.7
通讯作者：
Chiba, Yasutaka
中科院分区：
文献类型：
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作者：
Chiba, Yasutaka
背景在临床试验中，对于在结果评估之前死亡的个体，感兴趣的结果可能是不确定的。处理这些问题的一种方法是考虑幸存者因果效应（SCE），其定义为治疗对在任一治疗组下存活的亚群中结局的影响。尽管已经提出了几种方法来估计SCE与事件发生时间结局，目的：我们提出了一种简单的方法来创建Kaplan-Meier曲线，并估计SCE与时间的风险比（HR）。方法为了开发这样一种方法，我们将SCE的加权平均方法应用于无删失的结局，其中权重是使用患者在另一治疗组中存活的概率计算的，通过乘以每个患者的权重，可以为SCE创建Kaplan-Meier曲线。然后使用加权比例风险模型计算HR。对于这种方法，需要引入两个假设，以实现unbiasedness.Results所提出的方法说明使用随机II期临床试验的数据，比较两个化疗与放疗患者食管癌。在这里，我们重点关注局部区域控制率，这是从随机化后的时间计算，直到在辐射领域复发。对于无复发死亡的患者，持续时间未定义。拟定方法得出的HR为1.026（95%置信区间（CI）：0.627，1.677）。标准方法中，无进展死亡患者的数据被视为在死亡时删失，得出HR为1.121（95%CI：0.688，1.827）。作为一个普遍的问题，不幸的是，这些假设是否成立不能从观察到的数据得到证实。因此，我们不能确认是否Kaplan-Meier曲线和HR是unbiased.Conclusion我们提出了一种简单的方法SCE与时间到事件的结果，这是很容易实现的实践。所提出的方法是一个潜在的有价值的补充标准方法。
Background In clinical trials, an outcome of interest may be undefined for individuals who die before the outcome is evaluated. One approach to deal with such issues is to consider the survivor causal effect (SCE), which is defined as the effect of treatment on the outcome among the subpopulation that would have survived under either treatment arm. Although several methods have been presented to estimate the SCE with time-to-event outcomes, they are difficult to implement in practice.Purpose We present a simple method to create Kaplan-Meier curves and to estimate the hazard ratio (HR) for the SCE with time-to-event outcomes.Methods To develop such a method, we applied the weighted average method presented for the SCE to outcomes with no censoring, where weights are calculated using the probability that a patient would have survived had the patient been in the other treatment arm. By multiplying the weight to each patient, Kaplan-Meier curves can be created for the SCE to outcomes with censoring. The HR is then calculated using a weighted proportional hazard model. For this method, two assumptions need to be introduced to achieve unbiasedness.Results The proposed method is illustrated using data from a randomized Phase II clinical trial, comparing two chemotherapy treatments with radiotherapy in patients with esophageal cancer. Here, we focus on the loco-regional control rate, which is calculated from the time after randomization until recurrence in the radiation field. The duration is undefined for patients who died without recurrence. The proposed method yielded a HR of 1.026 (95% confidence interval (CI): 0.627, 1.677). The standard method, where data of patients who died without progression were regarded as censored at the time of death, yielded a HR of 1.121 (95% CI: 0.688, 1.827).Limitations The proposed method requires two assumptions. As a general problem, unfortunately, whether these assumptions hold cannot be confirmed from the observed data. Thus, we cannot confirm whether the Kaplan-Meier curves and the HR are unbiased.Conclusion We have proposed a simple method for the SCE with time-to-event outcomes, which is easy to implement in practice. The proposed method is a potentially valuable supplement to the standard method.