Causal inference for long-term survival in randomised trials with treatment switching: Should re-censoring be applied when estimating counterfactual survival times?
Causal inference for long-term survival in randomised trials with treatment switching: Should re-censoring be applied when estimating counterfactual survival times?
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DOI：
10.1177/0962280218780856
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发表时间：
2019-08-01
影响因子：
2.3
通讯作者：
Siebert, U.
中科院分区：
文献类型：
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作者：
Latimer, N. R.;White, I. R.;Siebert, U.
治疗转换通常对新肿瘤治疗的有效性和成本效益的估计产生关键影响。秩保持结构失效时间模型（RPSFTM）和两阶段估计（TSE）方法估计“反事实”（即没有转换）的生存时间，并纳入重新删失，以防止信息删失的反事实数据集。然而，重新删失会导致长期生存信息的丢失，这在需要估计长期生存影响时是有问题的，这通常是卫生技术评估决策的情况。我们提出了一个模拟研究，旨在研究应用程序的RPSFTM和TSE与和没有重新审查，以确定是否重新审查应始终建议调整分析。我们调查的背景下，切换是从对照组到实验治疗的情况下，不同的开关比例，治疗效果的大小，治疗效果随时间的变化，生存功能的形状，疾病的严重程度和切换预后。根据其对对照组限制性平均生存期的估计对方法进行评估，在没有转换的情况下观察到的平均生存期，直至试验随访结束。我们发现，重新删失的分析通常会产生负偏倚（即低估对照组限制的平均生存期和高估治疗效果），而没有重新删失的分析则会产生正偏倚，其幅度通常小于重新删失分析的偏倚，特别是当治疗效果较高且转换比例较低时。与其他方法相比，重新删失的RPSFTM通常导致偏倚增加。我们认为，分析应进行与不重新删失，因为这可能会提供决策者有用的信息，真正的治疗效果可能是谎言。当目标是估计长期生存时间和治疗效果时，重复再删失不应始终代表默认方法。
Treatment switching often has a crucial impact on estimates of effectiveness and cost-effectiveness of new oncology treatments. Rank preserving structural failure time models (RPSFTM) and two-stage estimation (TSE) methods estimate 'counterfactual' (i.e. had there been no switching) survival times and incorporate re-censoring to guard against informative censoring in the counterfactual dataset. However, re-censoring causes a loss of longer term survival information which is problematic when estimates of long-term survival effects are required, as is often the case for health technology assessment decision making. We present a simulation study designed to investigate applications of the RPSFTM and TSE with and without re-censoring, to determine whether re-censoring should always be recommended within adjustment analyses. We investigate a context where switching is from the control group onto the experimental treatment in scenarios with varying switch proportions, treatment effect sizes, treatment effect changes over time, survival function shapes, disease severity and switcher prognosis. Methods were assessed according to their estimation of control group restricted mean survival that would be observed in the absence of switching, up to the end of trial follow-up. We found that analyses which re-censored usually produced negative bias (i.e. underestimating control group restricted mean survival and overestimating the treatment effect), whereas analyses that did not re-censor consistently produced positive bias which was often smaller in magnitude than the bias associated with re-censored analyses, particularly when the treatment effect was high and the switching proportion was low. The RPSFTM with re-censoring generally resulted in increased bias compared to the other methods. We believe that analyses should be conducted with and without re-censoring, as this may provide decision-makers with useful information on where the true treatment effect is likely to lie. Incorporating re-censoring should not always represent the default approach when the objective is to estimate long-term survival times and treatment effects.