Wied Stephanie, Hilgers Ralf-Dieter, Heussen Nicole, Kotulska Katarzyna, Dirani Maya, Kuchenbuch Mathieu, Jozwiak Sergiusz, Nabbout Rima
Institute of Medical Statistics, RWTH Aachen University, Aachen, Germany.
Medical School, Sigmund Freud Private University, Vienna, Austria.
PLoS One. 2024 Dec 3;19(12):e0312936. doi: 10.1371/journal.pone.0312936. eCollection 2024.
In clinical research, the most appropriate way to assess the effect of an intervention is to conduct a randomized controlled trial (RCT). In the field of rare diseases, conducting an RCT is challenging, resulting in a low rate of clinical trials, with a high frequency of early termination and unpublished trials. The aim of the EPISTOP trial was to compare outcomes in infants with tuberous sclerosis (TSC) who received vigabatrin preventively before the seizures onset with those who received it conventionally after. The study was designed as a prospective, multicentre, randomized clinical trial. However, ethics committees at four centres did not approve this RCT design, resulting in an open-label trial (OLT) in these four centres and an RCT in the other six centres. In this paper, we re-analyse the data from the EPISTOP trial using methods to investigate the influence of allocation bias on the results of the EPISTOP trial.
A bias-corrected analysis is used to support and strengthen the published results. We included a term representing the effect of selection bias as an influencing factor on the corresponding endpoint in the statistical model. Thus, the treatment effect estimates for the primary endpoint of time to first seizure and additional secondary endpoints are adjusted for the bias effect.
The bias-corrected analyses for the primary endpoint show that the estimated hazard ratio and associated confidence intervals are in a very similar range (original analysis: HR 2.91, 95%-CI [1.11 to 7.67], p-value 0.0306; bias-corrected analysis: HR 2.89, 95%-CI [1.10 to 7.58], p-value 0.0316). This was also the case for the secondary endpoints.
The statistical re-analysis of the raw trial data therefore supports the published results and confirms that there is no additional bias introduced by randomization, thereby increasing the value of the results. However, this highlights that this aspect needs to be considered in future trials, especially in rare diseases, to avoid additional biases in an already small sample size where it may be difficult to reach significance.
在临床研究中，评估干预效果的最合适方法是进行随机对照试验（RCT）。在罕见病领域，开展RCT具有挑战性，导致临床试验率较低，早期终止和未发表试验的频率较高。EPISTOP试验的目的是比较在癫痫发作前预防性使用vigabatrin的结节性硬化症（TSC）婴儿与在癫痫发作后常规使用vigabatrin的婴儿的结局。该研究设计为一项前瞻性、多中心、随机临床试验。然而，四个中心的伦理委员会未批准该RCT设计，导致这四个中心进行开放标签试验（OLT），其他六个中心进行RCT。在本文中，我们使用方法重新分析EPISTOP试验的数据，以研究分配偏倚对EPISTOP试验结果的影响。
采用偏差校正分析来支持和强化已发表的结果。我们在统计模型中纳入一个代表选择偏倚效应的项作为对相应终点的影响因素。因此，对首次癫痫发作时间的主要终点和其他次要终点的治疗效果估计进行了偏差效应调整。
主要终点的偏差校正分析表明，估计的风险比和相关置信区间处于非常相似的范围（原始分析：HR 2.91，95%置信区间[1.11至7.67]，p值0.0306；偏差校正分析：HR 2.89，95%置信区间[1.10至7.58]，p值0.0316）。次要终点也是如此。
因此，对原始试验数据的统计重新分析支持了已发表的结果，并确认随机化未引入额外偏差，从而增加了结果的价值。然而，这突出表明在未来试验中，尤其是在罕见病试验中，需要考虑这一方面，以避免在本就小的样本量中出现额外偏差，因为在小样本量中可能难以达到显著性。
