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当事件定义在有限时间区间上时的事件发生时间分析。

Time-to-event analysis when the event is defined on a finite time interval.

作者信息

Lee Catherine, Lee Stephanie J, Haneuse Sebastien

机构信息

Division of Research, Kaiser Permanente, Oakland, CA, USA.

Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.

出版信息

Stat Methods Med Res. 2020 Jun;29(6):1573-1591. doi: 10.1177/0962280219869364. Epub 2019 Aug 22.

Abstract

Acute graft-versus-host disease (GVHD) is a frequent complication following hematopoietic cell transplantation (HCT). Research on risk factors for acute GVHD has tended to ignore two important clinical issues. First, post-transplant mortality is high. In our motivating data, 100-day post-HCT mortality was 15.4%. Second, acute GVHD in its classic form is only diagnosed within 100 days of the transplant; beyond 100 days, a patient may be diagnosed with late onset acute or chronic GVHD. Standard modeling of time-to-event outcomes, however, generally conceive of patients being able to experience the event at any point on the time scale. In this paper, we propose a novel multi-state model that simultaneously: (i) accounts for mortality through joint modeling of acute GVHD and death, and (ii) explicitly acknowledges the finite time interval during which the event of interest can take place. The observed data likelihood is derived, with estimation and inference via maximum likelihood. Additionally, we provide methods for estimating the absolute risk of acute GVHD and death simultaneously. The proposed framework is compared via comprehensive simulations to a number of alternative approaches that each acknowledge some but not all aspects of acute GVHD, and illustrated with an analysis of HCT data that motivated this work.

摘要

急性移植物抗宿主病(GVHD)是造血细胞移植(HCT)后常见的并发症。对急性GVHD危险因素的研究往往忽视了两个重要的临床问题。第一,移植后死亡率很高。在我们的激励数据中,HCT后100天的死亡率为15.4%。第二,典型形式的急性GVHD仅在移植后100天内诊断;超过100天,患者可能被诊断为迟发性急性或慢性GVHD。然而,事件发生时间结果的标准建模通常认为患者能够在时间尺度上的任何时间点经历该事件。在本文中,我们提出了一种新颖的多状态模型,该模型同时:(i)通过对急性GVHD和死亡的联合建模来考虑死亡率,以及(ii)明确承认感兴趣事件可能发生的有限时间间隔。推导了观察数据的似然性,并通过最大似然法进行估计和推断。此外,我们提供了同时估计急性GVHD和死亡绝对风险的方法。通过全面模拟将所提出的框架与许多替代方法进行比较,这些替代方法各自承认急性GVHD的一些但不是所有方面,并通过对激发这项工作的HCT数据的分析进行说明。

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