Sun Yanqing, Hyun Seunggeun, Gilbert Peter
Department of Mathematics and Statistics, University of North Carolina at Charlotte, Charlotte, North Carolina 28223, USA.
Biometrics. 2008 Dec;64(4):1070-9. doi: 10.1111/j.1541-0420.2008.01012.x. Epub 2008 Mar 19.
In the evaluation of efficacy of a vaccine to protect against disease caused by a genetically diverse infectious pathogen, it is often important to assess whether vaccine protection depends on variations of the exposing pathogen. This problem can be viewed within the framework of a K-competing risks model where the endpoint event is pathogen-specific infection and the cause of failure is the strain type determined after the infection is diagnosed. The Cox model with time-dependent coefficients is used to relate the cause-specific outcomes to explanatory variables to allow for time-varying treatment effects. The strain-specific vaccine efficacy can be defined in terms of one minus the cause-specific hazard ratios. We develop inferential methods for testing whether the vaccine affords some protection against at least one pathogen strain, and for testing equal vaccine protection against the strains, adjusting for covariate effects. We also consider estimation of covariate-adjusted time-varying strain-specific vaccine efficacy. The methods are applied to a dataset from an oral cholera vaccine trial and the performances of the proposed tests are studied through simulations. These techniques apply more generally for testing and estimation of time-varying cause-specific hazard ratios.
在评估一种疫苗预防由基因多样化的传染性病原体引起的疾病的效力时，评估疫苗保护是否取决于暴露病原体的变异通常很重要。这个问题可以在一个K竞争风险模型的框架内看待，其中终点事件是病原体特异性感染，失败原因是感染被诊断后确定的菌株类型。具有时间依赖系数的Cox模型用于将病因特异性结局与解释变量相关联，以考虑随时间变化的治疗效果。菌株特异性疫苗效力可以用1减去病因特异性风险比来定义。我们开发了推断方法，用于检验疫苗是否对至少一种病原体菌株提供了一定的保护，以及检验对各菌株的疫苗保护是否相等，并对协变量效应进行调整。我们还考虑了协变量调整后的随时间变化的菌株特异性疫苗效力的估计。这些方法应用于一项口服霍乱疫苗试验的数据集，并通过模拟研究了所提出检验的性能。这些技术更广泛地应用于随时间变化的病因特异性风险比的检验和估计。
