Analysis of human immune responses in quasi-experimental settings: tutorial in biostatistics.
Analysis of human immune responses in quasi-experimental settings: tutorial in biostatistics.
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DOI：
10.1186/1471-2288-12-1
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发表时间：
2012-01-03
影响因子：
4
通讯作者：
Naumova EN
中科院分区：
文献类型：
--
作者：
Sarkar R;Ajjampur SS;Ward HD;Kang G;Naumova EN
人体免疫学是一个不断发展的研究领域，其中使用了许多生命科学学科的实验、临床和分析方法。经典的流行病学研究设计，包括观察性纵向出生队列研究，为获得人类对病原体的免疫反应的新知识和见解提供了强大的潜力。然而，缺乏与设计和统计分析相关的方法问题的严格讨论，这些问题适合于纵向研究。在本通讯中，我们讨论了用于测量免疫反应的传统和最近开发的统计工具的质量和有效性的关键问题。为此目的，我们使用体液免疫反应（IR）的数据，这些数据与居住在印度南部城市贫民窟的儿童出生队列中的第一例隐孢子虫腹泻相关。主要目的是检测在两个时间点，在感兴趣的事件之前（前）和之后（后）测量的IR变化的差异并得出推论。我们说明了分析和数据可视化技术的使用和解释，包括广义线性和加性模型，数据驱动平滑，以及箱形图，散点图和针形图的组合。我们提供了进行彻底和相对简单的分析调查的逐步说明，描述了挑战和陷阱，并提供了全面检查数据的实用解决方案。我们举例说明如何假设时间无关可以处理研究与前后设计。我们演示了如何通过考虑在感兴趣的事件之后的反应时间和通过适当对准测量时间的暴露的季节性波动来研究人类的红外动力学。这种日历测量时间和儿童在感兴趣事件时的年龄的一致性使我们能够探索红外辐射、季节性暴露和首次感染年龄之间的相互作用。使用传统的统计技术来分析来自观察性人体研究的免疫学数据可能导致重要信息的丢失。使用量身定制的技术进行详细分析，可以在人类纵向研究中描述对病原体免疫反应的新特征。提出的分阶段方法对未来的研究设计和分析具有重要意义。
Human immunology is a growing field of research in which experimental, clinical, and analytical methods of many life science disciplines are utilized. Classic epidemiological study designs, including observational longitudinal birth cohort studies, offer strong potential for gaining new knowledge and insights into immune response to pathogens in humans. However, rigorous discussion of methodological issues related to designs and statistical analysis that are appropriate for longitudinal studies is lacking. In this communication we address key questions of quality and validity of traditional and recently developed statistical tools applied to measures of immune responses. For this purpose we use data on humoral immune response (IR) associated with the first cryptosporidial diarrhea in a birth cohort of children residing in an urban slum in south India. The main objective is to detect the difference and derive inferences for a change in IR measured at two time points, before (pre) and after (post) an event of interest. We illustrate the use and interpretation of analytical and data visualization techniques including generalized linear and additive models, data-driven smoothing, and combinations of box-, scatter-, and needle-plots. We provide step-by-step instructions for conducting a thorough and relatively simple analytical investigation, describe the challenges and pitfalls, and offer practical solutions for comprehensive examination of data. We illustrate how the assumption of time irrelevance can be handled in a study with a pre-post design. We demonstrate how one can study the dynamics of IR in humans by considering the timing of response following an event of interest and seasonal fluctuation of exposure by proper alignment of time of measurements. This alignment of calendar time of measurements and a child's age at the event of interest allows us to explore interactions between IR, seasonal exposures and age at first infection. The use of traditional statistical techniques to analyze immunological data derived from observational human studies can result in loss of important information. Detailed analysis using well-tailored techniques allows the depiction of new features of immune response to a pathogen in longitudinal studies in humans. The proposed staged approach has prominent implications for future study designs and analyses.
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影响因子：
9.4
作者：
Banerjee, Indrani;Ramani, Sasirekha;Kang, Gagandeep
通讯作者：
Kang, Gagandeep
影响因子：
7.7
作者：
Frost, FJ;Muller, T;Calderon, RL
通讯作者：
Calderon, RL
DOI：
10.4269/ajtmh.2004.71.412
发表时间：
2004-10-01
影响因子：
3.3
作者：
Khan, WA;Rogers, KA;Ward, HD
通讯作者：
Ward, HD
DOI：
10.1602/neurorx.1.3.341
发表时间：
2004-07-01
期刊：
NeuroRx : the journal of the American Society for Experimental NeuroTherapeutics
影响因子：
--
作者：
Concato, John
通讯作者：
Concato, John
影响因子：
8.3
作者：
Jagai, Jyotsna S.;Castronovo, Denise A.;Monchak, Jim;Naumova, Elena N.
通讯作者：
Naumova, Elena N.