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Standardized representation, visualization and searchable repository of antiretroviral treatment-change episodes

机译:抗逆转录病毒治疗变化事件的标准化表示,可视化和可搜索的存储库

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Background To identify the determinants of successful antiretroviral (ARV) therapy, researchers study the virological responses to treatment-change episodes (TCEs) accompanied by baseline plasma HIV-1 RNA levels, CD4+ T lymphocyte counts, and genotypic resistance data. Such studies, however, often differ in their inclusion and virological response criteria making direct comparisons of study results problematic. Moreover, the absence of a standard method for representing the data comprising a TCE makes it difficult to apply uniform criteria in the analysis of published studies of TCEs. Results To facilitate data sharing for TCE analyses, we developed an XML (Extensible Markup Language) Schema that represents the temporal relationship between plasma HIV-1 RNA levels, CD4 counts and genotypic drug resistance data surrounding an ARV treatment change. To demonstrate the adaptability of the TCE XML Schema to different clinical environments, we collaborate with four clinics to create a public repository of about 1,500 TCEs. Despite the nascent state of this TCE XML Repository, we were able to perform an analysis that generated a novel hypothesis pertaining to the optimal use of second-line therapies in resource-limited settings. We also developed an online program (TCE Finder) for searching the TCE XML Repository and another program (TCE Viewer) for generating a graphical depiction of a TCE from a TCE XML Schema document. Conclusions The TCE Suite of applications – the XML Schema, Viewer, Finder, and Repository – addresses several major needs in the analysis of the predictors of virological response to ARV therapy. The TCE XML Schema and Viewer facilitate sharing data comprising a TCE. The TCE Repository, the only publicly available collection of TCEs, and the TCE Finder can be used for testing the predictive value of genotypic resistance interpretation systems and potentially for generating and testing novel hypotheses pertaining to the optimal use of salvage ARV therapy.
机译:背景技术为了确定成功的抗逆转录病毒(ARV)治疗的决定因素,研究人员研究了对治疗变化发作(TCE)的病毒学应答,并伴有基线血浆HIV-1 RNA水平,CD4 + T淋巴细胞计数和基因型耐药性数据。但是,此类研究的收录和病毒学应答标准经常不同,因此直接比较研究结果存在问题。此外,由于缺乏用于表示包含传统文化表现形式的数据的标准方法,因此难以在已发表的传统文化表现形式研究的分析中应用统一的标准。结果为了促进TCE分析的数据共享,我们开发了XML(可扩展标记语言)架构,该架构表示血浆HIV-1 RNA水平,CD4计数和围绕ARV治疗改变的基因型耐药数据之间的时间关系。为了证明TCE XML Schema对不同临床环境的适应性,我们与四家诊所合作创建了约1,500个TCE的公共存储库。尽管该TCE XML存储库尚处于起步阶段,但我们仍然能够进行分析,从而得出一种与在资源有限的环境中最佳使用第二线疗法有关的新颖假设。我们还开发了一个在线程序(TCE Finder),用于搜索TCE XML存储库,另一个程序(TCE Viewer),用于从TCE XML Schema文档生成TCE的图形表示。结论TCE应用程序套件– XML Schema,Viewer,Finder和Repository –满足了对ARV疗法的病毒学应答预测因子分析中的几个主要需求。 TCE XML模式和查看器有助于共享包含TCE的数据。 TCE信息库(TCE信息库,TCE的唯一公开信息)和TCE Finder可用于测试基因型耐药性解释系统的预测价值,并可能用于生成和测试与挽救ARV疗法的最佳使用有关的新颖假设。

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