Department of Medicine, Stanford University, Stanford, CA, USA.
AIDS Res Ther. 2012 May 3;9(1):13. doi: 10.1186/1742-6405-9-13.
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.
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.
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.
为了确定抗逆转录病毒 (ARV) 治疗成功的决定因素，研究人员研究了伴随基线血浆 HIV-1 RNA 水平、CD4+T 淋巴细胞计数和基因型耐药数据的治疗转换期 (TCE) 的病毒学反应。然而，此类研究在纳入和病毒学反应标准方面存在差异，使得研究结果难以直接比较。此外，由于缺乏表示 TCE 数据的标准方法，因此难以在分析已发表的 TCE 研究中应用统一的标准。
为了促进 TCE 分析的数据共享，我们开发了一个 XML（可扩展标记语言）架构，该架构表示 ARV 治疗转换前后血浆 HIV-1 RNA 水平、CD4 计数和基因型药物耐药数据之间的时间关系。为了展示 TCE XML 架构对不同临床环境的适应性，我们与四个诊所合作创建了一个约 1500 个 TCE 的公共存储库。尽管这个 TCE XML 存储库还处于起步阶段，但我们还是能够进行分析，提出了一个关于在资源有限环境中最佳使用二线治疗的新假设。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 架构文档生成 TCE 的图形表示。
TCE 套件应用程序 - XML 架构、Viewer、Finder 和 Repository - 满足了分析 ARV 治疗病毒学反应预测因素的几个主要需求。TCE XML 架构和 Viewer 促进了 TCE 数据的共享。唯一可用的 TCE 公共存储库 TCE 存储库和 TCE Finder 可用于测试基因型耐药解读系统的预测价值，并可能生成和测试有关最佳使用挽救性 ARV 治疗的新假设。
