Frequency Analysis of Medical Concepts in Clinical Trials and their Coverage in MeSH and SNOMED-CT
Frequency Analysis of Medical Concepts in Clinical Trials and their Coverage in MeSH and SNOMED-CT
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临床试验中医学概念的频率分析及其在 MeSH 和 SNOMED-CT 中的覆盖范围
DOI：
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发表时间：
2014
影响因子：
1.7
通讯作者：
M. Dugas
中科院分区：
文献类型：
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作者：
J. Varghese;M. Dugas
摘要背景：临床试验的资格标准(EC)在选择合适的研究候选者和临床试验结果的有效性方面起着关键作用。然而，在大多数情况下，EC是以自由文本等非标准化的方式提供的，这给机器可读性带来了巨大的挑战。目的：建立临床试验中最常用的带语义标注的医学概念列表。这份概念清单有助于EC的标准化，并确定用于临床研究的电子健康记录(EHR)中的相关数据项。将评估该清单在两个主要临床词汇表-MESH和SNOMED-CT中的覆盖面。方法：对2000年至2011年间在德国一所大学医院进行的425项临床试验进行分析。6671个EC由医学编码者使用由统一医学语言系统提供的概念唯一识别符(CUI)手动标注。两名医生进行了半自动CUI代码修订。分析概念频度，人工识别概念簇，用二项式显著性检验量化Mesh和SNOMED-CT中最常用概念的复盖率差异。结果：基于425项临床试验的人工医学编码，识别出7588个概念，其中5236个概念是明确的。建立了一份包含101个最常见的医学概念的前100名名单。这个列表的概念覆盖了所有分析的临床试验中出现的所有概念的25%。该列表显示SNOMED-CT中缺少6个条目，MESH中缺少12个条目。每个试验的EC频率的中位数在整个试验年份都有所增加(2000-2005年：8个EC/试验，2011年：14个EC/试验)。结论：在最近的研究中，相对较少的概念覆盖了四分之一的代表EC的概念发生。因此，这些概念可以作为候选数据元素集成到EHR中，以优化临床研究中的患者招募。
Summary Background: Eligibility criteria (EC) of clinical trials play a key role in selecting appropriate study candidates and the validity of the outcome of a clinical trial. However, in most cases EC are provided in unstandardised ways such as free text, which raises significant challenges for machine-readability. Objectives: To establish a list of most frequent medical concepts in clinical trials with semantic annotations. This concept list contributes to standardisation of EC and identifies relevant data items in electronic health records (EHRs) for clinical research. The coverage of the list in two major clinical vocabularies, MeSH and SNOMED-CT, will be assessed. Methods: Four hundred and twenty-fivec linical trials conducted between 2000 and 2011 at a German university hospital were analysed. 6671 EC were manually annotated by a medical coder using Concept Unique Identifiers (CUIs) provided by the Unified Medical Language System. Two physicians performed a semi-automatic CUI code revision. Concept frequency was analysed and clusters of concepts were manually identified.A binomial significance test was applied to quantify coverage differences of the most frequent concepts in MeSH and SNOMED-CT. Results: Based on manual medical coding of 425 clinical trials, 7588 concepts were identified, of which 5236 were distinct. A top 100 list containing 101 most frequent medical concepts was established. The concepts of this list cover 25 % of all concept occur-rences in all analysed clinical trials. This list reveals six missing entries in SNOMED-CT, 12 in MeSH. The median of EC frequency per trial has increased throughout the trial years (2000 –2005: 8 EC/trial, 2011: 14 EC/ trial). Conclusions: Relatively few concepts cover one quarter of concept occurrences that represent EC in recent studies. Therefore, these concepts can serve as candidate data elements for integration into EHRs to optimise patient recruitment in clinical research.
基于 UMLS 的医疗表格自动比较
影响因子：
3.7
作者：
M. Dugas;F. Fritz;R. Krumm;B. Breil
通讯作者：
B. Breil