Trialstreamer: A living, automatically updated database of clinical trial reports.
Trialstreamer: A living, automatically updated database of clinical trial reports.
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DOI：
10.1093/jamia/ocaa163
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发表时间：
2020-12-09
期刊：
影响因子：
--
通讯作者：
Wallace BC
中科院分区：
文献类型：
--
作者：
Marshall IJ;Nye B;Kuiper J;Noel-Storr A;Marshall R;Maclean R;Soboczenski F;Nenkova A;Thomas J;Wallace BC
随机对照试验（RCT）是评估治疗是否在医疗保健中有效的金标准方法，但很难找到和使用。我们描述了一个系统的开发和评估，自动查找和分类所有新的RCT报告。Trialstreamer持续监测PubMed和世界卫生组织国际临床试验注册平台，使用经过验证的分类器寻找新的人体RCT。我们结合联合收割机和基于规则的方法从RCT摘要中提取信息，包括试验皮科（人群、干预/对照药物和结局）元素的自由文本描述，并将这些片段映射到标准化的MeSH（医学主题词）词汇术语。我们还确定样本量，预测偏倚风险，并提取传达关键发现的文本。我们将所有提取的数据存储在数据库中，我们可以免费下载，并通过搜索门户网站，允许用户输入结构化的临床查询。结果自动排序，以优先考虑更大和更高质量的研究。截至2020年6月初，我们共检索了673 191篇RCT出版物，其中22 363篇发表于2020年前5个月（每天142篇）。我们还包括来自国际临床试验注册平台的304 111项试验注册。中位试验样本量为66。我们提出了一个自动化系统，用于查找和分类RCT。这产生了一个新的资源：一个结构化信息的数据库，自动提取所有已发表的人类随机对照试验。我们在我们的网站（https：//www.example.com）上提供该数据库的每日更新。trialstreamer.robotreviewer.net
Randomized controlled trials (RCTs) are the gold standard method for evaluating whether a treatment works in health care but can be difficult to find and make use of. We describe the development and evaluation of a system to automatically find and categorize all new RCT reports. Trialstreamer continuously monitors PubMed and the World Health Organization International Clinical Trials Registry Platform, looking for new RCTs in humans using a validated classifier. We combine machine learning and rule-based methods to extract information from the RCT abstracts, including free-text descriptions of trial PICO (populations, interventions/comparators, and outcomes) elements and map these snippets to normalized MeSH (Medical Subject Headings) vocabulary terms. We additionally identify sample sizes, predict the risk of bias, and extract text conveying key findings. We store all extracted data in a database, which we make freely available for download, and via a search portal, which allows users to enter structured clinical queries. Results are ranked automatically to prioritize larger and higher-quality studies. As of early June 2020, we have indexed 673 191 publications of RCTs, of which 22 363 were published in the first 5 months of 2020 (142 per day). We additionally include 304 111 trial registrations from the International Clinical Trials Registry Platform. The median trial sample size was 66. We present an automated system for finding and categorizing RCTs. This yields a novel resource: a database of structured information automatically extracted for all published RCTs in humans. We make daily updates of this database available on our website (https://trialstreamer.robotreviewer.net).
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DOI：
10.1093/database/bay079
发表时间：
2018-01-01
期刊：
Database : the journal of biological databases and curation
影响因子：
--
作者：
Cohen AM;Dunivin ZO;Smalheiser NR
通讯作者：
Smalheiser NR
DOI：
10.1093/jamia/ocv044
发表时间：
2016-01-01
影响因子：
6.4
作者：
Marshall, Iain J.;Kuiper, Joel;Wallace, Byron C.
通讯作者：
Wallace, Byron C.
影响因子：
15.8
作者：
Bastian H;Glasziou P;Chalmers I
通讯作者：
Chalmers I
影响因子：
7.2
作者：
Steyerberg, EW;Harrell, FE;Habbema, JDF
通讯作者：
Habbema, JDF
DOI：
10.1093/jamia/ocx053
发表时间：
2017-11-01
影响因子：
6.4
作者：
Wallace, Byron C.;Noel-Storr, Anna;Thomas, James
通讯作者：
Thomas, James