数字治疗临床试验的特征：基于自然语言处理的系统评价。
Characterisation of digital therapeutic clinical trials: a systematic review with natural language processing.
机构信息
Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.
Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.
出版信息
Lancet Digit Health. 2024 Mar;6(3):e222-e229. doi: 10.1016/S2589-7500(23)00244-3.
Digital therapeutics (DTx) are a somewhat novel class of US Food and Drug Administration-regulated software that help patients prevent, manage, or treat disease. Here, we use natural language processing to characterise registered DTx clinical trials and provide insights into the clinical development landscape for these novel therapeutics. We identified 449 DTx clinical trials, initiated or expected to be initiated between 2010 and 2030, from ClinicalTrials.gov using 27 search terms, and available data were analysed, including trial durations, locations, MeSH categories, enrolment, and sponsor types. Topic modelling of eligibility criteria, done with BERTopic, showed that DTx trials frequently exclude patients on the basis of age, comorbidities, pregnancy, language barriers, and digital determinants of health, including smartphone or data plan access. Our comprehensive overview of the DTx development landscape highlights challenges in designing inclusive DTx clinical trials and presents opportunities for clinicians and researchers to address these challenges. Finally, we provide an interactive dashboard for readers to conduct their own analyses.
数字疗法（DTx）是一类较为新颖的美国食品和药物管理局监管软件，可帮助患者预防、管理或治疗疾病。在这里，我们使用自然语言处理来描述已注册的 DTx 临床试验，并深入了解这些新型疗法的临床开发情况。我们使用 27 个搜索词从 ClinicalTrials.gov 中确定了 449 项 DTx 临床试验，这些试验计划于 2010 年至 2030 年间启动或预期启动，并对可用数据进行了分析，包括试验持续时间、地点、MeSH 类别、入组情况和赞助商类型。使用 BERTopic 对入选标准进行主题建模的结果表明，DTx 试验经常根据年龄、合并症、妊娠、语言障碍以及智能手机或数据计划访问等数字健康决定因素排除患者。我们对 DTx 开发情况的全面概述突出了设计包容性 DTx 临床试验所面临的挑战，并为临床医生和研究人员提供了应对这些挑战的机会。最后，我们为读者提供了一个交互式仪表板，供其进行自己的分析。
Zotero 插件