Artificial Intelligence Tool for Optimizing Eligibility Screening for Clinical Trials in a Large Community Cancer Center
Artificial Intelligence Tool for Optimizing Eligibility Screening for Clinical Trials in a Large Community Cancer Center
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DOI：
10.1200/cci.19.00079
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发表时间：
2020-01-24
影响因子：
4.2
通讯作者：
Vinegra, Michael
中科院分区：
文献类型：
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作者：
Beck, J. Thaddeus;Rammage, Melissa;Vinegra, Michael
不到5%的癌症患者参加了临床试验，五分之一的试验因不良累积而停止。我们评估了一个自动化的临床试验匹配系统，该系统使用自然语言处理从非结构化来源和机器学习中提取患者和试验特征，以将患者与临床试验进行匹配。患者和方法2016年5月至8月期间，在高地肿瘤组对997例乳腺癌患者的病历进行了试验资格评估。使用239例患者和4项试验的一致率比较系统和手动属性提取和合格性确定。系统生成的资格测定的灵敏度和特异性进行了测量，并进行了人工审查和系统辅助的资格determinations.Results之间的系统和手动属性提取的协议所需的时间进行了比较，从64.3%到94.0%。系统和手动合格性确定之间的一致性为81%-96%。系统合格性确定显示特异性在76%至99%之间，3项试验的灵敏度在91%至95%之间，第4项试验的灵敏度为46.7%。手动筛选90例患者的3项试验需要110分钟;系统辅助的资格确定相同的患者为相同的trials required 24 minutes.CONCLUSION在这项研究中，临床试验匹配系统显示出良好的性能在筛选乳腺癌患者的试验资格。系统辅助的试验合格性确定比人工审查快得多，并且该系统可靠地排除了所有试验的不合格患者，并确定了大多数试验的合格患者。
PURPOSE Less than 5% of patients with cancer enroll in clinical trials, and 1 in 5 trials are stopped for poor accrual. We evaluated an automated clinical trial matching system that uses natural language processing to extract patient and trial characteristics from unstructured sources and machine learning to match patients to clinical trials.PATIENTS AND METHODS Medical records from 997 patients with breast cancer were assessed for trial eligibility at Highlands Oncology Group between May and August 2016. System and manual attribute extraction and eligibility determinations were compared using the percentage of agreement for 239 patients and 4 trials. Sensitivity and specificity of system-generated eligibility determinations were measured, and the time required for manual review and system-assisted eligibility determinations were compared.RESULTS Agreement between system and manual attribute extraction ranged from 64.3% to 94.0%. Agreement between system and manual eligibility determinations was 81%-96%. System eligibility determinations demonstrated specificities between 76% and 99%, with sensitivities between 91% and 95% for 3 trials and 46.7% for the 4th. Manual eligibility screening of 90 patients for 3 trials took 110 minutes; system-assisted eligibility determinations of the same patients for the same trials required 24 minutes.CONCLUSION In this study, the clinical trial matching system displayed a promising performance in screening patients with breast cancer for trial eligibility. System-assisted trial eligibility determinations were substantially faster than manual review, and the system reliably excluded ineligible patients for all trials and identified eligible patients for most trials.