Thomas W. Wilson, Joseph T. Dye, Sarah Spark, N. Robert, J. Espirito, E. Amirian
{"title":"Feasibility of Using Oncology-Specific Electronic Health Record (EHR) Data to Emulate Clinical Trial Eligibility Criteria","authors":"Thomas W. Wilson, Joseph T. Dye, Sarah Spark, N. Robert, J. Espirito, E. Amirian","doi":"10.3390/pharma2020013","DOIUrl":null,"url":null,"abstract":"We examined eligibility criteria from recent oncology clinical trials to see whether real-world data (RWD) from electronic health records (EHRs) could be used to create external control groups for clinical trials. Trials were identified from the Aggregate Analysis of ClinicalTrials.gov database; the selected trials were for oncology drugs approved by the FDA in 2020. Verbatim text from trial inclusion and exclusion criteria was qualitatively assessed by an expert panel to determine if criteria could be ascertained from structured and unstructured EHR data. Identified criteria were categorized (cancer-related, comorbidity-related, demographic, functional status, and trial operations) and subcategorized. Among 53 identified trials, 20 met the requirements for study inclusion, which included 463 eligibility criteria. Percentages of criteria by category were as follows: cancer-related factors (46%), comorbidities (20%), functional status (18%), trial operations (14%), and demographics (2%). For 18 of the 20 trials, 80% of the eligibility criteria could be ascertained with RWD; for 4 of the 20, it was 100%. When trial operation-specific criteria were excluded, all 20 met the 100% threshold. Our study indicates that both structured and unstructured data from community-based oncology-specific EHRs can be used for determining patient eligibility for external control arms for clinical trials.","PeriodicalId":74431,"journal":{"name":"Pharmacoepidemiology","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pharmacoepidemiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/pharma2020013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We examined eligibility criteria from recent oncology clinical trials to see whether real-world data (RWD) from electronic health records (EHRs) could be used to create external control groups for clinical trials. Trials were identified from the Aggregate Analysis of ClinicalTrials.gov database; the selected trials were for oncology drugs approved by the FDA in 2020. Verbatim text from trial inclusion and exclusion criteria was qualitatively assessed by an expert panel to determine if criteria could be ascertained from structured and unstructured EHR data. Identified criteria were categorized (cancer-related, comorbidity-related, demographic, functional status, and trial operations) and subcategorized. Among 53 identified trials, 20 met the requirements for study inclusion, which included 463 eligibility criteria. Percentages of criteria by category were as follows: cancer-related factors (46%), comorbidities (20%), functional status (18%), trial operations (14%), and demographics (2%). For 18 of the 20 trials, 80% of the eligibility criteria could be ascertained with RWD; for 4 of the 20, it was 100%. When trial operation-specific criteria were excluded, all 20 met the 100% threshold. Our study indicates that both structured and unstructured data from community-based oncology-specific EHRs can be used for determining patient eligibility for external control arms for clinical trials.
我们检查了近期肿瘤临床试验的资格标准,以了解电子健康记录(EHRs)的真实世界数据(RWD)是否可用于创建临床试验的外部对照组。试验从ClinicalTrials.gov数据库的汇总分析(Aggregate Analysis of ClinicalTrials.gov)中确定;所选试验是针对FDA于2020年批准的肿瘤药物。专家小组对试验纳入标准和排除标准的逐字文本进行定性评估,以确定是否可以从结构化和非结构化电子病历数据中确定标准。确定的标准被分类(癌症相关、合并症相关、人口统计学、功能状态和试验手术)和亚分类。在纳入的53项试验中,有20项符合纳入研究的要求,其中包括463项入选标准。分类标准的百分比如下:癌症相关因素(46%)、合并症(20%)、功能状态(18%)、试验手术(14%)和人口统计学(2%)。在20项试验中的18项中,80%的合格标准可以用RWD确定;20个中有4个是100%。当排除试验手术特定标准时,所有20例均达到100%阈值。我们的研究表明,来自社区肿瘤特异性电子病历的结构化和非结构化数据均可用于确定患者是否适合临床试验的外部对照组。