Department of Biomedical Informatics, Columbia University, New York, New York.
Medical Informatics Services, New York-Presbyterian Hospital, New York, New York.
JAMA Netw Open. 2021 Apr 1;4(4):e214732. doi: 10.1001/jamanetworkopen.2021.4732.
Assessing generalizability of clinical trials is important to ensure appropriate application of interventions, but most assessments provide minimal granularity on comparisons of clinical characteristics.
To assess the extent of underlying clinical differences between clinical trial participants and nonparticipants by using a combination of electronic health record and trial enrollment data.
DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used data obtained from a single academic medical center between September 1996 and January 2019 to identify 1645 clinical trial participants from a diverse set of 202 available trials conducted at the center. Using an aggregated resampling procedure, nonparticipants were matched to participants 1:1 based on trial conditions, number of recent visits to a health care professional, and calendar time.
Clinical trial enrollment vs no enrollment.
The primary outcome was standardized differences in clinical characteristics between participants and nonparticipants in clinical trials stratified into the 4 most common disease domains.
This cross-sectional study included 1645 participants from 202 trials (929 [56.5%] male; mean [SD] age, 54.65 [21.38] years) and an aggregated set of 1645 nonparticipants (855 [52.0%] male; mean [SD] age, 57.24 [21.91] years). The most common disease domains for the selected trials were neoplastic disease (86 trials; 737 participants), disorders of the digestive system (31 trials; 321 participants), inflammatory disorders (28 trials; 276 participants), and disorders of the cardiovascular system (27 trials; 319 participants); trials could qualify for multiple disease domains. Among 31 conditions, the percentage of conditions for which the prevalence was lower among participants than among nonparticipants per standardized differences was 64.5% (20 conditions) for neoplastic disease trials, 61.3% (19) for digestive system trials, 58.1% (18) for inflammatory disorder trials, and 38.7% (12) for cardiovascular system trials. Among 17 medications, the percentage of medications for which use was less among participants than among nonparticipants per standardized differences was 64.7% (11) for neoplastic disease trials, 58.8% (10) for digestive system trials, 88.2% (15) for inflammatory disorder trials, and 52.9% (9) for cardiovascular system trials.
Using a combination of electronic health record and trial enrollment data, this study found that clinical trial participants had fewer comorbidities and less use of medication than nonparticipants across a variety of disease domains. Combining trial enrollment data with electronic health record data may be useful for better understanding of the generalizability of trial results.
评估临床试验的可推广性对于确保干预措施的适当应用非常重要,但大多数评估方法对临床特征的比较提供的粒度都非常有限。
使用电子病历和试验登记数据的组合来评估临床试验参与者和非参与者之间潜在临床差异的程度。
设计、地点和参与者:这项横断面研究使用了 1996 年 9 月至 2019 年 1 月期间从一家学术医疗中心获得的数据,从该中心开展的 202 项可用试验中确定了 1645 名来自不同试验的临床试验参与者。使用聚合重采样程序,根据试验条件、最近去医疗保健专业人员就诊的次数和日历时间,将非参与者与参与者 1:1 进行匹配。
临床试验登记与未登记。
主要结局是根据最常见的 4 个疾病领域对临床试验参与者和非参与者的临床特征进行分层,评估标准化差异。
这项横断面研究包括了 202 项试验中的 1645 名参与者(929 [56.5%] 名男性;平均[标准差]年龄 54.65 [21.38] 岁)和一组聚合的 1645 名非参与者(855 [52.0%] 名男性;平均[标准差]年龄 57.24 [21.91] 岁)。所选试验最常见的疾病领域是肿瘤疾病(86 项试验;737 名参与者)、消化系统疾病(31 项试验;321 名参与者)、炎症性疾病(28 项试验;276 名参与者)和心血管系统疾病(27 项试验;319 名参与者);试验可以符合多个疾病领域。在 31 种疾病中,标准化差异显示,参与者比非参与者更易患的疾病的比例为 64.5%(20 种疾病),肿瘤疾病试验;61.3%(19 种),消化系统疾病试验;58.1%(18 种),炎症性疾病试验;38.7%(12 种),心血管系统疾病试验。在 17 种药物中,标准化差异显示,参与者比非参与者更少使用药物的药物的比例为 64.7%(11 种),肿瘤疾病试验;58.8%(10 种),消化系统疾病试验;88.2%(15 种),炎症性疾病试验;52.9%(9 种),心血管系统疾病试验。
使用电子病历和试验登记数据的组合,本研究发现,在各种疾病领域,临床试验参与者的合并症和药物使用均少于非参与者。将试验登记数据与电子病历数据相结合,可能有助于更好地理解试验结果的可推广性。