Towards clinical data-driven eligibility criteria optimization for interventional COVID-19 clinical trials. (1st December 2020)

• Record Type: Journal Article
• Authors: Kim, Jae Hyun; Ta, Casey N; Liu, Cong; Sung, Cynthia; Butler, Alex M; Stewart, Latoya A; Ena, Lyudmila; Rogers, James R; Lee, Junghwan; Ostropolets, Anna; Ryan, Patrick B; Liu, Hao; Lee, Shing M; Elkind, Mitchell S V; Weng, Chunhua
• Is Part Of: Journal of the American Medical Informatics Association. Volume 28:Number 1(2021)
• Page Start: 14
• Page End: 22
• Publication Date: 2020-12-01
• Subjects: real-world data -- clinical trial -- eligibility criteria -- COVID-19, criteria optimization ; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocaa276
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract: Objective: This research aims to evaluate the impact of eligibility criteria on recruitment and observable clinical outcomes of COVID-19 clinical trials using electronic health record (EHR) data. Materials and Methods: On June 18, 2020, we identified frequently used eligibility criteria from all the interventional COVID-19 trials in ClinicalTrials.gov (n = 288), including age, pregnancy, oxygen saturation, alanine/aspartate aminotransferase, platelets, and estimated glomerular filtration rate. We applied the frequently used criteria to the EHR data of COVID-19 patients in Columbia University Irving Medical Center (CUIMC) (March 2020–June 2020) and evaluated their impact on patient accrual and the occurrence of a composite endpoint of mechanical ventilation, tracheostomy, and in-hospital death. Results: There were 3251 patients diagnosed with COVID-19 from the CUIMC EHR included in the analysis. The median follow-up period was 10 days (interquartile range 4–28 days). The composite events occurred in 18.1% (n = 587) of the COVID-19 cohort during the follow-up. In a hypothetical trial with common eligibility criteria, 33.6% (690/2051) were eligible among patients with evaluable data and 22.2% (153/690) had the composite event. Discussion: By adjusting the thresholds of common eligibility criteria based on the characteristics of COVID-19 patients, we could observe more composite events from fewer patients. Conclusions: This research demonstrated the potential of using the EHR data of COVID-19 patients to inform the selection of eligibility criteria and their thresholds, supporting data-driven optimization of participant selection towards improved statistical power of COVID-19 trials.