Landscape of coronavirus disease 2019 clinical trials: New frontiers and challenges. (October 2022)

• Record Type: Journal Article
• Authors: Halabi, Susan; Zhou, Jinyi; He, Yijie; Bressler, Linda R; Hernandez, Adrian F; Turner, Nicholas A; Hong, Hwanhee
• Is Part Of: Clinical trials. Volume 19:Number 5(2022)
• Page Start: 561
• Page End: 572
• Publication Date: 2022-10
• Subjects: COVID-19 -- phase III clinical trials -- endpoints -- treatment -- design -- platform; 615.5072405
• DOI: 10.1177/17407745221105106
• Languages: English
• ISSNs: 1740-7745

Abstract

Background/Aim: The number of coronavirus disease 2019 deaths and cases continues to increase globally. Novel therapies are urgently needed to treat patients with coronavirus disease 2019. We sought to provide a critical review of trials designed during the coronavirus disease 2019 pandemic. Our primary goal was to provide a critical review of the landscape of clinical trials designed to address the coronavirus disease 2019 pandemic. Specifically, we were interested in assessing the design of phase II/III and phase III interventional trials. Methods: We utilized the ClinicalTrials.gov database to include trials registered between 1 December 2019 and 11 April 2021 to survey the current landscape of clinical trials for coronavirus disease 2019. Variables extracted included: National Clinical Trial number, title, location, sponsor, study type, start date, completion date, gender group, age group, primary outcome, secondary outcome, overall status, and associated references. Results: About 57% of studies were interventional, 14.5% were phase III trials, and the majority of the therapeutic trials included hospitalized patients. There were 52 primary composite outcomes and 285 unique interventions spanning 10 drug classes. The outcomes, disease severity, and comparators varied substantially across trials, and the trials were often too small to be definitive. Conclusion: These findings are relevant as we strongly advocate for global coordination of efforts through the use of common platforms that enable harmonizing of endpoints, collection of common key variables and clear definition of disease severity to have clinically meaningful results from clinical trials.