Visualization analysis of the characteristics of COVID-19 clinical trial
Abstract Objectives: This article points out the characteristics and trends of COVID-19 clinical trials through data collection, translation, mining and visualization to help in clinical trial design.Method: The registered data of COVID-19 clinical trials are gathered from the Chinese Clinical Trial Registry and ClinicalTrials.gov website transformed by Python, further demonstrated by visual tools.Results: As of 24:00 on March 28, 2020, totally 732 trial registration records have been retrieved. Overall, there are 406 (55.46%) interventional studies and 271 (37.02%) observational studies. Among interventional studies, 38.93% are randomized parallel trials, 55 (13.55%) trials considered time condition for clinical recovery as the primary endpoint, and 46 (11.33%) trials through clinical parameters and laboratory index as the primary endpoint. In the selection of intervention measures, chemical or biological agents was under the responsibility of 43.60%, of which antivirals accounted for 14.53%, antimalarials accounted for 8.87%, and 98 cases (24.14%) of studies involving Traditional Chinese Medicine or Integrated Medicine. In addition, joint network analysis of antivirals to explore the combination of drugs is further conducted.Conclusions: By Mining characteristic information of topical COVID-19 clinical trial registration, this article deserves further trial design ideas for researchers to enhance the effects.