Identifying core outcome sets in COVID-19 clinical trials using

Irena Parvanova, Joseph Finkelstein

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations


Introduction of core outcome sets (COS) facilitates evidence synthesis, transparency in outcome reporting, and standardization in clinical research. However, development of COS may be a time consuming and expensive process. Publicly available repositories, such as (CTG), provide access to a vast collection of clinical trial characteristics including primary and secondary outcomes, which can be analyzed using a comprehensive set of tools. With growing number of COVID-19 clinical trials, COS development may provide crucial means to standardize, aggregate, share, and analyze diverse research results in a harmonized way. This study was aimed at initial assessment of utility of CTG analytics for identifying COVID-19 COS. At the time of this study, January, 2021, we analyzed 120 ongoing NIH-funded COVID-19 clinical trials initiated in 2020 to inform COVID-19 COS development by evaluating and ranking clinical trial outcomes based on their structured representation in CTG. Using this approach, COS comprised of 25 major clinical outcomes has been identified with mortality, mental health status, and COVID-19 antibodies at the top of the list. We concluded that CTG analytics can be instrumental for COVID-19 COS development and that further analysis is warranted including broader number of international trials combined with more granular approach and ontology-driven pipelines for outcome extraction and curation.

Original languageEnglish
Title of host publicationPublic Health and Informatics
Subtitle of host publicationProceedings of MIE 2021
PublisherIOS Press
Number of pages2
ISBN (Electronic)9781643681856
ISBN (Print)9781643681849
StatePublished - 1 Jul 2021


  • Big data
  • COVID-19
  • Core outcome sets


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