Layman’s abstract for Pharmaceutical Statistics article on Just say no to data listings!

Each week, we publish layman’s abstracts of new articles from our prestigious portfolio of journals in statistics. The aim is to highlight the latest research to a broader audience in an accessible format.
The article featured today is from Pharmaceutical Statistics with the full article now available to read here.
Navarro, MBrucken, NYang, ABall, GJust say no to data listings!Pharmaceutical Statistics20231– 4. doi:10.1002/pst.2286

Sponsor companies often create voluminous static listings for Clinical Study Reports (CSRs) and regulatory submissions, and possibly for internal use to review participant-level data. The 1995 ICH E3 Harmonized Guideline, “Structure and Content of Clinical Study Reports” outlines the recommended data displays to include in CSR Sections 14 and 16, and is often cited as justification for production of complete sets of static clinical study data listings. However, ICH E3 was published before widespread use of interactive data review tools, both internally within sponsor companies and by regulatory agencies, and before submission of electronic study data to regulatory agencies took effect. At the present time, there are other ways of viewing clinical study data that can provide an improved user experience, and are made possible by standard data structures such as the Study Data Tabulation Model (SDTM). The purpose of this article is to explore some alternatives to providing a complete set of static listings and make a case for sponsors to begin considering these alternatives. Reviewing a stack of printed listings is a tedious process that provides relatively little insight.  Interactive data exploration can help to identify issues faster and to drill down for more information, gaining a better understanding of the data.  In addition, visual analytics enables cross-functional teams to carry out collective assessments of data instead of compartmentalized reviews of static data, thereby improving the information flow and efficiency of the process. Statisticians can work closely with clinicians to explore, review, analyze, and report on the data. 

Acknowledgments: The authors would like to thank the following members of the PHUSE Safety Analytics Working Group for their contributions: Maria Dalton, Anna Leath, Kim Musgrave and Mary Nilsson. 

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