The National COVID Cancer Antibody Survey: a hyper-accelerated study proof of principle for cancer research

Journal article

The COVID-19 pandemic has led to a range of novel and adaptive research designs. In this perspective, we use our experience coordinating the National COVID Cancer Antibody Survey to demonstrate how a balance between speed and integrity can be achieved within a hyper-accelerated study design. Using the COVID-19 pandemic as an example, we show this approach is necessary in the face of uncertain and evolving situations wherein reliable information is needed in a timely fashion to guide policy. We identify streamlined participant involvement, healthcare systems integration, data architecture and real-world real-time analytics as key areas that differentiate this design from traditional cancer trials, and enable rapid results. Caution needs to be taken to avoid the exclusion of patient subgroups without digital access or literacy. We summarise the merits and defining features of hyper-accelerated cancer studies.Accepted version (6 month embargo), submitted versionThe article is available via Open Access. Click on the 'Additional link' above to access the full-text

Authors: Fittall, M; Liu, J; Platt, J; Ionescu, M; Sheehan, R

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Springer Nature [academic journals on nature.com]
• Journal: British Journal of Cancer
• Volume: 128
• Issue: 11
• Pages: 1977-1980
• Publication date: 2023-04-20
• DOI: 10.1038/s41416-023-02251-9
• EISSN: 1532-1827
• ISSN: 0007-0920
• Language: English
• Keywords: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Proof of concept; Artificial intelligence; Coronavirus disease 2019 (COVID-19); Virology; Perspective (graphical); Data science; Pandemic; 2019-20 coronavirus outbreak; Analytics; Cancer; Medicine; Disease; Computer science; Pathology