Revisiting the standard blueprint for biomarker development to address emerging cancer early detection technologies
Year: 2023
Type: review
Abstract: Novel liquid biopsy technologies are creating a watershed moment in cancer early detection. Evidence supporting population screening is nascent, but a rush to market the new tests is prompting cancer early detection researchers to revisit the standard blueprint that the Early Detection Research Network established to evaluate novel screening biomarkers. In this commentary, we review the Early Detection Research Network's Phases of Biomarker Development (PBD) for rigorous evaluation of novel early detection biomarkers and discuss both hazards and opportunities involved in expedited evaluation. According to the PBD, for a biomarker-based test to be considered for population screening, 1) test sensitivity in a prospective screening setting must be adequate, 2) the shift to early curable stages must be meaningful, and 3) any stage shift must translate into clinically significant mortality benefit. In the past, determining mortality benefit has required lengthy randomized screening trials, but interest is growing in expedited trial designs with shorter-term endpoints. Whether and how best to use such endpoints in a manner that retains the rigor of the PBD remains to be determined. We discuss how computational disease modeling can be harnessed to learn about screening impact and meet the needs of the moment.
DOI: 10.1093/jnci/djad227
Institutions: Fred Hutch Cancer Center, National Cancer Institute
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
Funder: National Cancer Institute
Awards: Statistical modeling to support population and translational cancer research, Modeling and analytics for cancer diagnostics: traversing the data-evidence divide, The Early Detection Research Network: Data Management and Coordinating Center, Accelerating biomarker development through novel statistical methods for analyzing phase III/IV studies
OpenAlex ID: W4388515808
