A multi-cancer early detection blood test using machine learning detects early-stage cancers lacking USPSTF-recommended screening
Janet L. Vittone, David Gill, Alex Goldsmith, Eric A. Klein, Jordan J. Karlitz
Abstract
US Preventive Services Task Force (USPSTF) guidelines recommend single-cancer screening for select cancers (e.g., breast, cervical, colorectal, lung). Advances in genome sequencing and machine learning have facilitated the development of blood-based multi-cancer early detection (MCED) tests intended to complement single-cancer screening. MCED tests can interrogate circulating cell-free DNA to detect a shared cancer signal across multiple tumor types. We report real-world experience with an MCED test that detected cancer signals in three individuals subsequently diagnosed with cancers of the ovary, kidney, and head/neck that lack USPSTF-recommended screening. These cases illustrate the potential of MCED tests to detect early-stage cancers amenable to cure.