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A multi-cancer early detection blood test using machine learning detects early-stage cancers lacking USPSTF-recommended screening.
Vittone, Janet; Gill, David; Goldsmith, Alex; Klein, Eric A; Karlitz, Jordan J.
Afiliação
  • Vittone J; Mayo Clinic, Rochester, Minnesota, USA.
  • Gill D; Intermountain Healthcare, Salt Lake City, UT, USA.
  • Goldsmith A; Colorado Center of Medical Excellence, Denver, CO, USA.
  • Klein EA; GRAIL, LLC, Menlo Park, CA, USA.
  • Karlitz JJ; GRAIL, LLC, Menlo Park, CA, USA. jkarlitz@grailbio.com.
NPJ Precis Oncol ; 8(1): 91, 2024 Apr 17.
Article em En | MEDLINE | ID: mdl-38632333
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.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article