For example, lung cancer--the world’s #1 cancer killer--has survival rates that exceed 90% when detected early, according to a landmark study published in the New England Journal of Medicine. On the other hand, lung cancers detected in late stages (stage IVb) have survival rates that fall below 1% according to the American Cancer Society. Dozens of similar studies have concluded similar patterns of outcomes for pancreatic, colon, kidney, ovarian, and most other tumor types. Early detection offers substantial survival benefits. The biomarkers measured as part of OneTest™ (AFP, CEA, PSA, CA 19-9, CA 125, CA 15-3, and CYFRA 21-1) are associated with the presence of different malignancies and have the potential to detect cancers in asymptomatic persons when cancers are in early development and may have better outcomes. See Accuracy, Reliability, & Scientific Support.
One's risk of developing cancer increases significantly with age. Persons may also have elevated risk due to other factors, such as family history or who have occupational exposure to toxic carcinogens.
Frequency of testing is a function of age, family history of cancer, and environment/occupational exposures. For most middle-aged individuals, annual testing is suggested.
Studies have shown that significant changes in biomarker levels can be observed years before a cancer diagnosis is made. Annual testing may help identify changes in biomarkers which may be due to a developing tumor.
Health experts in countries where biomarker cancer screening is commonplace believe that yearly testing is an optimal way to improve early stage detection rates.
OneTest™ is a blood test and machine learning algorithm developed to aid in the detection of multiple cancers.
The foundation of OneTest™ is a panel of protein biomarkers. Unlike genetic tests that predict your lifetime risk of getting cancer, OneTest™ measures current cancer markers (tumor-associated proteins secreted by tumors as they grow).
These biomarkers have been widely used for cancer screening outside of the U.S., especially in the Far East (Japan, South Korea, China) for decades. In that region, tens of millions of individuals receive what are often day-long health check-ups that include blood tests that measure the levels of the same biomarkers that are part of OneTest™.
The OneTest™ algorithm was built using machine learning to interpret real-world data from over 27,000 individuals. The algorithm significantly improves the interpretation of tumor biomarker data allowing for enhanced prediction of cancer risk.