Cancer Blood Test Faces Setback: Early Detection Hopes Dimmed

GRAIL's ambitious Galleri blood test, aimed at detecting over 50 cancer types early, faced a significant hurdle. A three-year trial with 142,000 individuals aged 50-77, where half received the Galleri screening alongside standard tests, did not achieve its goal of reducing late-stage diagnoses. The full trial results are anticipated in May and may offer a more detailed view of the test's effectiveness for specific cancers and populations. This news impacts the field of early cancer detection, where competitors are also developing novel blood tests. The underlying principle involves analyzing DNA fragments or proteins shed by cancer cells. Galleri, available since 2021, has undergone extensive study, previously showing it could spot about 40% of cancers diagnosed within a year, though with a notable rate of false alarms.

Further analysis of GRAIL's trials suggests potential for detecting cancers earlier than standard methods, as indicated by a study in England where some presumed false alarms were later diagnosed with cancer over an extended follow-up period. A critical question remains whether early detection truly translates to improved survival, especially concerning the identification of slow-growing, harmless tumors that might not require treatment. This echoes concerns raised by the UK's NHS regarding the PSA test for prostate cancer, where overdiagnosis and unnecessary treatments were identified as significant harms. Similarly, a trial for ovarian cancer using the CA125 blood test showed that improved early detection did not necessarily save lives due to the cancer's inherent lethality.

As GRAIL awaits further trial results, indications suggest Galleri's performance may vary across different cancer types. Experts note that GRAIL's current methylation-based DNA analysis method is becoming outdated, as it destroys much of the DNA sample. Newer, more sophisticated tests are emerging, utilizing less destructive methods and scanning the entire genome. These advanced approaches, coupled with AI for data analysis, hold promise for more reliable cancer detection, potentially distinguishing between cancers needing immediate intervention and those that do not.