AI Article Synopsis
- Pancreatic surveillance, which includes yearly endoscopic ultrasounds and MRI/MRCP, can identify early pancreatic cancer and improve long-term survival, but is limited to those with specific familial or genetic risk factors.
- There is a need for more accurate, affordable, and safer biomarkers for early detection of pancreatic cancer, as current methods have not succeeded in finding them.
- New strategies, like gene tests for personalized biomarker analysis and the use of artificial intelligence to manage complex biomarker data, show potential for developing clinically useful biomarkers for early pancreatic cancer detection.
Article Abstract
Pancreatic surveillance can detect early-stage pancreatic cancer and achieve long-term survival, but currently involves annual endoscopic ultrasound and MRI/MRCP, and is recommended only for individuals who meet familial/genetic risk criteria. To improve upon current approaches to pancreatic cancer early detection and to expand access, more accurate, inexpensive, and safe biomarkers are needed, but finding them has remained elusive. Newer approaches to early detection, such as using gene tests to personalize biomarker interpretation, and the increasing application of artificial intelligence approaches to integrate complex biomarker data, offer promise that clinically useful biomarkers for early pancreatic cancer detection are on the horizon.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11309746 | PMC |
| http://dx.doi.org/10.1007/s10689-024-00381-4 | DOI Listing |
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