Beyond sensitivity and specificity: Redefining the era connotation of “low-risk” in pancreatic cancer screening

Abstract

Pancreatic cancer remains a highly lethal malignancy, primarily due to late-stage diagnosis. Current screening paradigms, which focus exclusively on high-risk individuals, leave the vast “low-risk” population unscreened. This conventional binary risk stratification, based predominantly on family history and known genetic syndromes, fails to incorporate emerging risk dimensions such as polygenic risk scores, lifestyle factors, and novel biomarkers. We propose a paradigm shift from this static model towards a dynamic, multidimensional risk stratification framework. By integrating genetic susceptibility (e.g., newly identified variants in NOC2L, HNF4G), lifestyle metrics (e.g., new-onset diabetes), and liquid biopsy biomarkers (e.g., circulating tumor DNA, carbohydrate antigen 19-9 dynamics), we can reclassify a subset of “low-risk” individuals who may benefit from targeted screening. The integration of artificial intelligence for prospective validation, as seen in ongoing trials, is crucial for implementing this approach.

Keywords: Pancreatic cancer screening; Low-risk redefinition; Dynamic risk stratification; Precision prevention; Multimodal integration

Core Tip: This commentary argues that the conventional “low-risk” label for pancreatic cancer, based solely on family history and known genetic syndromes, is obsolete. We propose a paradigm shift towards a dynamic, multidimensional risk model. This framework continuously integrates polygenic risk scores, liquid biopsy biomarkers (e.g., circulating tumor DNA), lifestyle factors, and artificial intelligence to enable real-time, personalized risk stratification. This approach can reclassify a significant portion of the “low-risk” population, paving the way for precision screening and potentially transforming early detection strategies for this lethal malignancy.