Case-control and prospective cohort studies reveal promising diagnostic accuracy in detecting pancreatic cancer, suggesting scaling of non-invasive screening.
Pancreatic cancer (PC) remains a highly lethal malignancy due to late-stage diagnosis and limited therapeutic options. This study presents the development and validation of a non-invasive circulating cell-free DNA (cfDNA)-based model for early PC detection. In a case-control study comprising 232 PC patients and 235 healthy controls, the model demonstrated high diagnostic accuracy (AUC=0.9799 in training; 0.9622 in validation). A prospective cohort study involving 1,926 individuals with diabetes and obesity, established risk factors for PC, further assessed its clinical applicability. The model detected 75% of PC cases, including all Stage 0 patients, with a lead time of up to 298 days, significantly outperforming CA19-9. Additionally, it demonstrates potential for distinguishing high-risk from low-risk pancreatic cysts, thereby facilitating more precise risk stratification. This study highlights the potential of cfDNA-based screening as a scalable, non-invasive tool for early PC detection, warranting further large-scale clinical validation to enhance patient outcomes.
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Wang et al. (2025) studied this question.
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