European journal of cancer (Oxford, England : 1990) · 2026
Longitudinal analysis of circulating tumor DNA and CA19-9 dynamics in predicting disease relapse and monitoring treatment response in stage I-III pancreatic ductal adenocarcinoma: An interim analysis of a prospective observational study.
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Zou Siyi, Li Fanlu, Xu Li-Di, Zhang Jiao, Qian Juanjuan, Tian Qiang, Liu Di, Jiang Cen, Shen Baiyong, Wen Chenlei, Zhan Qian
Аннотация
INTRODUCTION: Postoperative recurrence is the leading cause of mortality in resected pancreatic ductal adenocarcinoma (PDAC), yet reliable tools for early relapse detection and treatment response assessment remain lacking.
METHODS: In a prospective cohort of 136 patients with resected stage I-III PDAC receiving adjuvant chemotherapy, we evaluated circulating tumor DNA (ctDNA) and CA19-9 as longitudinal biomarkers across multiple postoperative time windows.
RESULTS: ctDNA consistently outperformed CA19-9 as an independent prognostic factor; ctDNA positivity at on-treatment and surveillance assessments achieved a positive predictive value of 91.7%, while persistent negativity identified the lowest-risk patients. Integrating CA19-9 with ctDNA resolved the ctDNA-alone gap in distinguishing treatment clearance from conversion, improving discrimination of responders from non-responders (HR 3.72; P = .008). A time-weighted dynamic ctDNA risk score (MinerVa-dynamic) further stratified ctDNA-negative patients into clinically distinct prognostic subgroups, achieving an area under the curve of 0.87 and 0.82 for one- and two-year disease-free survival prediction, respectively.
CONCLUSIONS: These findings support a dual-biomarker longitudinal monitoring framework as a practical, individualized approach to postoperative surveillance and early therapeutic decision-making in PDAC.
METHODS: In a prospective cohort of 136 patients with resected stage I-III PDAC receiving adjuvant chemotherapy, we evaluated circulating tumor DNA (ctDNA) and CA19-9 as longitudinal biomarkers across multiple postoperative time windows.
RESULTS: ctDNA consistently outperformed CA19-9 as an independent prognostic factor; ctDNA positivity at on-treatment and surveillance assessments achieved a positive predictive value of 91.7%, while persistent negativity identified the lowest-risk patients. Integrating CA19-9 with ctDNA resolved the ctDNA-alone gap in distinguishing treatment clearance from conversion, improving discrimination of responders from non-responders (HR 3.72; P = .008). A time-weighted dynamic ctDNA risk score (MinerVa-dynamic) further stratified ctDNA-negative patients into clinically distinct prognostic subgroups, achieving an area under the curve of 0.87 and 0.82 for one- and two-year disease-free survival prediction, respectively.
CONCLUSIONS: These findings support a dual-biomarker longitudinal monitoring framework as a practical, individualized approach to postoperative surveillance and early therapeutic decision-making in PDAC.