Surgery today · 2026
Redefining biologically borderline resectable pancreatic cancer: a data-driven reassessment of CA19-9 cutoff and a preoperative lymph node metastasis prediction model.
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Yamada Suguru, Oshima Kenji, Nomoto Kosuke, Sanada Shotaro, Oshima Yukiko, Nakao Akimasa
Аннотация
PURPOSES: The IAP resectability classification defines biologically borderline resectable pancreatic cancer using elevated CA19-9 (≥ 500 U/mL) and PET-suspected lymph node (LN) metastasis; however, these criteria have limited clinical applicability. This study aimed to refine the biological dimension of resectability by reassessing the CA19-9 cut-off and developing a preoperative LN metastasis prediction model.
METHODS: We retrospectively analyzed 399 patients with anatomically resectable or borderline resectable pancreatic cancer who underwent surgery at a single institution. The optimal CA19-9 cutoff for disease-specific survival was determined using maximally selected rank statistics. A logistic regression model incorporating pretreatment CA19-9 levels and tumor size was developed to predict LN metastasis. Survival was evaluated using Kaplan-Meier survival analysis.
RESULTS: The maxstat-derived CA19-9 cutoff (133 U/mL) showed superior prognostic discrimination compared to the IAP threshold. Patients with CA19-9 ≥ 133 U/mL had survival rates comparable to those with anatomically borderline resectable disease. Pathological LN metastasis was strongly prognostic, even in anatomically resectable diseases. The LN prediction model demonstrated good discrimination (AUC 0.739), and the highest-risk group showed outcomes equivalent to those of patients with anatomically borderline resectable disease.
CONCLUSION: A data-driven CA19-9 cutoff and preoperative LN prediction model accurately identified biologically high-risk pancreatic cancer, potentially improving risk stratification for neoadjuvant therapy.
METHODS: We retrospectively analyzed 399 patients with anatomically resectable or borderline resectable pancreatic cancer who underwent surgery at a single institution. The optimal CA19-9 cutoff for disease-specific survival was determined using maximally selected rank statistics. A logistic regression model incorporating pretreatment CA19-9 levels and tumor size was developed to predict LN metastasis. Survival was evaluated using Kaplan-Meier survival analysis.
RESULTS: The maxstat-derived CA19-9 cutoff (133 U/mL) showed superior prognostic discrimination compared to the IAP threshold. Patients with CA19-9 ≥ 133 U/mL had survival rates comparable to those with anatomically borderline resectable disease. Pathological LN metastasis was strongly prognostic, even in anatomically resectable diseases. The LN prediction model demonstrated good discrimination (AUC 0.739), and the highest-risk group showed outcomes equivalent to those of patients with anatomically borderline resectable disease.
CONCLUSION: A data-driven CA19-9 cutoff and preoperative LN prediction model accurately identified biologically high-risk pancreatic cancer, potentially improving risk stratification for neoadjuvant therapy.