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| Development and multicenter validation of a nomogram for preoperative prediction of lymph node positivity in pancreatic cancer (NeoPangram) |
| Jie Hua a , b , c , # , Xue-Min Chen d , # , Yun-Jie Chen e , # , Bao-Chun Lu f , # , Jin Xu a , b , c , Wei Wang a , b , c , Si Shi b , c , ∗, Xian-Jun Yu a , b , c , ∗ |
a Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China
b Department of Oncology, Shanghai Medical College of Fudan University, Shanghai 200032, China
c Shanghai Pancreatic Cancer Institute, Shanghai 200032, China
d Department of Hepatobiliary and Pancreatic Surgery, The First People’s Hospital of Changzhou, Changzhou 213004, China
e Department of Minimally Invasive Hepatobiliary and Pancreatic Surgery, Ningbo No. 2 Hospital, Ningbo 315010, China
f Department of Hepatobiliary and Pancreatic Surgery, Shaoxing People’s Hospital, Shaoxing 312000, China
∗ Corresponding authors at: Department of Oncology, Shanghai Medical College of Fudan University, Shanghai 20 0 032, China.
E-mail addresses: yuxianjun@fudanpci.org (X.-J. Yu), shisi@fudanpci.org (S. Shi).
# Contributed equally. |
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Abstract Background: Neoadjuvant therapy is associated with nodal downstaging and improved oncological outcomes in patients with lymph node (LN)-positive pancreatic cancer. This study aimed to develop and validate a nomogram to preoperatively predict LN-positive disease.
Methods: A total of 558 patients with resected pancreatic cancer were randomly and equally divided into development and internal validation cohorts. Multivariate logistic regression analysis was used to construct the nomogram. Model performance was evaluated by discrimination, calibration, and clinical usefulness. An independent multicenter cohort consisting of 250 patients was used for external validation.
Results: A four-marker signature was built consisting of carbohydrate antigen 19–9 (CA19–9), CA125, CA50, and CA242. A nomogram was constructed to predict LN metastasis using three predictors identified by multivariate analysis: risk score of the four-marker signature, computed tomography-reported LN status, and clinical tumor stage. The prediction model exhibited good discrimination ability, with C-indexes of 0.806, 0.742 and 0.763 for the development, internal validation, and external validation cohorts, respectively. The model also showed good calibration and clinical usefulness. A cut-offvalue (0.72) for the probability of LN metastasis was determined to separate low-risk and high-risk patients. Kaplan-Meier survival analysis revealed a good agreement of the survival curves between the nomogram-predicted status and the true LN status.
Conclusions: This nomogram enables the identification of pancreatic cancer patients at high risk for LN positivity who may have more advanced disease and thus could potentially benefit from neoadjuvant therapy.
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2021, Vol. 20 
