Shi-Wei Guo1, Jing Shen2, Jun-Hui Gao3, Xiao-Han Shi1, Sui-Zhi Gao1, Huan Wang1, Bo Li1, Wei-Lan Yuan3, Ling Lin3, Gang Jin4. 1. Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Navy Military Medical University (Second Military Medical University), 200433 Shanghai, China. 2. Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Navy Military Medical University (Second Military Medical University), 200433 Shanghai, China; Department of General Surgery, No.971 Hospital of Navy, 266071, Qingdao, Shandong, China. 3. Shanghai Biotecan Pharmaceuticals Co., Ltd., Zhangjiang Center for Translational Medicine, 201204 Shanghai, China. 4. Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Navy Military Medical University (Second Military Medical University), 200433 Shanghai, China. Electronic address: jingang@smmu.edu.cn.
Abstract
BACKGROUND: Neoadjuvant chemotherapy may benefit patients with pancreatic ductal adenocarcinoma with resectable and borderline disease. Inappropriate use of neoadjuvant therapy, however, may lead to the loss of therapeutic opportunities. Until an effective prediction model of individual drug sensitivity is established, no accurate model exists to help surgeons decide on the appropriate use of neoadjuvant chemotherapy. We hypothesized that early recurrence in patients undergoing upfront, early resection may be an indication for neoadjuvant chemotherapy. Therefore, we aimed to use preoperative clinical parameters to establish a model of early recurrence to select patients at high risk for neoadjuvant chemotherapy. METHODS: Patients who underwent resection for pancreatic ductal adenocarcinoma between January 2014 and November 2017 were analyzed retrospectively. After the minimum P-value approach, the patients were divided into three groups: early recurrence, middle recurrence, and late/non-recurrence. Preoperative clinicopathologic factors that could predict early recurrence were included in a Cox proportional hazards regression model for univariate and multivariate analyses. The factors related to early recurrence were included to establish nomogram and decision tree models, which were then validated in 68 patients. RESULTS: We found that 235 (72.5%) of 324 patients had recurrence with a median recurrence-free survival of 210 days. The early recurrence, middle recurrence, and late/non-recurrence groups differed in preoperative carbohydrate antigen 19-9 and carcinoembryonic antigen levels, "resectability" on cross-sectional imaging, resection requiring a vascular resection, T stage, tumor size, and adjuvant chemotherapy. The best cutoff value of early recurrence was the first 162 days postoperatively. Univariate and multivariate analyses showed that selected preoperative chief complaints, lymph node enlargement and resectability on cross-sectional imaging, preoperative carbohydrate antigen 19-9 levels >210 kU/L, and a neutrophil/lymphocyte ratio >4.2 were independent predictors for early recurrence. CONCLUSION: We have successfully built a prediction model of early recurrence of patients with pancreatic ductal adenocarcinoma with the optimal cutoff early-recurrence value of 162 days. Our nomogram and decision tree models may be used to select those at high risk for early recurrence to guide preoperative decision-making concerning the use of neoadjuvant therapy in those patients who have "resectable" disease and not only the more classic criteria of borderline resectability.
BACKGROUND: Neoadjuvant chemotherapy may benefit patients with pancreatic ductal adenocarcinoma with resectable and borderline disease. Inappropriate use of neoadjuvant therapy, however, may lead to the loss of therapeutic opportunities. Until an effective prediction model of individual drug sensitivity is established, no accurate model exists to help surgeons decide on the appropriate use of neoadjuvant chemotherapy. We hypothesized that early recurrence in patients undergoing upfront, early resection may be an indication for neoadjuvant chemotherapy. Therefore, we aimed to use preoperative clinical parameters to establish a model of early recurrence to select patients at high risk for neoadjuvant chemotherapy. METHODS:Patients who underwent resection for pancreatic ductal adenocarcinoma between January 2014 and November 2017 were analyzed retrospectively. After the minimum P-value approach, the patients were divided into three groups: early recurrence, middle recurrence, and late/non-recurrence. Preoperative clinicopathologic factors that could predict early recurrence were included in a Cox proportional hazards regression model for univariate and multivariate analyses. The factors related to early recurrence were included to establish nomogram and decision tree models, which were then validated in 68 patients. RESULTS: We found that 235 (72.5%) of 324 patients had recurrence with a median recurrence-free survival of 210 days. The early recurrence, middle recurrence, and late/non-recurrence groups differed in preoperative carbohydrate antigen 19-9 and carcinoembryonic antigen levels, "resectability" on cross-sectional imaging, resection requiring a vascular resection, T stage, tumor size, and adjuvant chemotherapy. The best cutoff value of early recurrence was the first 162 days postoperatively. Univariate and multivariate analyses showed that selected preoperative chief complaints, lymph node enlargement and resectability on cross-sectional imaging, preoperative carbohydrate antigen 19-9 levels >210 kU/L, and a neutrophil/lymphocyte ratio >4.2 were independent predictors for early recurrence. CONCLUSION: We have successfully built a prediction model of early recurrence of patients with pancreatic ductal adenocarcinoma with the optimal cutoff early-recurrence value of 162 days. Our nomogram and decision tree models may be used to select those at high risk for early recurrence to guide preoperative decision-making concerning the use of neoadjuvant therapy in those patients who have "resectable" disease and not only the more classic criteria of borderline resectability.
Authors: Gerard M Healy; Emmanuel Salinas-Miranda; Rahi Jain; Xin Dong; Dominik Deniffel; Ayelet Borgida; Ali Hosni; David T Ryan; Nwabundo Njeze; Anne McGuire; Kevin C Conlon; Jonathan D Dodd; Edmund Ronan Ryan; Robert C Grant; Steven Gallinger; Masoom A Haider Journal: Eur Radiol Date: 2021-11-10 Impact factor: 7.034