Objective:To validate the 8 th edition of the American Joint Committee on Cancer(AJCC)staging system for pancreatic ductal adenocarcinoma(PDAC)in a Chinese cohort of radically resected patients and to develop a refine...Objective:To validate the 8 th edition of the American Joint Committee on Cancer(AJCC)staging system for pancreatic ductal adenocarcinoma(PDAC)in a Chinese cohort of radically resected patients and to develop a refined staging system for PDAC.Methods:Data were collected from the China Pancreas Data Center(CPDC)for patients with resected PDAC in 2016 and 2017,and cancer-specific survival(CSS)was evaluated using the Kaplan-Meier method and log-rank test.Univariate and multivariate analyses based on Cox regression were performed to identify prognostic factors.The recursive partitioning analysis(RPA),Kaplan-Meier method,and log-rank test were performed on the training dataset to generate a proposed modification for the 8 th TNM staging system utilizing the preoperative carbohydrate antigen(CA)19-9 level.Validation was performed for both staging systems in the validation cohort.Results:A total of 1,676 PDAC patients were retrieved,and the median CSS was significantly different between the 8 th TNM groupings,with no significant difference in survival between stage IB and IIA.The analysis of T and N stages demonstrated a better prognostic value in the N category.Multivariate analysis showed that the preoperative serum CA19-9 level was the strongest prognostic indicator among all the independent risk factors.All patients with CA19-9>500 U/mL had similar survival,and we proposed a new staging system by combining IB and IIA and stratifying all patients with high CA19-9 into stage III.The modified staging system had a better performance for predicting CSS than the 8 th AJCC staging scheme.Conclusions:The 8 th AJCC staging system for PDAC is suitable for a Chinese cohort of resected patients,and the N category has a better prognostic value than the T category.Our modified staging system has superior accuracy in predicting survival than the 8 th AJCC TNM staging system.展开更多
基金supported by grants from the National Natural Science Foundation of China(No.81672353 and 81871954)。
文摘Objective:To validate the 8 th edition of the American Joint Committee on Cancer(AJCC)staging system for pancreatic ductal adenocarcinoma(PDAC)in a Chinese cohort of radically resected patients and to develop a refined staging system for PDAC.Methods:Data were collected from the China Pancreas Data Center(CPDC)for patients with resected PDAC in 2016 and 2017,and cancer-specific survival(CSS)was evaluated using the Kaplan-Meier method and log-rank test.Univariate and multivariate analyses based on Cox regression were performed to identify prognostic factors.The recursive partitioning analysis(RPA),Kaplan-Meier method,and log-rank test were performed on the training dataset to generate a proposed modification for the 8 th TNM staging system utilizing the preoperative carbohydrate antigen(CA)19-9 level.Validation was performed for both staging systems in the validation cohort.Results:A total of 1,676 PDAC patients were retrieved,and the median CSS was significantly different between the 8 th TNM groupings,with no significant difference in survival between stage IB and IIA.The analysis of T and N stages demonstrated a better prognostic value in the N category.Multivariate analysis showed that the preoperative serum CA19-9 level was the strongest prognostic indicator among all the independent risk factors.All patients with CA19-9>500 U/mL had similar survival,and we proposed a new staging system by combining IB and IIA and stratifying all patients with high CA19-9 into stage III.The modified staging system had a better performance for predicting CSS than the 8 th AJCC staging scheme.Conclusions:The 8 th AJCC staging system for PDAC is suitable for a Chinese cohort of resected patients,and the N category has a better prognostic value than the T category.Our modified staging system has superior accuracy in predicting survival than the 8 th AJCC TNM staging system.
