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Prognostic Nomogram for Patients With Pancreatic Ductal Adenocarcinoma of Pancreatic Head After Pancreaticoduodenectomy

Authors :
Hongkai Zhuang
Zixuan Zhou
Zuyi Ma
Shanzhou Huang
Yuanfeng Gong
Zhenchong Li
Chunsheng Liu
Shujie Wang
Bo Chen
Chuanzhao Zhang
Baohua Hou
Source :
Clinical Medicine Insights: Oncology, Vol 15 (2021)
Publication Year :
2021
Publisher :
SAGE Publishing, 2021.

Abstract

Background: The prognosis of patients with pancreatic ductal adenocarcinoma (PDAC) of pancreatic head remains poor, even after potentially curative R0 resection. The aim of this study was to develop an accurate model to predict patients’ prognosis for PDAC of pancreatic head following pancreaticoduodenectomy. Methods: We retrospectively reviewed 112 patients with PDAC of pancreatic head after pancreaticoduodenectomy in Guangdong Provincial People’s Hospital between 2014 and 2018. Results: Five prognostic factors were identified using univariate Cox regression analysis, including age, histologic grade, American Joint Committee on Cancer (AJCC) Stage 8th, total bilirubin (TBIL), CA19-9. Using all subset analysis and multivariate Cox regression analysis, we developed a nomogram consisted of age, AJCC Stage 8th, perineural invasion, TBIL, and CA19-9, which had higher C-indexes for OS (0.73) and RFS (0.69) compared with AJCC Stage 8th alone (OS: 0.66; RFS: 0.67). The area under the curve (AUC) values of the receiver operating characteristic (ROC) curve for the nomogram for OS and RFS were significantly higher than other single parameter, which are AJCC Stage 8th, age, perineural invasion, TBIL, and CA19-9. Importantly, our nomogram displayed higher C-index for OS than previous reported models, indicating a better predictive value of our model. Conclusions: A simple and practical nomogram for patient prognosis in PDAC of pancreatic head following pancreaticoduodenectomy was established, which shows satisfactory predictive efficacy and deserves further evaluation in the future.

Details

Language :
English
ISSN :
11795549
Volume :
15
Database :
Directory of Open Access Journals
Journal :
Clinical Medicine Insights: Oncology
Publication Type :
Academic Journal
Accession number :
edsdoj.8db454e64a824f7aab8f3a4558406741
Document Type :
article
Full Text :
https://doi.org/10.1177/11795549211024149