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Development of Nomograms for Predicting Prognosis of Pancreatic Cancer after Pancreatectomy: A Multicenter Study

Authors :
So Jeong Yoon
Boram Park
Jaewoo Kwon
Chang-Sup Lim
Yong Chan Shin
Woohyun Jung
Sang Hyun Shin
Jin Seok Heo
In Woong Han
Source :
Biomedicines, Vol 10, Iss 6, p 1341 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

Surgical resection is the only curative treatment for pancreatic ductal adenocarcinoma (PDAC). Currently, the TNM classification system is considered the standard for predicting prognosis after surgery. However, the prognostic accuracy of the system remains limited. This study aimed to develop new predictive nomograms for resected PDAC. The clinicopathological data of patients who underwent surgery for PDAC between 2006 and 2015 at five major institutions were retrospectively reviewed; 885 patients were included in the analysis. Cox regression analysis was performed to investigate prognostic factors for recurrence and survival, and statistically significant factors were used for creating nomograms. The nomogram for predicting recurrence-free survival included nine factors: sarcopenic obesity, elevated carbohydrate antigen 19–9, platelet-to-lymphocyte ratio, preoperatively-identified arterial abutment, estimated blood loss (EBL), tumor differentiation, size, lymph node ratio, and tumor necrosis. The nomogram for predicting overall survival included 10 variables: age, underlying liver disease, chronic kidney disease, preoperatively found portal vein invasion, portal vein resection, EBL, tumor differentiation, size, lymph node metastasis, and tumor necrosis. The time-dependent area under the receiver operating characteristic curve for both nomograms exceeded 0.70. Nomograms were developed for predicting survival after resection of PDAC, and the platforms showed fair predictive performance. These new comprehensive nomograms provide information on disease status and are useful for determining further treatment for PDAC patients.

Details

Language :
English
ISSN :
22279059
Volume :
10
Issue :
6
Database :
Directory of Open Access Journals
Journal :
Biomedicines
Publication Type :
Academic Journal
Accession number :
edsdoj.79e3f7cc76648e095937d9dd81a1d1a
Document Type :
article
Full Text :
https://doi.org/10.3390/biomedicines10061341