Hai-Feng Zhou1, Jia-Lei Wang1, Wei Yang1, Chun Zhou1, Yan Shen1, Ling-Ling Wu1, Zhong-Ling Pei1, Wei-Zhong Zhou2, Sheng Liu3, Hai-Bin Shi4. 1. Department of Interventional Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing, 210029, China. 2. Department of Interventional Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing, 210029, China. xmjbq007@163.com. 3. Department of Interventional Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing, 210029, China. liusheng@njmu.edu.cn. 4. Department of Interventional Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing, 210029, China. shihb@njmu.edu.cn.
Abstract
BACKGROUND: Patients with pancreatic cancer-caused biliary obstruction (PC-BO) have poor prognosis, but we lack of tools to predict survival for clinical decision-making. This study aims to establish a model for survival prediction among patients with PC-BO. METHODS: A total of 172 patients with PC-BO treated with percutaneous biliary drainage were randomly divided into a training group (n = 120) and a validation group (n = 52). The independent risk factors for overall survival were selected to develop a Cox model. The predictive performance of M stage, hepatic metastases, cancer antigen 199, and the Cox model was determined. Naples prognostic score (NPS), the prognostic nutritional index (PNI), and the controlling nutritional status (CONUT) for 1-month mortality risk were compared with the Cox model. RESULTS: The Cox model was developed based on total cholesterol, direct bilirubin, hepatic metastases, cancer antigen 199, stenosis type, and preprocedural infection (all P < 0.05), which named "COMBO-PaS." The COMBO-PaS model had the highest area under the curves (AUC) (0.801-0.933) comparing with other predictors (0.506-0.740) for 1-, 3-, and 6-month survival prediction. For 1-month mortality risk prediction, the COMBO-PaS model had the highest AUC of 0.829 comparing with NPS, PNI, and CONUT. CONCLUSION: The COMBO-PaS model was useful for survival prediction among patients with PC-BO.
BACKGROUND: Patients with pancreatic cancer-caused biliary obstruction (PC-BO) have poor prognosis, but we lack of tools to predict survival for clinical decision-making. This study aims to establish a model for survival prediction among patients with PC-BO. METHODS: A total of 172 patients with PC-BO treated with percutaneous biliary drainage were randomly divided into a training group (n = 120) and a validation group (n = 52). The independent risk factors for overall survival were selected to develop a Cox model. The predictive performance of M stage, hepatic metastases, cancer antigen 199, and the Cox model was determined. Naples prognostic score (NPS), the prognostic nutritional index (PNI), and the controlling nutritional status (CONUT) for 1-month mortality risk were compared with the Cox model. RESULTS: The Cox model was developed based on total cholesterol, direct bilirubin, hepatic metastases, cancer antigen 199, stenosis type, and preprocedural infection (all P < 0.05), which named "COMBO-PaS." The COMBO-PaS model had the highest area under the curves (AUC) (0.801-0.933) comparing with other predictors (0.506-0.740) for 1-, 3-, and 6-month survival prediction. For 1-month mortality risk prediction, the COMBO-PaS model had the highest AUC of 0.829 comparing with NPS, PNI, and CONUT. CONCLUSION: The COMBO-PaS model was useful for survival prediction among patients with PC-BO.
Authors: Jean-Marc Dumonceau; Andrea Tringali; Ioannis S Papanikolaou; Daniel Blero; Benedetto Mangiavillano; Arthur Schmidt; Geoffroy Vanbiervliet; Guido Costamagna; Jacques Devière; Jesús García-Cano; Tibor Gyökeres; Cesare Hassan; Frédéric Prat; Peter D Siersema; Jeanin E van Hooft Journal: Endoscopy Date: 2018-08-07 Impact factor: 10.093
Authors: John P Neoptolemos; Jörg Kleeff; Patrick Michl; Eithne Costello; William Greenhalf; Daniel H Palmer Journal: Nat Rev Gastroenterol Hepatol Date: 2018-06 Impact factor: 46.802