Yue Wang1, Boshi Duan2, Lihui Yan3, Chunjian Shen4, Bo Wu5, Ji Luo6, Feng Shen7, Guohua Zhao8. 1. The Department of Anesthesiology, Liaoning Cancer Hospital and Institute, Shenyang, China. Electronic address: gre031025@gmail.com. 2. The Department of Internal Medicine, Liaoning Cancer Hospital and Institute, Shenyang, China. 3. The Department of Anesthesiology, Liaoning Cancer Hospital and Institute, Shenyang, China. 4. The Department of General Surgery, Shen Zhou Hospital, Shen Yang Medical College, Shenyang, China. 5. Shen Yang Emergency Center, China. 6. The Department of General Surgery, The First Hospital of China Medical University, Shenyang, China. 7. The Department of General Surgery, Huaxi Hospital, Si Chuan University, Chengdu, China. 8. The Department of Gastric Surgery, Liaoning Cancer Hospital and Institute, Shenyang, China.
Abstract
OBJECTIVE: To investigate the prognostic factors of patients with cholangiocarcinoma and establish a prognostic model to evaluate the prognosis. METHODS: 169 cases of cholangiocarcinoma were analyzed retrospectively. Clinicopathological factors were evaluated using univariate and multivariate analysis. Prognostic index (PI) was calculated based on the results of multivariate analysis. Patients with different PI were divided into 3 groups in order to compare the survival rate of each group and draw the survival curves. Individual expected survival rate was calculated based on the prognostic Cox model and PI. The PI equation was built that included all significant variables and coefficients as follow formula: PI = (β1 × lymph node metastasis) + (β2 × CEA level) - (β3 × surgical margin). RESULTS: Univariate analysis showed that CEA, lymph node metastasis, surgical margin, AJCC staging, tumor differentiation and adjuvant chemotherapy were prognostic impacts. The difference was statistically significant (p < 0.05). Cox multivariate analysis showed that CEA, lymph node metastasis and surgical margin are three separate prognostic factors. According to different PI, patients were divided into high-risk group, middle-risk group and low-risk group and three groups were statistically significant difference in survival rate (P < 0.05). CONCLUSION: Racical resection is the key to improve the long-term survival rate of cholangiocarcinoma. By using prognostic Cox model and the PI, the prognosis of patients could be estimated and individualized clinical treatment could be conducted.
OBJECTIVE: To investigate the prognostic factors of patients with cholangiocarcinoma and establish a prognostic model to evaluate the prognosis. METHODS: 169 cases of cholangiocarcinoma were analyzed retrospectively. Clinicopathological factors were evaluated using univariate and multivariate analysis. Prognostic index (PI) was calculated based on the results of multivariate analysis. Patients with different PI were divided into 3 groups in order to compare the survival rate of each group and draw the survival curves. Individual expected survival rate was calculated based on the prognostic Cox model and PI. The PI equation was built that included all significant variables and coefficients as follow formula: PI = (β1 × lymph node metastasis) + (β2 × CEA level) - (β3 × surgical margin). RESULTS: Univariate analysis showed that CEA, lymph node metastasis, surgical margin, AJCC staging, tumor differentiation and adjuvant chemotherapy were prognostic impacts. The difference was statistically significant (p < 0.05). Cox multivariate analysis showed that CEA, lymph node metastasis and surgical margin are three separate prognostic factors. According to different PI, patients were divided into high-risk group, middle-risk group and low-risk group and three groups were statistically significant difference in survival rate (P < 0.05). CONCLUSION: Racical resection is the key to improve the long-term survival rate of cholangiocarcinoma. By using prognostic Cox model and the PI, the prognosis of patients could be estimated and individualized clinical treatment could be conducted.
Authors: Sven H Loosen; Christoph Roderburg; Katja L Kauertz; Alexander Koch; Mihael Vucur; Anne T Schneider; Marcel Binnebösel; Tom F Ulmer; Georg Lurje; Wenzel Schoening; Frank Tacke; Christian Trautwein; Thomas Longerich; Cornelis H Dejong; Ulf P Neumann; Tom Luedde Journal: Sci Rep Date: 2017-12-05 Impact factor: 4.379
Authors: Xuan Zheng; Bo Chen; Jian-Xiong Wu; Angela Y Jia; Wei-Qi Rong; Li-Ming Wang; Fan Wu; Yu-Ting Zhao; Ye-Xiong Li; Wei-Hu Wang Journal: Cancer Manag Res Date: 2018-09-26 Impact factor: 3.989