Survival analysis of patients with intrahepatic cholangiocarcinoma treated with adjuvant chemotherapy after radical resection based on CoxPH model and deep learning algorithm.
10.3760/cma.j.cn112139-20230105-00007
- Author:
Jia Lu CHEN
1
;
Xiao Peng YU
1
;
Yue TANG
1
;
Chen CHEN
2
;
Ying He QIU
3
;
Hong WU
4
;
Tian Qiang SONG
5
;
Yu HE
6
;
Xian Hai MAO
7
;
Wen Long ZHAI
8
;
Zhang Jun CHENG
9
;
Jing Dong LI
10
;
Zhi Min GENG
2
;
Zhao Hui TANG
1
;
Zhi Wei QUAN
1
Author Information
1. Department of General Surgery,Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine,Shanghai 200092,China.
2. Department of Hepatobiliary Surgery,the First Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710061,China.
3. Department of Biliary Surgery, the Third Affiliated Hospital of Naval Medical University,Shanghai 200433,China.
4. Department of Liver Transplantation,West China Hospital,Sichuan University,Chengdu 610041,China.
5. Department of Hepatobiliary Oncology,Tianjin Medical University Cancer Hospital,Tianjin 300060,China.
6. Department of Hepatobiliary Surgery,the Southwest Hospital of Army Medical University,Chongqing 400038,China.
7. Department of Hepatobiliary Surgery,Hunan Provincial People's Hospital,Changsha 410005,China.
8. Department of Hepatobiliary and Pancreas Liver Transplantation Surgery,the First Affiliated Hospital of Zhengzhou University,Zhengzhou 450052,China.
9. Department of Hepatobiliary and Pancreatic Surgery,Zhongda Hospital,Southeast University,Nanjing 210009,China.
10. Department of Hepatobiliary Surgery,Affiliated Hospital of North Sichuan Medical College,Nanchong 637000,China.
- Publication Type:Journal Article
- From:
Chinese Journal of Surgery
2023;61(4):313-320
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To establish a predictive model for survival benefit of patients with intrahepatic cholangiocarcinoma (ICC) who received adjuvant chemotherapy after radical resection. Methods: The clinical and pathological data of 249 patients with ICC who underwent radical resection and adjuvant chemotherapy at 8 hospitals in China from January 2010 to December 2018 were retrospectively collected. There were 121 males and 128 females,with 88 cases>60 years old and 161 cases≤60 years old. Feature selection was performed by univariate and multivariate Cox regression analysis. Overall survival time and survival status were used as outcome indicators,then target clinical features were selected. Patients were stratified into high-risk group and low-risk group,survival differences between the two groups were analyzed. Using the selected clinical features, the traditional CoxPH model and deep learning DeepSurv survival prediction model were constructed, and the performance of the models were evaluated according to concordance index(C-index). Results: Portal vein invasion, carcinoembryonic antigen>5 μg/L,abnormal lymphocyte count, low grade tumor pathological differentiation and positive lymph nodes>0 were independent adverse prognostic factors for overall survival in 249 patients with adjuvant chemotherapy after radical resection (all P<0.05). The survival benefit of adjuvant chemotherapy in the high-risk group was significantly lower than that in the low-risk group (P<0.05). Using the above five features, the traditional CoxPH model and the deep learning DeepSurv survival prediction model were constructed. The C-index values of the training set were 0.687 and 0.770, and the C-index values of the test set were 0.606 and 0.763,respectively. Conclusion: Compared with the traditional Cox model, the DeepSurv model can more accurately predict the survival probability of patients with ICC undergoing adjuvant chemotherapy at a certain time point, and more accurately judge the survival benefit of adjuvant chemotherapy.
