A novel prognostic nomogram for colorectal cancer liver metastasis patients with recurrence after hepatectomy

Autor: Jie‐ying Liang, Hao‐cheng Lin, Jingwen Liu, De‐shen Wang, Yun‐fei Yuan, Bin‐kui Li, Yun Zheng, Xiao‐jun Wu, Gong Chen, Feng‐hua Wang, Zhi‐qiang Wang, Zhi‐zhong Pan, De‐sen Wan, Rui‐hua Xu, Yu‐hong Li
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Cancer Medicine, Vol 10, Iss 5, Pp 1535-1544 (2021)
Druh dokumentu: article
ISSN: 2045-7634
DOI: 10.1002/cam4.3697
Popis: Abstract Purpose We aimed to construct a nomogram to predict personalized post‐recurrence survival (PRS) among colorectal cancer liver metastasis (CRLM) patients with post‐hepatectomy recurrence. Methods Colorectal cancer liver metastasis patients who received initial hepatectomy and had subsequent recurrence between 2001 and 2019 in Sun Yat‐sen University Cancer Center from China were included in the study. Patients were randomly assigned to a training cohort and a validation cohort on a ratio of 2:1. Univariable analysis was first employed to select potential predictive factors for PRS. Then, the multivariable Cox regression model was applied to recognize independent prognostic factors. According to the model, a nomogram to predict PRS was established. The nomogram's predictive capacity was further assessed utilizing concordance index (C‐index) values, calibration plots, and Kaplan–Meier curves. Results About 376 patients were finally enrolled, with a 3‐year PRS rate of 37.3% and a 5‐year PRS rate of 24.6%. The following five independent predictors for PRS were determined to construct the nomogram: the largest size of liver metastases at initial hepatectomy, relapse‐free survival, CEA level at recurrence, recurrent sites, and treatment for recurrence. The nomogram displayed fairly good discrimination and calibration. The C‐index value was 0.742 for the training cohort and 0.773 for the validation cohort. Patients were grouped into three risk groups very well by the nomogram, with 5‐year PRS rates of 45.2%, 23.3%, and 9.0%, respectively (p
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