Development and validation of a gene expression-based nomogram to predict the prognosis of patients with cholangiocarcinoma

列线图 医学 内科学 肿瘤科 比例危险模型 克拉斯 单变量 队列 多元分析 血液学 单变量分析 基因突变 癌症 多元统计 基因 突变 结直肠癌 生物 遗传学 统计 数学
作者
Wei Wang,Chen Wu,Lijun Xu,Peilin Li,Kai Wang,Guangbing Li,Shanshan Zhao,Yongsheng Li,Xiaoyu Fan,Weifeng Wang,Meizhen Hu,Jing Wu,Shifeng Xu
出处
期刊:Journal of Cancer Research and Clinical Oncology [Springer Science+Business Media]
标识
DOI:10.1007/s00432-023-04858-0
摘要

To establish and validate a prognostic nomogram of cholangiocarcinoma (CCA) using independent clinicopathological and genetic mutation factors.213 patients with CCA (training cohort n = 151, validation cohort n = 62) diagnosed from 2012 to 2018 were included from multi-centers. Deep sequencing targeting 450 cancer genes was performed. Independent prognostic factors were selected by univariate and multivariate Cox analyses. The clinicopathological factors combined with (A)/without (B) the gene risk were used to establish nomograms for predicting overall survival (OS). The discriminative ability and calibration of the nomograms were assessed using C-index values, integrated discrimination improvement (IDI), decision curve analysis (DCA), and calibration plots.The clinical baseline information and gene mutations in the training and validation cohorts were similar. SMAD4, BRCA2, KRAS, NF1, and TERT were found to be related with CCA prognosis. Patients were divided into low-, median-, and high-risk groups according to the gene mutation, the OS of which was 42.7 ± 2.7 ms (95% CI 37.5-48.0), 27.5 ± 2.1 ms (95% CI 23.3-31.7), and 19.8 ± 4.0 ms (95% CI 11.8-27.8) (p < 0.001), respectively. The systemic chemotherapy improved the OS in high and median risk groups, but not in the low-risk group. The C-indexes of the nomogram A and B were 0.779 (95% CI 0.693-0.865) and 0.725 (95% CI 0.619-0.831), p < 0.01, respectively. The IDI was 0.079. The DCA showed a good performance and the prognostic accuracy was validated in the external cohort.Gene risk has the potential to guide treatment decision for patients at different risks. The nomogram combined with gene risk showed a better accuracy in predicting OS of CCA than not.

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