Related Experiment Video
Updated: Jul 29, 2025
Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Development and validation of a gene expression-based nomogram to predict the prognosis of patients with
Wei Wang1, Chen Wu2, Lijun Xu3
1Interventional Department, The Second Hospital of Shandong University, Jinan, 250033, China.
Aim:
To establish and validate a prognostic nomogram of cholangiocarcinoma (CCA) using independent clinicopathological and genetic mutation factors.
Methods:
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.
Results:
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.
Conclusion:
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.
