Wang XY, Zhu WW, Lu L, Li YT, Zhu Y, Yang LY, Sun HT, Wang CQ, Lin J, Huang C, Yang X, Fan J, Jia HL, Zhang JB, Yin BB, Chen JH, Qin LX. Development and validation of a mutation-annotated prognostic score for intrahepatic cholangiocarcinoma after resection: a retrospective cohort study.
Int J Surg 2023;
109:3506-3518. [PMID:
37578492 PMCID:
PMC10651289 DOI:
10.1097/js9.0000000000000636]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Accepted: 07/13/2023] [Indexed: 08/15/2023]
Abstract
BACKGROUND
The value of existing prognostic models for intrahepatic cholangiocarcinoma is limited. The inclusion of prognostic gene mutations would enhance the predictive efficacy.
METHODS
In the screening cohorts, univariable Cox regression analysis was applied to investigate the effect of individual mutant genes on overall survival (OS). In the training set, multivariable analysis was performed to evaluate the independent prognostic roles of the clinicopathological and mutational parameters, and a prognostic model was constructed. Internal and external validations were conducted to evaluate the performance of this model.
RESULTS
Among the recurrent mutations, only TP53 and KRASG12 were significantly associated with OS across all three screening cohorts. In the training cohort, TP53 and KRASG12 mutations in combination with seven other clinical parameters (tumor size, tumor number, vascular invasion, lymph node metastasis, adjacent invasion, CA19-9, and CEA), were independent prognostic factors for OS. A mutation-annotated prognostic score (MAPS) was established based on the nine prognosticators. The C-indices of MAPS (0.782 and 0.731 in the internal and external validation cohorts, respectively) were statistically higher than those of other existing models ( P <0.05). Furthermore, the MAPS model also demonstrated significant value in predicting the possible benefits of upfront surgery and adjuvant therapy.
CONCLUSIONS
The MAPS model demonstrated good performance in predicting the OS of intrahepatic cholangiocarcinoma patients. It may also help predict the possible benefits of upfront surgery and adjuvant therapy.
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