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Original Article
Preoperative Prediction Model for Early Recurrence of Intrahepatic Cholangiocarcinoma After Surgical Resection: Development and External Validation Study
Dong Hwan Kim1orcid , Sang Hyun Choi1orcid , Sehee Kim2, Hyungjin Rhee3, Eun-Suk Cho4, Suk-Keu Yeom5, Sumi Park6, Seung Soo Lee1, Mi-Suk Park3

DOI: https://doi.org/10.4143/crt.2024.1187 [Accepted]
Published online: February 5, 2025
1Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
2Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
3Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
4Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
5Department of Radiology, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, Korea
6Department of Radiology, National Health Insurance Service Ilsan Hospital, Goyang, Korea
Corresponding author:  Sang Hyun Choi
Tel: 82-2-3010-1797 
Email: edwardchoi83@gmail.com
Received: 10 December 2024   • Accepted: 4 February 2025
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Purpose
We aimed to develop a preoperative risk scoring system to predict early recurrence (ER) of intrahepatic cholangiocarcinoma (ICCA) after resection, utilizing clinical and computed tomography (CT) features.
Materials and Methods
This multicenter study included 365 patients who underwent curative-intent surgical resection for ICCA at six institutions between 2009 and 2016. Of these, 264 patients from one institution constituted the development cohort, while 101 patients from the other institutions constituted the external validation cohort. Logistic regression models were constructed to predict ER based on preoperative variables and were subsequently translated into a risk-scoring system. The discrimination performance of the risk-scoring system was validated using external data and compared to the American Joint Committee on Cancer (AJCC) TNM staging system.
Results
Among the 365 patients (mean age, 62±10 years), 153 had ER. A preoperative risk scoring system that incorporated both clinical and CT features demonstrated superior discriminatory performance compared to the postoperative AJCC TNM staging system in both the development (area under the curve [AUC], 0.78 vs. 0.68; p=0.002) and validation cohorts (AUC, 0.69 vs. 0.66; p=0.641). The preoperative risk scoring system effectively stratified patients based on their risk for ER: the 1-year recurrence-free survival rates for the low, intermediate, and high-risk groups were 85.5%, 56.6%, and 15.6%, respectively (p<0.001) in the development cohort, and 87.5%, 58.5%, and 25.0%, respectively (p<0.001) in the validation cohort.
Conclusion
A preoperative risk scoring system that incorporates clinical and CT imaging features was valuable in identifying high-risk patients with ICCA for ER following resection.

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