Log odds of positive lymph nodes predict surgical prognosis in intrahepatic cholangiocarcinoma based on SEER cohort and nomogram model

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Authors: Shan Li, Guoxia Jia, Fan Luo, Jiaxin Yin, Shaochong Deng, Jianfu Zhao, Huizhong Wang
Cited by: 0
References: 28

Abstract

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) has a high postoperative recurrence rate, but quantitative assessment of lymph node metastasis (LNM) by AJCC staging remains inadequate. The log odds of positive lymph nodes (LODDS) have prognostic value in digestive system tumors, but its application in ICC has yet to be studied. METHOD: Based on the SEER database (2010–2017), 593 ICC patients after hepatectomy or choledochotomy surgery, Cox regression was applied to analyze the association between LODDS and the risk of all-cause mortality (ACM) and cancer-specific mortality (CSM), and risk thresholds were determined by restricted cubic spline (RCS), and a nomogram predictive model was constructed based on variables screened by Boruta’s algorithm. Patients were stratified by optimal nomogram cutoff, and survival was compared via Kaplan-Meier curves. RESULTS: LODDS was positively linear correlated with ACM (HR = 2.062, 95% CI: 1.683, 2.527, P < 0.001) and CSM (HR = 2.068, 95% CI: 1.632, 2.622, P < 0.001), with the optimal cutoff value of -0.63. The risk of death was increased 1.7 times in the high LODDS group (>− 0.477) compared with the baseline group. The nomogram integrating variables such as LODDS, T-staging, and tumor size had a C-index of 0.711, which had a good predictive performance. Survival differences were statistically significant for both LODDS-based stratification and nomogram-based risk groups. CONCLUSION: LODDS is an independent prognostic factor for post-operative ICC survival, enabling optimized risk stratification and personalized follow-up strategies.

Fields of Study & Subjects

Cholangiocarcinoma and Gallbladder Cancer Studies Pediatric Hepatobiliary Diseases and Treatments Hepatocellular Carcinoma Treatment and Prognosis

Publication details

Journal / source
Discover Oncology
Volume
17
Issue
1
Pages
246–246
Publication date
5 February 2026
Language
EN