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A Three-Dimensional Spheroid Model to Investigate the Tumor-Stromal Interaction in Hepatocellular Carcinoma
Published on: September 30, 2021
Correlation between clinical and pathological nodal status in hepatocellular carcinoma: identifying risk factors for
Huisong Lee1, Kyunguk Jung2, Michael Luu3
1Department of Surgery, Ewha Womans University Mokdong Hospital, Ewha Womans University College of Medicine, Seoul, Republic of Korea.
Background:
Lymph node metastasis (LNM) in hepatocellular carcinoma (HCC) is associated with significantly worse prognosis, yet its detection and risk stratification remain challenging in clinical practice. This study aimed to investigate the correlation between clinical nodal status (cN) and pathological nodal status (pN) in HCC patients and to identify risk factors for LNM via the National Cancer Database (NCDB).
Methods:
We identified HCC patients who underwent liver resection between 2004 and 2017 from the NCDB. Clinical and pathological variables were analyzed to assess the correlation between cN1 and pN1. Logistic regression models were used to identify risk factors for LNM and to evaluate the diagnostic performance of cN1 in predicting pN1.
Results:
A total of 21,733 HCC patients who underwent liver resection were analyzed. Of these, 15,496 (71%) were male, and the median age was 65 years. Only 1.4% of patients had cN1 disease. Among the 7,612 patients who underwent lymph node excision (LNE), 3.3% had pN1. Clinical LNM (cN1) demonstrated high specificity (99.2%) but low sensitivity (46.2%) in detecting pN1. Logistic regression analysis revealed that younger age, female sex, fibrolamellar histology, combined hepatocellular-cholangiocarcinoma (HCC-CCA), advanced clinical T stage, and higher tumor grade were significant risk factors for pN1.
Conclusions:
Tumor characteristics, patient demographics, and specific histological subtypes significantly influence the risk of pN1 in patients with resectable HCC. Given the low sensitivity of cN1, LNE should be considered for high-risk patients to improve diagnostic accuracy and inform treatment decisions. These findings underscore the importance of integrating risk factors into clinical practice and highlight the need for further research to refine predictive models for LNM in HCC.
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