Assessment of Lymph Node Status in Gallbladder Cancer: Location, Number, or Ratio of Positive Nodes

Overview

Journal World J Surg Oncol

Publisher Biomed Central

Specialties General Surgery
Oncology

Date 2012 May 19

PMID 22594526

Citations 43

Authors

Yoshio Shirai

Jun Sakata

Toshifumi Wakai

Taku Ohashi

Yoichi Ajioka

Katsuyoshi Hatakeyama

Affiliations

Soon will be listed here.

Abstract

Unlabelled: A BACKGROUND: Assessment of lymph node status is a critical issue in the surgical management of gallbladder cancer. The aim of this study was to compare the anatomical location of positive nodes, number of positive nodes, and lymph node ratio (LNR) as prognostic predictors in gallbladder cancer.

Methods: We conducted a retrospective analysis of 135 patients with gallbladder cancer who underwent a radical resection with regional lymphadenectomy. A total of 2,245 regional lymph nodes were retrieved (median, 14 per patient). The location of positive nodes was classified according to the AJCC staging manual (7th edition). 'Optimal' cutoff values were determined for the number of positive nodes and LNR based on maximal χ(2) scores calculated with the Cox proportional hazards regression model.

Results: Lymph node metastasis was found histologically in 59 (44%) patients. The 'optimal' cutoff values for the number of positive nodes and LNR were determined to be three nodes and 10%, respectively. Univariate analysis identified location of positive nodes (pN0, pN1, pN2; P<0.001), number of positive nodes (0, 1 to 3, ≥ 4; P <0.001), and LNR (0%, 0 to 10%, >10%; P<0.001) as significant prognostic factors. Multivariate analysis identified number of positive nodes as an independent prognostic factor ( P=0.004); however, location of positive nodes and LNR failed to remain as an independent variable.

Conclusions: The number of positive lymph nodes better predicts patient outcome after resection than either the location of positive lymph nodes or LNR in gallbladder cancer. Dividing the number of positive lymph nodes into three categories (0, 1 to 3, or ≥ 4) is valid for stratifying patients based on the prognosis after resection.

Citing Articles

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PMID: 39542966 DOI: 10.1245/s10434-024-16492-2.

Machine Learning Algorithm for Predicting Distant Metastasis of T1 and T2 Gallbladder Cancer Based on SEER Database.

Guo Z, Zhang Z, Liu L, Zhao Y, Liu Z, Zhang C Bioengineering (Basel). 2024; 11(9).

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Molecular biomarkers involved in the progression of gallbladder inflammatory lesions to invasive cancer: A proteomic approach.

Rawal N, Hariprasad G, Bandyopadhyay S, Dash N, Kumar S, Das P Biomol Biomed. 2024; 25(1):115-143.

PMID: 39284282 PMC: 11647257. DOI: 10.17305/bb.2024.10704.

Lymph Node Metastasis in Gastrointestinal Carcinomas: A View from a Proteomics Perspective.

Jain V, Sakhuja P, Agarwal A, Sirdeshmukh R, Siraj F, Gautam P Curr Oncol. 2024; 31(8):4455-4475.

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Nomograms to predict long-term survival for patients with gallbladder carcinoma after resection.

Bai S, Yang P, Qiu J, Wang J, Liu L, Wang C Cancer Rep (Hoboken). 2024; 7(3):e1991.

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