Evidence map›Paper›PMID 39687042›Full record

ArticleLiver cancer2024

LI-RADS Category Can Be a Post-Surgical Prognostic Factor for Intrahepatic Cholangiocarcinoma in Patients with Liver Cirrhosis or Chronic Hepatitis B.

Sungeun Park, Boyeon Koo, Boryeong Jeong, Sang Hyun Choi, Jeong Min Lee

Abstract read
In one paragraph

Article in Liver cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Sungeun ParkDepartment of Radiology, Konkuk University Medical Center, Seoul, South Korea.
Boyeon KooDepartment of Medicine, Graduate School, Kyung Hee University, Seoul, South Korea.
Boryeong JeongDepartment of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Sang Hyun ChoiDepartment of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Jeong Min LeeDepartment of Radiology, Seoul National University Hospital, Seoul, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The Liver Imaging Reporting and Data System (LI-RADS) categorization has been proposed as a potential prognostic indicator for primary liver neoplasms in patients with liver cirrhosis or chronic hepatitis B. This multicenter study aimed to determine whether LI-RADS categorization can offer additional post-surgical prognostic value for intrahepatic cholangiocarcinoma (ICCA) when used in conjunction with the American Joint Committee on Cancer (AJCC) guidelines. Methods: Patients with high risk for hepatocellular carcinoma, surgically confirmed ICCAs, and available preoperative MRI were enrolled. LI-RADS categorization of ICCAs was performed using MRI features, and multivariate analyses were conducted incorporating LI-RADS category, AJCC staging, and clinicopathologic factors to evaluate their predictive value for postoperative recurrence-free survival (RFS) and overall survival (OS). In patients with early recurrence (<2 years), the percentages of AJCC stage I and LR-M or LR tumor-in-vein (TIV) were calculated, respectively. Results: Among the 166 ICCAs analyzed, 13.3% (22/166) were classified as LR-4/5, 77.7% (129/166) as LR-M, and 9.0% (15/166) as LR TIV. Classifications according to the 8th AJCC guidelines for patients with available post-surgical pathologic data and follow-up imaging were 40.6% (63/155) stage I tumors, 23.9% (37/155) stage II, and 35.5% (55/155) stage III. Multivariate analysis revealed that LI-RADS category (LR-M or LR-TIV) was a significant factor for predicting both RFS (hazard ratio [HR] = 2.86, Conclusion: The MRI-based preoperative LI-RADS categorization of ICCA provides additional post-surgical prognostic value beyond the AJCC guidelines, with significant implications for both RFS and OS.

Indexed as

CholangiocarcinomaLiver Imaging Reporting and Data SystemMagnetic resonance imagingRecurrenceSurvival

Identifiers

PMID39687042
PMCPMC11649255

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.