Evidence map›Paper›PMID 39224117›Full record

ArticleJournal of hepatocellular carcinoma2024

Exploring the MRI and Clinical Features of P53-Mutated Hepatocellular Carcinoma.

Jingfei Weng, Yuyao Xiao, Jing Liu, Xiaohua Liu, Yuqing He, Fei Wu, Xiaoyan Ni, Chun Yang

Abstract read
In one paragraph

Article in Journal of hepatocellular carcinoma, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

5 citing papers in PubMed.

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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

8 authors.

Jingfei Weng *Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Yuyao Xiao *Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Jing Liu *Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, People's Republic of China.
Xiaohua LiuDepartment of Radiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, People's Republic of China.
Yuqing HeDepartment of Radiology, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, People's Republic of China.
Fei WuDepartment of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.ORCID 0000-0001-5169-0417
Xiaoyan NiDepartment of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Chun YangDepartment of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.ORCID 0000-0002-6293-9158

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To study the MRI features (based on LI-RADS) and clinical characteristics of P53-mutated hepatocellular carcinoma (HCC) patients. Patients and Methods: This study enrolled 344 patients with histopathologically confirmed HCC (P53-mutated group [n = 196], non-P53-mutated group [n = 148]). We retrospectively evaluated the preoperative MRI features, clinical and pathologic features of the lesions and assigned each lesion according to the LI-RADS. MRI findings, clinical features, and pathologic findings were compared using the Student's t test, χ2 test, and multivariable regression analysis. Results: Most HCC patients were categorized as LR-5. On multivariate analysis, the Edmondson-Steiner grade (odds ratio, 2.280; 95% CI: 1.268, 4.101; Conclusion: Poor differentiation and rim enhancement are potential predictive biomarkers for P53-mutated HCC, while HCCs of different diameters have different risk factors for predicting P53 mutations.

Indexed as

liver neoplasmsmagnetic resonance imagingP53-mutated

Identifiers

PMID39224117
PMCPMC11368099

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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.