Evidence map›Paper›PMID 42163157›Full record

ArticleBMC gastroenterology2026

The predictive value of abdominal fat area and volume for early recurrence of after resection hepatocellular carcinoma.

Mi Pei, Xiaoqin Yin, Limei Wang, Guojiao Zuo, Yiman Li, Jie Cheng, Chen Liu, Wei Chen, Ping Cai, Xiaoming Li

Abstract read
In one paragraph

Article in BMC gastroenterology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Mi Pei *7T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Xiaoqin Yin *7T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Limei Wang7T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Guojiao Zuo7T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Yiman Li7T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Jie Cheng7T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Chen Liu7T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Wei Chen7T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Ping Cai7T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China. caiping@tmmu.edu.cn.
Xiaoming Li7T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China. lxm359261069@tmmu.edu.cn.

Funding

Program of the National Natural Science Foundation of Chongqing (Chongqing Science and Technology Development Foundation) CSTB2024NSCQ-KJFZZDX0036This study received funding from the Program of the National Natural Science Foundation of Chongqing CSTB2022NSCQMSX1371
6 · The paper itself

Abstract

backgroundAbdominal fat area has been reported to be associated with early recurrence (ER) after surgical resection of hepatocellular carcinoma (HCC). This study aimed to compare the predictive value of abdominal fat area and volume for ER after resection of HCC.

methodsWe retrospectively included 161 patients with single HCC ≤5 cm who underwent resection from May 2015 to June 2021. Visceral fat area (VFA) and subcutaneous fat area (SFA) were measured at L3, L4, and L5 vertebral levels, and L4-derived parameters were retained for subsequent analyses. Visceral fat volume (VFV) and subcutaneous fat volume (SFV) were assessed from the diaphragm to lower margin of L5. Multivariate analyses were performed to identify predictors of ER. Receiver operating characteristic (ROC) curves were used to compare predictive values.

resultsMultivariate analysis identified VFA and VFV as independent risk factors for ER. ROC analysis showed similar predictive values for VFA (AUC: 0.712) and VFV (AUC: 0.730; p = 0.307). The patients were divided into two groups based on tumor size: group A [(d) ≤ 3 cm] and group B [3 cm < (d) ≤ 5 cm]. VFA demonstrated a higher predictive value for group A (AUC: 0.796) compared to group B (AUC: 0.636) (p = 0.049).

conclusionsBoth VFA and VFV showed comparable predictive value for ER in patients with single HCC ≤5 cm, and VFA appeared to have better predictive performance in patients with tumor diameter ≤ 3 cm.

Indexed as

Abdominal FatCarcinoma, HepatocellularIntra-Abdominal FatLiver NeoplasmsNeoplasm Recurrence, LocalAgedFemaleHepatectomyHumansMaleMiddle AgedPredictive Value of TestsRetrospective StudiesRisk FactorsROC CurveTomography, X-Ray ComputedAbdominal fat areaAbdominal fat volumeComputed tomographyHepatocellular carcinoma

Identifiers

PMID42163157
PMCPMC13361723

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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 Socratic graph.