Evidence map›Paper›PMID 41451114›Full record

ArticleJournal of hepatocellular carcinoma2025

Predicting the Occurrence of Cachexia in Patients with BCLC Stage B/C Hepatocellular Carcinoma Receiving Systemic Therapy: A Nomogram Based on Common Clinical Parameters.

Weihong Ma, Jie Han, Hongli Yu, Zhipeng Liang, Caiyun Peng, Yinying Lu

Abstract read
In one paragraph

Article in Journal of hepatocellular carcinoma, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Weihong MaSenior Department of Hepatology, The 5th Medical Center of the PLA General Hospital, Beijing, People's Republic of China.
Jie HanSenior Department of Hepatology, The 5th Medical Center of the PLA General Hospital, Beijing, People's Republic of China.
Hongli YuSenior Department of Hepatology, The 5th Medical Center of the PLA General Hospital, Beijing, People's Republic of China.
Zhipeng LiangGuizhou Medical University, Guizhou, People's Republic of China.
Caiyun PengSenior Department of Hepatology, The 5th Medical Center of the PLA General Hospital, Beijing, People's Republic of China.
Yinying LuSenior Department of Hepatology, The 5th Medical Center of the PLA General Hospital, Beijing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objective: During the disease course of patients with BCLC B/C hepatocellular carcinoma (HCC) receiving systemic therapy, approximately half of the patients will develop cachexia. Therefore, early identification of which patients are likely to develop cachexia is of crucial significance.This study aims to construct and validate a nomogram for predicting the risk of cachexia in this population based on common clinical parameters. Patients and Methods: This retrospective single - center study involved 906 patients managed at the Fifth Medical Center of Chinese PLA General Hospital from January 2020 to December 2023. Baseline clinical imaging data, biochemical indicators, and relevant clinical data of patients before systemic treatment were collected. All patients were followed up to record treatment regimens and document weight changes for cachexia diagnosis. The data were stratified into a training cohort and a validation cohort. In this study, LASSO regression alongside univariate and multivariate Logistic regression analyses were utilized to ascertain independent risk factors linked to cachexia occurrence, and further to construct and validate a diagnostic nomogram. Results: This nomogram incorporates predictors such as patient age, maximum size of intrahepatic lesions, extrahepatic metastasis, neutrophil-to-lymphocyte ratio (NLR), and total bile acids, demonstrating good predictive performance. In the training and validation cohorts, its Harrell's concordance index (C-index) reached 0.865 (95% CI: 0.836-0.895) and 0.820 (95% CI: 0.768-0.871), respectively. Calibration curves demonstrated strong consistency between the nomogram's predicted outcomes and the actual measured values, and decision curve analysis (DCA) further substantiated its clinical applicability. Conclusion: This nomogram shows good predictive performance and can effectively identify high-risk individuals, but it is limited by its single-center retrospective design and requires further verification and optimization through multicenter prospective studies.

Indexed as

cancer-related cachexiamodel evaluationtargeted immunotherapyweight loss

Identifiers

PMID41451114
PMCPMC12732188

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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.