Evidence map›Paper›PMID 37693156›Full record

ArticleAmerican journal of cancer research2023

Adding nutritional status to the original BCLC stage improves mortality prediction for hepatocellular carcinoma patients in HBV-endemic regions.

Yan-Ting Lin, Po-Ting Lin, Chen-Chun Lin, Tsung-Han Wu, Li-Tong Liu, Chung-Wei Su, Wei Teng, Chun-Yi Tsai, Chien-Hao Huang, Wei-Ting Chen and 5 more

Abstract read
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Article in American journal of cancer research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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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3 · Its place in the literature

Who cites it

4 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

15 authors.

Yan-Ting LinDivision of Hepatology, Department of Gastroenterology and Hepatology, Chang-Gung Memorial Hospital, Linkou Medical Center Taoyuan, Taiwan.
Po-Ting LinDivision of Hepatology, Department of Gastroenterology and Hepatology, Chang-Gung Memorial Hospital, Linkou Medical Center Taoyuan, Taiwan.
Chen-Chun LinDivision of Hepatology, Department of Gastroenterology and Hepatology, Chang-Gung Memorial Hospital, Linkou Medical Center Taoyuan, Taiwan.
Tsung-Han WuCollege of Medicine, Chang-Gung University Taoyuan, Taiwan.
Li-Tong LiuDivision of Hepatology, Department of Gastroenterology and Hepatology, Chang-Gung Memorial Hospital, Linkou Medical Center Taoyuan, Taiwan.
Chung-Wei SuDivision of Hepatology, Department of Gastroenterology and Hepatology, Chang-Gung Memorial Hospital, Linkou Medical Center Taoyuan, Taiwan.
Wei TengDivision of Hepatology, Department of Gastroenterology and Hepatology, Chang-Gung Memorial Hospital, Linkou Medical Center Taoyuan, Taiwan.
Chun-Yi TsaiCollege of Medicine, Chang-Gung University Taoyuan, Taiwan.
Chien-Hao HuangDivision of Hepatology, Department of Gastroenterology and Hepatology, Chang-Gung Memorial Hospital, Linkou Medical Center Taoyuan, Taiwan.
Wei-Ting ChenDivision of Hepatology, Department of Gastroenterology and Hepatology, Chang-Gung Memorial Hospital, Linkou Medical Center Taoyuan, Taiwan.
Kun-Ming ChanCollege of Medicine, Chang-Gung University Taoyuan, Taiwan.
Chao-Wei HsuDivision of Hepatology, Department of Gastroenterology and Hepatology, Chang-Gung Memorial Hospital, Linkou Medical Center Taoyuan, Taiwan.
Chun-Yen LinDivision of Hepatology, Department of Gastroenterology and Hepatology, Chang-Gung Memorial Hospital, Linkou Medical Center Taoyuan, Taiwan.
Shi-Ming LinDivision of Hepatology, Department of Gastroenterology and Hepatology, Chang-Gung Memorial Hospital, Linkou Medical Center Taoyuan, Taiwan.
Rong-Nan ChienDivision of Hepatology, Department of Gastroenterology and Hepatology, Chang-Gung Memorial Hospital, Linkou Medical Center Taoyuan, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is associated with high mortality, especially in Asian populations where chronic HBV infection is a major cause. Accurate prediction of mortality can assist clinical decision-making. We aim to (i) compare the predicting ability of Barcelona Clinic Liver Cancer classification (BCLC) stage, neutrophil-to-lymphocyte ratio (NLR), and Albumin-Bilirubin (ALBI) score in predicting short-term mortality (one- and two-year) and (ii) develop a novel model with improved accuracy compared to the conventional models. This study enrolled 298 consecutive HCC patients from our hepatology department. The prognostic values for mortality were assessed by area under the receiver operating characteristic curve (AUROC) analysis. A novel model was established and internally validated using 5-fold cross-validation, followed by external validation in a cohort of 100 patients. The primary etiology of cirrhosis was hepatitis B virus (HBV), with 81.2% of HCC patients having preserved liver function. Significant differences were observed in hemoglobin (Hb) and serum albumin levels, which reflect patients' nutrition status, between patients who survived for one year and those who died. BCLC exhibited superior predictive accuracy compared to NLR but had borderline superiority to the ALBI score. Therefore, a novel model incorporating BCLC, Hb, and serum albumin was developed, internally and externally validated, as well as subgroup sensitivity analysis. The model exhibited significantly higher predictive accuracy for one- and two-year mortality than conventional prognostic predictors, with AUROC values of 0.841 and 0.805, respectively. The novel "BCLC-Nutrition Model", which incorporates BCLC, Hb, and serum albumin, may provide improved predictive accuracy for short-term mortality in HCC patients compared to commonly used prognostic scores. This emphasizes the importance of nutrition in the management of HCC patients.

Indexed as

5-fold cross-validationalbumin-bilirubin (ALBI) scorearea under receiver operating characteristic curve (AUROC)Barcelona Clinic Liver Cancer (BCLC) stageHepatocellular carcinoma (HCC)internal and external validationmodel buildingneutrophil-lymphocyte ratio (NLR)nutritional statusshort-term mortalitysubgroup sensitivity analysis

Identifiers

PMID37693156
PMCPMC10492128

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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.