Evidence map›Paper›PMID 41090669›Full record

ArticleCancer medicine2025

A New Model to Predict Survival Time in Patients With Hepatocellular Carcinoma With BCLC Advanced Stage.

Masashi Ninomiya, Mio Tsuruoka, Jun Inoue, Atsushi Hiraoka, Akitoshi Sano, Kosuke Sato, Masazumi Onuki, Satoko Sawahashi, Keishi Ouchi, Kengo Watanabe and 14 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer medicine, 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

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

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

24 authors.

Masashi NinomiyaDivision of Gastroenterology, Tohoku University Hospital, Sendai, Japan.ORCID https://orcid.org/0000-0002-6154-8075
Mio TsuruokaDivision of Gastroenterology, Tohoku University Hospital, Sendai, Japan.
Jun InoueDivision of Gastroenterology, Tohoku University Hospital, Sendai, Japan.
Atsushi HiraokaGastroenterology Center, Ehime Prefectural Central Hospital, Ehime, Japan.
Akitoshi SanoDivision of Gastroenterology, Tohoku University Hospital, Sendai, Japan.
Kosuke SatoDivision of Gastroenterology, Tohoku University Hospital, Sendai, Japan.
Masazumi OnukiDivision of Gastroenterology, Tohoku University Hospital, Sendai, Japan.
Satoko SawahashiDivision of Gastroenterology, Tohoku University Hospital, Sendai, Japan.
Keishi OuchiDivision of Gastroenterology, Tohoku University Hospital, Sendai, Japan.
Kengo WatanabeDivision of Gastroenterology, Tohoku University Hospital, Sendai, Japan.
Hidekatsu KurodaDivision of Gastroenterology and Hepatology, Department of Internal Medicine, Iwate Medical University, Iwate, Japan.
Takayoshi OikawaDivision of Gastroenterology and Hepatology, Department of Internal Medicine, Iwate Medical University, Iwate, Japan.
Tamami AbeDivision of Gastroenterology and Hepatology, Department of Internal Medicine, Iwate Medical University, Iwate, Japan.
Masashi FujitaDepartment of Gastroenterology, School of Medicine, Fukushima Medical University, Fukushima, Japan.
Kazumichi AbeDepartment of Gastroenterology, School of Medicine, Fukushima Medical University, Fukushima, Japan.
Tomohiro KatsumiDepartment of Gastroenterology, Faculty of Medicine, Yamagata University, Yamagata, Japan.
Wataru SatoDepartment of Gastroenterology, Graduate School of Medicine, Akita University, Akita, Japan.
Go IgarashiDepartment of Gastroenterology, Graduate School of Medicine, Hirosaki University, Hirosaki, Japan.
Chikara IinoDepartment of Gastroenterology, Graduate School of Medicine, Hirosaki University, Hirosaki, Japan.ORCID https://orcid.org/0000-0001-6844-4415
Nobukazu TanabeDepartment of Gastroenterology, National Hospital Organization Sendai Medical Center, Sendai, Japan.
Hiroshi NumaoDepartment of Gastroenterology, Aomori Prefectural Central Hospital, Aomori, Japan.
Hiromasa OhiraDepartment of Gastroenterology, School of Medicine, Fukushima Medical University, Fukushima, Japan.
Yoshiyuki UenoDepartment of Gastroenterology, Faculty of Medicine, Yamagata University, Yamagata, Japan.
Atsushi MasamuneDivision of Gastroenterology, Tohoku University Hospital, Sendai, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The variety of treatments available makes it difficult to determine whether a treatment would be effective for an individual case in advanced-stage hepatocellular carcinoma. We aimed to establish a new model of survival prediction in patients to establish standards in the recent and coming multimolecular targeted agents era. This analysis was prepared using a data set of 518 patients diagnosed with hepatocellular carcinoma prior to 2017. Multiple regression analysis showed the size of the largest tumor nodule, the number of nodules, macrovascular invasion, extrahepatic metastasis, total bilirubin, albumin, prothrombin time (PT), α-fetoprotein, and des-γ-carboxyprothrombin (DCP) as independent predictors of survival. A Weibull model had the best fit and, based on these predictors, we established two new predicted survival models with or without incorporating PT and DCP. This model is useful for planning and evaluating the efficacy of recent sequential therapies in the multimolecular targeted agents era.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsAdultAgedalpha-FetoproteinsBiomarkersFemaleHumansMaleMiddle AgedNeoplasm StagingPrognosisProtein PrecursorsProthrombinacarboxyprothrombinalpha-FetoproteinsBiomarkersProtein PrecursorsProthrombinBCLC advanced stage HCCoverall survivalparametric modelsurvival predictors

Identifiers

PMID41090669
PMCPMC12522174

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.