Evidence map›Paper›PMID 40414618›Full record

ArticleCancer science2025

A Novel Method for Prognostic Risk Classification After Carbon-Ion Radiotherapy for Hepatocellular Carcinoma Using Data-Mining Methods.

Kazuhiko Hayashi, Osamu Suzuki, Koji Ichise, Hirofumi Uchida, Makoto Anzai, Azusa Hasegawa, Shinichi Shimizu, Teruki Teshima, Jiro Fujimoto, Kazuhiko Ogawa

Abstract read
In one paragraph

Article in Cancer science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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4 · The record

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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.

Kazuhiko HayashiDepartment of Radiology, Osaka Heavy Ion Therapy Center, Osaka, Japan.ORCID https://orcid.org/0000-0001-5054-4629
Osamu SuzukiDepartment of Radiology, Osaka Heavy Ion Therapy Center, Osaka, Japan.
Koji IchiseDepartment of Radiology, Osaka Heavy Ion Therapy Center, Osaka, Japan.
Hirofumi UchidaDepartment of Radiology, Osaka Heavy Ion Therapy Center, Osaka, Japan.
Makoto AnzaiDepartment of Radiology, Osaka Heavy Ion Therapy Center, Osaka, Japan.
Azusa HasegawaDepartment of Radiology, Osaka Heavy Ion Therapy Center, Osaka, Japan.
Shinichi ShimizuDepartment of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka, Japan.
Teruki TeshimaDepartment of Radiology, Osaka Heavy Ion Therapy Center, Osaka, Japan.
Jiro FujimotoDepartment of Radiology, Osaka Heavy Ion Therapy Center, Osaka, Japan.
Kazuhiko OgawaDepartment of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

No classification methods to predict prognosis after carbon-ion radiotherapy for hepatocellular carcinoma have yet been reported. This study aimed to develop risk classification for cancer-specific survival (CSS) after carbon-ion radiotherapy for hepatocellular carcinoma using decision tree analysis as a data-mining method. In this single-center, retrospective study, we analyzed 90 consecutive patients with hepatocellular carcinoma treated with carbon-ion radiotherapy between 2018 and 2022. Liver tumors were irradiated at 60 Gy (relative biological effectiveness [RBE]) in four fractions. If the tumor was close to the gastrointestinal tract, it was irradiated at 60 Gy [RBE] in 12 fractions. Univariate and multivariate analyses of progression-free survival (PFS) and CSS were performed to assess patients' background and treatment-related factors. Decision tree analysis (DTA) was performed to assess prognostic factors for CSS that were significantly different in the multivariate analysis. The median follow-up period was 32.8 months for all patients and 35.6 months for survivors. Multivariate analysis identified dose fractionation and pretreatment alpha-fetoprotein values as significant prognostic factors for PFS and CSS. Moreover, clinical stage and pretreatment protein induced by vitamin K absence or antagonist ΙΙ values were significant prognostic factors for CSS. DTA revealed that the patients could be divided into three groups according to prognosis: low-risk, high-risk, and intermediate-risk. Consequently, the 3-year CSS rates for the low-, intermediate-, and high-risk groups were 100%, 73.3%, and 44.4%, respectively. DTA represents a new method for risk classification for CSS after carbon-ion radiotherapy for hepatocellular carcinoma based on tumor markers and clinical stage.

Indexed as

Carcinoma, HepatocellularData MiningHeavy Ion RadiotherapyLiver NeoplasmsAdultAgedAged, 80 and overDecision TreesFemaleHumansMaleMiddle AgedPrognosisRetrospective Studiescarbon‐ion radiotherapydata‐mining methoddecision tree analysishepatocellular carcinomaprognosis

Identifiers

PMID40414618
PMCPMC12317380

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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.