Evidence map›Paper›PMID 40895195›Full record

ArticleJournal of hepatocellular carcinoma2025

Screening Candidates for Conversion Therapy in Unresectable Hepatocellular Carcinoma Patients After Tyrosine Kinase Inhibitor Plus PD-1/PD-L1 Antibody Therapy: A Multicenter Retrospective Study.

Zhe Jin, Xueyan Li, Ling Lv, Bin Zhang, Xiao Ma, Siqin Chen, Jingjing You, Xuewei Wu, Liaoyuan Wang, Xin Liu and 5 more

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. 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

15 authors.

Zhe Jin *Department of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, People's Republic of China.ORCID 0000-0001-5737-9267
Xueyan Li *Department of Nuclear Medicine, Hainan Cancer Hospital, Haikou, Hainan, People's Republic of China.ORCID 0000-0002-7753-8429
Ling Lv *Department of Radiology, Guangdong Provincial Key Laboratory of Major Obstetric Diseases; Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology; The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, People's Republic of China.
Bin ZhangDepartment of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, People's Republic of China.
Xiao MaDepartment of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, People's Republic of China.
Siqin ChenDepartment of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, People's Republic of China.
Jingjing YouDepartment of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, People's Republic of China.
Xuewei WuDepartment of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, People's Republic of China.ORCID 0000-0003-0447-0221
Liaoyuan WangDepartment of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, People's Republic of China.
Xin LiuDepartment of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, People's Republic of China.
Fei WangDepartment of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, People's Republic of China.
Xiaoming ChenDepartment of Minimally Invasive Intervention, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, People's Republic of China.
Lijuan YuDepartment of Nuclear Medicine, Hainan Cancer Hospital, Haikou, Hainan, People's Republic of China.
Shuixing ZhangDepartment of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, People's Republic of China.
Lu ZhangDepartment of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, People's Republic of China.ORCID 0000-0002-1652-7523

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Conversion therapies after immune checkpoint inhibitors (ICIs) plus tyrosine-kinase inhibitors (TKIs) provide curative surgery chance and prolong survival for unresectable hepatocellular carcinoma (uHCC). However, only some patients have the opportunity to receive conversion therapies. To this end, we aimed to develop and validate a machine-learning model to identify patients who may have the chance to undergo conversion therapy. Methods: This retrospective cohort study included 443 patients with uHCC who received ICIs and TKIs from four centers. Variables were analyzed using univariate and multivariate logistic regression to identify independent indicators of conversion therapy. The Gradient Boosting Machine (GBM) algorithm was used to develop and validate model, and the Shapley additive explanation algorithm was used to mechanically explain the prediction of the model. Results: Overall, 84 (19%) patients underwent conversion therapy, and their prognosis were significantly longer than those did not ( Conclusion: The GBM-based combined model could identify patients who may benefit from conversion therapy for uHCC treated with ICIs and TKIs. Surgical resection as curative conversion therapy may provide better survival benefits than ablation therapy.

Indexed as

curative conversion therapyhepatocellular carcinomaimmune checkpoint inhibitormachine learningtyrosine kinase inhibitor

Identifiers

PMID40895195
PMCPMC12396238

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