Evidence map›Paper›PMID 34334138›Full record

ArticleWorld journal of surgical oncology2021

The preoperative prognostic value of the radiomics nomogram based on CT combined with machine learning in patients with intrahepatic cholangiocarcinoma.

Youyin Tang, Tao Zhang, Xianghong Zhou, Yunuo Zhao, Hanyue Xu, Yichun Liu, Hang Wang, Zheyu Chen, Xuelei Ma

Abstract read
In one paragraph

Article in World journal of surgical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

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21citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

What it found

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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

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Applications of artificial intelligence in biliary tract cancers.Indian journal of gastroenterology : official journal of the Indian Society of Gastroenterology · 2024
    Review
  6. Article
  7. Application of AI on cholangiocarcinoma.Frontiers in oncology · 2024
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

9 authors.

Youyin Tang *Department of Liver Surgery, Liver Transplantation Center, West China Hospital of Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, People's Republic of China.
Tao Zhang *West China School of Medicine, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, People's Republic of China.
Xianghong ZhouDepartment of Biotherapy, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, People's Republic of China.
Yunuo ZhaoWest China School of Medicine, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, People's Republic of China.
Hanyue XuWest China School of Medicine, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, People's Republic of China.
Yichun LiuWest China School of Public Health, NO.4 West China Teaching Hospital, Sichuan University, No. 18, three section of people south road, Chengdu, 610041, People's Republic of China.
Hang WangWest China School of Medicine, West China Hospital, Sichuan University, No.14, 3Rd Section Of Ren Min Nan Rd., Chengdu, Sichuan, 610041, People's Republic of China.
Zheyu ChenDepartment of Liver Surgery, Division of Liver Transplantation Center, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, People's Republic of China. Chenzheyu@scu.edu.cn.ORCID http://orcid.org/0000-0003-4059-4774
Xuelei MaDepartment of Biotherapy, West China Hospital and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, People's Republic of China. drmaxuelei@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIntrahepatic cholangiocarcinoma is an aggressive liver carcinoma with increasing incidence and mortality. A good auxiliary prognostic prediction tool is desperately needed for the development of treatment strategies. The purpose of this study was to explore the prognostic value of the radiomics nomogram based on enhanced CT in intrahepatic cholangiocarcinoma.

methodsIn this retrospective study, 101 patients with pathological confirmation of intrahepatic cholangiocarcinoma were recruited. A radiomics nomogram was developed by radiomics score and independent clinical risk factors selecting from multivariate Cox regression. All patients were stratified as high risk and low risk by a nomogram. Model performance and clinical usefulness were assessed by calibration curve, ROC curve, and survival curve.

resultsA total of 101patients (mean age, 58.2 years old; range 36-79 years old) were included in the study. The 1-year, 3-year, and 5-year overall survival rates were 49.5%, 26.6%, and 14.4%, respectively, with a median survival time of 12.2 months in the whole set. The least absolute shrinkage and selection operator (LASSO) method selected 3 features. Multivariate Cox analysis found three independent prognostic factors. The radiomics nomogram showed a significant prognosis value with overall survival. There was a significant difference in the 1-year and 3-year survival rates of stratified high-risk and low-risk patients in the whole set (30.4% vs. 56.4% and 13.0% vs. 30.6%, respectively, p = 0.018).

conclusionsThis radiomics nomogram has potential application value in the preoperative prognostic prediction of intrahepatic cholangiocarcinoma and may facilitate in clinical decision-making.

Indexed as

Bile Duct NeoplasmsCholangiocarcinomaAdultAgedHumansMachine LearningMiddle AgedNomogramsPrognosisRetrospective StudiesTomography, X-Ray ComputedIntrahepatic cholangiocarcinomaMachine learningNomogramPrognosisRadiomics

Identifiers

PMID34334138
PMCPMC8327418

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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.