Literature DB >> 35004943

Development and validation of a machine learning-based nomogram for prediction of intrahepatic cholangiocarcinoma in patients with intrahepatic lithiasis.

Xian Shen1, Huanhu Zhao2, Xing Jin3, Junyu Chen4, Zhengping Yu4, Kuvaneshan Ramen5, Xiangwu Zheng6, Xiuling Wu7, Yunfeng Shan4, Jianling Bai8, Qiyu Zhang4, Qiqiang Zeng1.   

Abstract

BACKGROUND: Accurate diagnosis of intrahepatic cholangiocarcinoma (ICC) caused by intrahepatic lithiasis (IHL) is crucial for timely and effective surgical intervention. The aim of the present study was to develop a nomogram to identify ICC associated with IHL (IHL-ICC).
METHODS: The study included 2,269 patients with IHL, who received pathological diagnosis after hepatectomy or diagnostic biopsy. Machine learning algorithms including Lasso regression and random forest were used to identify important features out of the available features. Univariate and multivariate logistic regression analyses were used to reconfirm the features and develop the nomogram. The nomogram was externally validated in two independent cohorts.
RESULTS: The seven potential predictors were revealed for IHL-ICC, including age, abdominal pain, vomiting, comprehensive radiological diagnosis, alkaline phosphatase (ALK), carcinoembryonic antigen (CEA), and cancer antigen (CA) 19-9. The optimal cutoff value was 2.05 µg/L for serum CEA and 133.65 U/mL for serum CA 19-9. The accuracy of the nomogram in predicting ICC was 82.6%. The area under the curve (AUC) of nomogram in training cohort was 0.867. The AUC for the validation set was 0.881 from The Second Affiliated Hospital of Wenzhou Medical University, and 0.938 from The First Affiliated Hospital of Fujian Medical University.
CONCLUSIONS: The nomogram holds promise as a novel and accurate tool to predict IHL-ICC, which can identify lesions in IHL in time for hepatectomy or avoid unnecessary surgical resection. 2021 Hepatobiliary Surgery and Nutrition. All rights reserved.

Entities:  

Keywords:  Intrahepatic cholangiocarcinoma (ICC); intrahepatic lithiasis (IHL); machine learning; nomogram; risk factors

Year:  2021        PMID: 35004943      PMCID: PMC8683924          DOI: 10.21037/hbsn-20-332

Source DB:  PubMed          Journal:  Hepatobiliary Surg Nutr        ISSN: 2304-3881            Impact factor:   7.293


  41 in total

1.  Intrahepatic cholangiocarcinoma and hepatitis C and B virus infection, alcohol intake, and hepatolithiasis: a case-control study in Italy.

Authors:  F Donato; U Gelatti; A Tagger; M Favret; M L Ribero; F Callea; C Martelli; A Savio; P Trevisi; G Nardi
Journal:  Cancer Causes Control       Date:  2001-12       Impact factor: 2.506

Review 2.  Peripheral cholangiocarcinoma (cholangiocellular carcinoma): clinical features, diagnosis and treatment.

Authors:  M F Chen
Journal:  J Gastroenterol Hepatol       Date:  1999-12       Impact factor: 4.029

Review 3.  Serum and bile biomarkers for cholangiocarcinoma.

Authors:  Domenico Alvaro
Journal:  Curr Opin Gastroenterol       Date:  2009-05       Impact factor: 3.287

4.  Intrahepatic cholangiocarcinoma: expert consensus statement.

Authors:  Sharon M Weber; Dario Ribero; Eileen M O'Reilly; Norihiro Kokudo; Masaru Miyazaki; Timothy M Pawlik
Journal:  HPB (Oxford)       Date:  2015-08       Impact factor: 3.647

Review 5.  Nomograms in oncology: more than meets the eye.

Authors:  Vinod P Balachandran; Mithat Gonen; J Joshua Smith; Ronald P DeMatteo
Journal:  Lancet Oncol       Date:  2015-04       Impact factor: 41.316

6.  Hepatolithiasis: analysis of Japanese nationwide surveys over a period of 40 years.

Authors:  Yutaka Suzuki; Toshiyuki Mori; Masaaki Yokoyama; Tetsuya Nakazato; Nobutsugu Abe; Yasuni Nakanuma; Hirohito Tsubouchi; Masanori Sugiyama
Journal:  J Hepatobiliary Pancreat Sci       Date:  2014-05-14       Impact factor: 7.027

7.  Risk factors for intrahepatic cholangiocarcinoma: a case-control study in China.

Authors:  Yan-Ming Zhou; Zheng-Feng Yin; Jia-Mei Yang; Bin Li; Wen-Yu Shao; Feng Xu; Yu-Lan Wang; Dian-Qi Li
Journal:  World J Gastroenterol       Date:  2008-01-28       Impact factor: 5.742

8.  Hepatitis B virus infection and intrahepatic cholangiocarcinoma in Korea: a case-control study.

Authors:  Tae Y Lee; Sang S Lee; Seok W Jung; Seong H Jeon; Sung-Cheol Yun; Hyoung-Chul Oh; Seunghyun Kwon; Sung K Lee; Dong W Seo; Myung-Hwan Kim; Dong J Suh
Journal:  Am J Gastroenterol       Date:  2008-06-28       Impact factor: 10.864

9.  Worldwide trends in mortality from biliary tract malignancies.

Authors:  Tushar Patel
Journal:  BMC Cancer       Date:  2002-05-03       Impact factor: 4.430

Review 10.  Diagnostic Accuracy of Serum CA19-9 in Patients with Cholangiocarcinoma: A Systematic Review and Meta-Analysis.

Authors:  Bin Liang; Liansheng Zhong; Qun He; Shaocheng Wang; Zhongcheng Pan; Tianjiao Wang; Yujie Zhao
Journal:  Med Sci Monit       Date:  2015-11-18
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  2 in total

Review 1.  Recent Advances of Deep Learning for Computational Histopathology: Principles and Applications.

Authors:  Yawen Wu; Michael Cheng; Shuo Huang; Zongxiang Pei; Yingli Zuo; Jianxin Liu; Kai Yang; Qi Zhu; Jie Zhang; Honghai Hong; Daoqiang Zhang; Kun Huang; Liang Cheng; Wei Shao
Journal:  Cancers (Basel)       Date:  2022-02-25       Impact factor: 6.639

2.  Exploring the function of stromal cells in cholangiocarcinoma by three-dimensional bioprinting immune microenvironment model.

Authors:  Changcan Li; Bao Jin; Hang Sun; Yunchao Wang; Haitao Zhao; Xinting Sang; Huayu Yang; Yilei Mao
Journal:  Front Immunol       Date:  2022-08-02       Impact factor: 8.786

  2 in total

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