Literature DB >> 26344337

Cancer screening through a multi-analyte serum biomarker panel during health check-up examinations: Results from a 12-year experience.

Ying-Hao Wen1, Pi-Yueh Chang2, Chen-Ming Hsu3, Hsin-Yao Wang1, Cheng-Tang Chiu3, Jang-Jih Lu4.   

Abstract

BACKGROUND: The use of blood-based tumor biomarkers for screening malignancies at early stages has significant advantages, including being convenient, automated, quantitative, objective, and relatively inexpensive compared with histology, endoscopy, and imaging.
METHODS: We describe our 12-year experience on the diagnostic usefulness of a biomarker panel consisting of eight molecules (i.e., α-fetoprotein, carcinoembryonic antigen, prostate-specific antigen, CA 19-9, CA125, CA 15-3, squamous cell specific antigen, and cytokeratin 19 fragment) for cancer screening in Taiwanese subjects who underwent a health check-up examination at their own expenses.
RESULTS: The sensitivity of the panel for the detection of specific cancers was higher than that of isolated cancer-specific markers. Specifically, the sensitivity of the panel for identifying the four most commonly diagnosed malignancies (i.e., liver cancer, lung cancer, prostate cancer, and colorectal cancer) was 90.9%, 75.0%, 100%, and 76.9%, respectively. The ability of the panel to detect early-stage (stage 1) hepatocellular carcinoma (HCC) or prostate cancer was similar to that observed for advanced malignancies.
CONCLUSIONS: The multi-analyte biomarker panel is clinically useful during health check-up examinations for the screening of different tumors (especially for the early detection of HCC and prostate malignancies).
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Biomarker; Cancer screening; Tumor marker

Mesh:

Substances:

Year:  2015        PMID: 26344337     DOI: 10.1016/j.cca.2015.09.004

Source DB:  PubMed          Journal:  Clin Chim Acta        ISSN: 0009-8981            Impact factor:   3.786


  4 in total

1.  Biomarker identification of hepatocellular carcinoma using a methodical literature mining strategy.

Authors:  Nai-Wen Chang; Hong-Jie Dai; Yung-Yu Shih; Chi-Yang Wu; Mira Anne C Dela Rosa; Rofeamor P Obena; Yu-Ju Chen; Wen-Lian Hsu; Yen-Jen Oyang
Journal:  Database (Oxford)       Date:  2017-01-01       Impact factor: 3.451

2.  Cancers Screening in an Asymptomatic Population by Using Multiple Tumour Markers.

Authors:  Hsin-Yao Wang; Chia-Hsun Hsieh; Chiao-Ni Wen; Ying-Hao Wen; Chun-Hsien Chen; Jang-Jih Lu
Journal:  PLoS One       Date:  2016-06-29       Impact factor: 3.240

3.  Uncovering nasopharyngeal carcinoma from chronic rhinosinusitis and healthy subjects using routine medical tests via machine learning.

Authors:  Qi Liu; Jinyang Du; Yuge Li; Guiyuan Peng; Xuefang Wang; Yong Zhong; Ruxu Du
Journal:  PLoS One       Date:  2022-09-09       Impact factor: 3.752

4.  Tumor characterization by ultrasound-release of multiple protein and microRNA biomarkers, preclinical and clinical evidence.

Authors:  Aloma L D'Souza; John R Chevillet; Pejman Ghanouni; Xinrui Yan; Muneesh Tewari; Sanjiv S Gambhir
Journal:  PLoS One       Date:  2018-03-16       Impact factor: 3.240

  4 in total

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