IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i10p5332-d556266.html
   My bibliography  Save this article

Risk Prediction of Barrett’s Esophagus in a Taiwanese Health Examination Center Based on Regression Models

Author

Listed:
  • Po-Hsiang Lin

    (Department of Emergency Medicine, Kaohsiung Veterans General Hospital, Kaohsiung 813, Taiwan
    Department of Electrical Engineering, I-Shou University, Kaohsiung 840, Taiwan)

  • Jer-Guang Hsieh

    (Department of Electrical Engineering, I-Shou University, Kaohsiung 840, Taiwan)

  • Hsien-Chung Yu

    (Division of Gastroenterology and Hepatology, Department of Internal Medicine, Kaohsiung Veterans General Hospital, Kaohsiung 813, Taiwan
    Health Management Center, Kaohsiung Veterans General Hospital, 386, Ta-Chung 1st Road, Kaohsiung 813, Taiwan
    Institute of Health Care Management, Department of Business Management, National Sun Yat-sen University, Kaohsiung 804, Taiwan
    Department of Nursing, Meiho University, Pingtung 912, Taiwan)

  • Jyh-Horng Jeng

    (Department of Information Engineering, I-Shou University, Kaohsiung 840, Taiwan)

  • Chiao-Lin Hsu

    (Health Management Center, Kaohsiung Veterans General Hospital, 386, Ta-Chung 1st Road, Kaohsiung 813, Taiwan
    Department of Nursing, Meiho University, Pingtung 912, Taiwan)

  • Chien-Hua Chen

    (Department of Electrical Engineering, I-Shou University, Kaohsiung 840, Taiwan
    Department of Emergency Medicine, Taichung Veterans General Hospital Chiayi Branch, Chia-Yi 600, Taiwan)

  • Pin-Chieh Wu

    (Health Management Center, Kaohsiung Veterans General Hospital, 386, Ta-Chung 1st Road, Kaohsiung 813, Taiwan
    Department of Nursing, Meiho University, Pingtung 912, Taiwan
    Department of Chemical Engineering and Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung 840, Taiwan)

Abstract

Determining the target population for the screening of Barrett’s esophagus (BE), a precancerous condition of esophageal adenocarcinoma, remains a challenge in Asia. The aim of our study was to develop risk prediction models for BE using logistic regression (LR) and artificial neural network (ANN) methods. Their predictive performances were compared. We retrospectively analyzed 9646 adults aged ≥20 years undergoing upper gastrointestinal endoscopy at a health examinations center in Taiwan. Evaluated by using 10-fold cross-validation, both models exhibited good discriminative power, with comparable area under curve (AUC) for the LR and ANN models (Both AUC were 0.702). Our risk prediction models for BE were developed from individuals with or without clinical indications of upper gastrointestinal endoscopy. The models have the potential to serve as a practical tool for identifying high-risk individuals of BE among the general population for endoscopic screening.

Suggested Citation

  • Po-Hsiang Lin & Jer-Guang Hsieh & Hsien-Chung Yu & Jyh-Horng Jeng & Chiao-Lin Hsu & Chien-Hua Chen & Pin-Chieh Wu, 2021. "Risk Prediction of Barrett’s Esophagus in a Taiwanese Health Examination Center Based on Regression Models," IJERPH, MDPI, vol. 18(10), pages 1-10, May.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:10:p:5332-:d:556266
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/10/5332/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/10/5332/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zi-Hui Tang & Juanmei Liu & Fangfang Zeng & Zhongtao Li & Xiaoling Yu & Linuo Zhou, 2013. "Comparison of Prediction Model for Cardiovascular Autonomic Dysfunction Using Artificial Neural Network and Logistic Regression Analysis," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    2. Xinxue Liu & Angela Wong & Sudarshan R Kadri & Andrej Corovic & Maria O’Donovan & Pierre Lao-Sirieix & Laurence B Lovat & Rodney W Burnham & Rebecca C Fitzgerald, 2014. "Gastro-Esophageal Reflux Disease Symptoms and Demographic Factors as a Pre-Screening Tool for Barrett’s Esophagus," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-8, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      Corrections

      All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:10:p:5332-:d:556266. See general information about how to correct material in RePEc.

      If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

      If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

      For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

      Please note that corrections may take a couple of weeks to filter through the various RePEc services.

      IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.