| Combined Application of Information Theory on Laboratory Results with Classification and Regression Tree Analysis: Analysis of Unnecessary Biopsy for Prostate Cancer. | |
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MedLine Citation:
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PMID: 23078854 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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BACKGROUND: The probability of a prostate cancer-positive biopsy result varies with PSA concentration. Thus, we applied information theory on classification and regression tree analysis (CART) for decision making predicting the probability of a biopsy result at various PSA concentrations. METHODS: From 2007 to 2009, prostate biopsies were performed in 664 referred patients in a tertiary hospital. We created 2 CART models based on the information theory: one for moderate uncertainty (PSA concentration: 2.5 - 10ng/ml) and the other for high uncertainty (PSA concentration: 10-25ng/ml). RESULTS: The CART model for moderate uncertainty (n=321) had 3 splits based on PSA density (PSAD), hypoechoic nodules, and age and the other CART for high uncertainty (n=160) had 2 splits based on prostate volume and free PSA. In this validation set, the patients (14.3 % and 14.0 % for moderate and high uncertainty groups, respectively) could avoid unnecessary biopsies without false-negative results. CONCLUSIONS: Using these CART models based on uncertainty information of PSA, the overall reduction in unnecessary prostate biopsies was 14.0 - 14.3 % and CART models were simplified. Using uncertainty of laboratory results from information theoretic approach can provide additional information for decision analysis such as CART. |
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Authors:
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Sang-Hyun Hwang; Tina Pyo; Heung-Bum Oh; Hyun Jun Park; Kwan-Jeh Lee |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2012-10-15 |
Journal Detail:
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Title: Clinica chimica acta; international journal of clinical chemistry Volume: - ISSN: 1873-3492 ISO Abbreviation: Clin. Chim. Acta Publication Date: 2012 Oct |
Date Detail:
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Created Date: 2012-10-19 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 1302422 Medline TA: Clin Chim Acta Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Copyright Information:
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Copyright © 2012. Published by Elsevier B.V. |
Affiliation:
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Department of Laboratory Medicine, Center for Diagnostic Oncology, Research Institute and Hospital, National Cancer Center, Goyang-si, South Korea. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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