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Clinical Chemistry and Laboratory Medicine (CCLM)

Published in Association with the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM)

Editor-in-Chief: Plebani, Mario

Hrsg. v. Gillery, Philippe / Greaves, Ronda / Lackner, Karl J. / Lippi, Giuseppe / Melichar, Bohuslav / Payne, Deborah A. / Schlattmann, Peter

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CiteScore 2018: 2.44

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Band 54, Heft 3


The side effects of translational omics: overtesting, overdiagnosis, overtreatment

Eleftherios P. Diamandis
  • Korrespondenzautor
  • Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, ON, Canada
  • Department of Clinical Biochemistry, University Health Network, Toronto, ON, Canada
  • Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
  • E-Mail
  • Weitere Artikel des Autors:
  • De Gruyter OnlineGoogle Scholar
/ Michelle Li
Online erschienen: 07.10.2015 | DOI: https://doi.org/10.1515/cclm-2015-0762


High-throughput technologies such as next-generation genomics, transcriptomics and proteomics are capable of generating massive amounts of data quickly, and at relatively low costs. It is tempting to use this data for various medical applications including preclinical disease detection and for prediction of disease predisposition. Pilot projects, initiated by various research groups and Google, are currently underway, but results with not be available for a few years. We here summarize some possible difficulties with these approaches, by using examples from already tried cancer and other screening programs. Population screening, especially with multiparametric algorithms, will identify at least some false positive parameters and screening programs will identify abnormal results in otherwise healthy individuals. Whole genome sequencing will identify genetic changes of unknown significance and may not predict accurately future disease predisposition if the disease is also influenced by environmental factors. In screening programs, if the disease is rare, the positive predictive value of the test will be low, even if the test has excellent sensitivity and specificity. False positive results may require invasive procedures to delineate. Furthermore, screening programs are not effective if the cancer grows quickly, and will identify indolent forms of the disease with slow-growing tumors. It has also been recently shown that for some cancers, more intensive and radical treatments do not usually lead to better clinical outcomes. We conclude that new omics testing technologies should avoid overdiagnosis and overtreatment and need to be evaluated for overall clinical benefit before introduction to the clinic.

Keywords: escape from cure; high-throughput omics; incidental findings; indolent disease; overdiagnosis; overtesting; overtreatment; side effects


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Corresponding author: Eleftherios P. Diamandis, MD, PhD, FRCP(C), FRSC, Head of Clinical Biochemistry, Mount Sinai Hospital and University Health Network, 60 Murray St. Box 32, Floor 6, Rm L6-201, Toronto, M5T 3L9 ON, Canada, Phone: +(416) 586-8443, E-mail: ; Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, ON, Canada; Department of Clinical Biochemistry, University Health Network, Toronto, ON, Canada; and Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada

Erhalten: 06.08.2015

Angenommen: 28.08.2015

Online erschienen: 07.10.2015

Erschienen im Druck: 01.03.2016

Quellenangabe: Clinical Chemistry and Laboratory Medicine (CCLM), Band 54, Heft 3, Seiten 389–396, ISSN (Online) 1437-4331, ISSN (Print) 1434-6621, DOI: https://doi.org/10.1515/cclm-2015-0762.

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