Correlates of circulating ovarian cancer early detection markers and their contribution to discrimination of early detection models: results from the ... View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-03-20

AUTHORS

Renée T. Fortner, Allison F. Vitonis, Helena Schock, Anika Hüsing, Theron Johnson, Raina N. Fichorova, Titilayo Fashemi, Hidemi S. Yamamoto, Anne Tjønneland, Louise Hansen, Kim Overvad, Marie-Christine Boutron-Ruault, Marina Kvaskoff, Gianluca Severi, Heiner Boeing, Antonia Trichopoulou, Vassiliki Benetou, Carlo La Vecchia, Domenico Palli, Sabina Sieri, Rosario Tumino, Giuseppe Matullo, Amalia Mattiello, N. Charlotte Onland-Moret, Petra H. Peeters, Elisabete Weiderpass, Inger Torhild Gram, Mie Jareid, J. Ramón Quirós, Eric J. Duell, Maria-Jose Sánchez, María Dolores Chirlaque, Eva Ardanaz, Nerea Larrañaga, Björn Nodin, Jenny Brändstedt, Annika Idahl, Kay-Tee Khaw, Naomi Allen, Marc Gunter, Mattias Johansson, Laure Dossus, Melissa A. Merritt, Elio Riboli, Daniel W. Cramer, Rudolf Kaaks, Kathryn L. Terry

ABSTRACT

BACKGROUND: Ovarian cancer early detection markers CA125, CA15.3, HE4, and CA72.4 vary between healthy women, limiting their utility for screening. METHODS: We evaluated cross-sectional relationships between lifestyle and reproductive factors and these markers among controls (n = 1910) from a nested case-control study in the European Prospective Investigation into Cancer and Nutrition (EPIC). Improvements in discrimination of prediction models adjusting for correlates of the markers were evaluated among postmenopausal women in the nested case-control study (n = 590 cases). Generalized linear models were used to calculate geometric means of CA125, CA15.3, and HE4. CA72.4 above vs. below limit of detection was evaluated using logistic regression. Early detection prediction was modeled using conditional logistic regression. RESULTS: CA125 concentrations were lower, and CA15.3 higher, in post- vs. premenopausal women (p ≤ 0.02). Among postmenopausal women, CA125 was higher among women with higher parity and older age at menopause (ptrend ≤ 0.02), but lower among women reporting oophorectomy, hysterectomy, ever use of estrogen-only hormone therapy, or current smoking (p < 0.01). CA15.3 concentrations were higher among heavier women and in former smokers (p ≤ 0.03). HE4 was higher with older age at blood collection and in current smokers, and inversely associated with OC use duration, parity, and older age at menopause (≤ 0.02). No associations were observed with CA72.4. Adjusting for correlates of the markers in prediction models did not improve the discrimination. CONCLUSIONS: This study provides insights into sources of variation in ovarian cancer early detection markers in healthy women and informs about the utility of individualizing marker cutpoints based on epidemiologic factors. More... »

PAGES

20

Journal

TITLE

Journal of Ovarian Research

ISSUE

1

VOLUME

10

Author Affiliations

  • Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg, 69120 Germany
  • Ob/Gyn Epidemiology Center, Brigham and Women’s Hospital, Boston, MA USA
  • Laboratory of Genital Tract Biology, Brigham and Women’s Hospital, Boston, MA USA
  • Unit of Diet, Genes and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark
  • Department of Public Health, Section for Epidemiology, Aarhus University, Aarhus, Denmark
  • Gustave Roussy, Villejuif, F-94805 France
  • Human Genetics Foundation (HuGeF), Torino, Italy
  • Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
  • WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Dept. of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
  • Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
  • Cancer Risk Factors and Life-Style Epidemiology Unit, Cancer Research and Prevention Institute – ISPO, Florence, Italy
  • Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
  • Cancer Registry and Histopathology Unit, “Civic - M.P-Arezzo” Hospital, ASP, Ragusa, Italy
  • Department of Medical Sciences, University of Torino and Human Genetics Foundation – HuGeF, Torino, Italy
  • Dipartimeno di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy
  • Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
  • MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK
  • Genetic Epidemiology Group, Folkhälsan Research Center, Helsinki, Finland
  • Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway
  • Public Health Directorate, Asturias, Spain
  • Cancer Epidemiology Research Program, Bellvitge Biomedical Research Institute (IDIBELL), Catalan Institute of Oncology (ICO), Barcelona, Spain
  • CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
  • IMIB-Arrixaca, Murcia University, CIBERESP, Murcia, Spain
  • IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
  • Public Health Division and BioDonostia Research Institute and CIBERESP, Basque Regional Health Department, San Sebastian, Spain
  • Department of Clinical Sciences, Lund University, Lund, Sweden
  • Division of Surgery, Skåne University Hospital, Lund, Sweden
  • Department of Clinical Sciences, Obstetrics and Gynecology, Umeå University, Umeå, Sweden
  • Cancer Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
  • Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
  • International Agency for Research on Cancer, Lyon, France
  • Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
  • Obstetrics, Gynecology and Reproductive Biology, Harvard Medical School, Boston, MA USA
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s13048-017-0315-6

    DOI

    http://dx.doi.org/10.1186/s13048-017-0315-6

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1084251932

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/28320479


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        "description": "BACKGROUND: Ovarian cancer early detection markers CA125, CA15.3, HE4, and CA72.4 vary between healthy women, limiting their utility for screening.\nMETHODS: We evaluated cross-sectional relationships between lifestyle and reproductive factors and these markers among controls (n\u2009=\u20091910) from a nested case-control study in the European Prospective Investigation into Cancer and Nutrition (EPIC). Improvements in discrimination of prediction models adjusting for correlates of the markers were evaluated among postmenopausal women in the nested case-control study (n\u2009=\u2009590 cases). Generalized linear models were used to calculate geometric means of CA125, CA15.3, and HE4. CA72.4 above vs. below limit of detection was evaluated using logistic regression. Early detection prediction was modeled using conditional logistic regression.\nRESULTS: CA125 concentrations were lower, and CA15.3 higher, in post- vs. premenopausal women (p\u2009\u2264\u20090.02). Among postmenopausal women, CA125 was higher among women with higher parity and older age at menopause (ptrend\u2009\u2264\u20090.02), but lower among women reporting oophorectomy, hysterectomy, ever use of estrogen-only hormone therapy, or current smoking (p\u2009<\u20090.01). CA15.3 concentrations were higher among heavier women and in former smokers (p\u2009\u2264\u20090.03). HE4 was higher with older age at blood collection and in current smokers, and inversely associated with OC use duration, parity, and older age at menopause (\u2264\u20090.02). No associations were observed with CA72.4. Adjusting for correlates of the markers in prediction models did not improve the discrimination.\nCONCLUSIONS: This study provides insights into sources of variation in ovarian cancer early detection markers in healthy women and informs about the utility of individualizing marker cutpoints based on epidemiologic factors.", 
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    680 grid-institutes:grid.7692.a schema:alternateName Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
    681 schema:name Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
    682 rdf:type schema:Organization
     




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