• 1 Department of Biomarker for Early Detection of Cancer, National Cancer Center Research Institute, Tokyo, Japan
  • 2 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
  • 3 Diet, Genes and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark
  • 4 Department of Public Health, Section for Epidemiology, Aarhus University, Aarhus, Denmark
  • 5 Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway
  • 6 Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, United Kingdom
  • 7 Cancer Risk Factors and Life-Style Epidemiology Unit, Cancer Research and Prevention Institute - ISPO, Florence, Italy
  • 8 Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy
  • 9 Cancer Registry and Histopathology Unit, "Civic - M.P. Arezzo" Hospital, Ragusa, Italy
  • 10 Department of Molecular and Genetic Epidemiology, IIGM - Italian Institute for Genomic Medicine, Torino, Italy
  • 11 Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy
  • 12 Department of Epidemiology, German Institute of Human Nutrition, Potsdam-Rehbruecke (DIfE), Nuthetal, Germany
  • 13 Department of Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
  • 14 Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
  • 15 Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens, School of Medicine, WHO Collaborating Center for Nutrition and Health
  • 16 Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts
  • 17 Cancer Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
  • 18 MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
  • 19 Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
  • 20 Public Health Directorate, Asturias, Spain, Acknowledgment of funds: Regional Government of Asturias
  • 21 PanC4 Consortium, Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO-IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
  • 22 Escuela Andaluza de Salud Pública. Instituto de Investigación Biosanitaria ibs.GRANADA, Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain
  • 23 Department of Epidemiology, Murcia Regional Health Council, CIBER Epidemiología y Salud Pública (CIBERESP), Spain, Ronda de Levante, Murcia, Spain
  • 24 CIBER Epidemiology and Public Health CIBERESP, Madrid, Spain
  • 25 Pancreatology Unit, Beaujon Hospital, Clichy, France
  • 26 CESP, INSERM U1018, Univ. Paris-Sud, UVSQ, Université Paris-Saclay, Villejuif, France
  • 27 INSERM - UMR 1149, University Paris 7, Paris, France
  • 28 Section of Genetics, International Agency for Research on Cancer (IARC), World Health Organization, Lyon, France
  • 29 Department of Surgery, Skåne University Hospital, Lund University, Lund, Sweden
  • 30 Department of Surgical and Preoperative Sciences, Umeå University, Umeå, Sweden
  • 31 Department of Radiation Sciences and Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden
  • 32 Genomic Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
Int. J. Cancer, 2019 04 15;144(8):1877-1887.
PMID: 30259989 DOI: 10.1002/ijc.31900


Recently, we identified unique processing patterns of apolipoprotein A2 (ApoA2) in patients with pancreatic cancer. Our study provides a first prospective evaluation of an ApoA2 isoform ("ApoA2-ATQ/AT"), alone and in combination with carbohydrate antigen 19-9 (CA19-9), as an early detection biomarker for pancreatic cancer. We performed ELISA measurements of CA19-9 and ApoA2-ATQ/AT in 156 patients with pancreatic cancer and 217 matched controls within the European EPIC cohort, using plasma samples collected up to 60 months prior to diagnosis. The detection discrimination statistics were calculated for risk scores by strata of lag-time. For CA19-9, in univariate marker analyses, C-statistics to distinguish future pancreatic cancer patients from cancer-free individuals were 0.80 for plasma taken ≤6 months before diagnosis, and 0.71 for >6-18 months; for ApoA2-ATQ/AT, C-statistics were 0.62, and 0.65, respectively. Joint models based on ApoA2-ATQ/AT plus CA19-9 significantly improved discrimination within >6-18 months (C = 0.74 vs. 0.71 for CA19-9 alone, p = 0.022) and ≤ 18 months (C = 0.75 vs. 0.74, p = 0.022). At 98% specificity, and for lag times of ≤6, >6-18 or ≤ 18 months, sensitivities were 57%, 36% and 43% for CA19-9 combined with ApoA2-ATQ/AT, respectively, vs. 50%, 29% and 36% for CA19-9 alone. Compared to CA19-9 alone, the combination of CA19-9 and ApoA2-ATQ/AT may improve detection of pancreatic cancer up to 18 months prior to diagnosis under usual care, and may provide a useful first measure for pancreatic cancer detection prior to imaging.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.