Journal of Ovarian Research (Nov 2019)
Development and validation of circulating CA125 prediction models in postmenopausal women
- Naoko Sasamoto,
- Ana Babic,
- Bernard A. Rosner,
- Renée T. Fortner,
- Allison F. Vitonis,
- Hidemi Yamamoto,
- Raina N. Fichorova,
- Linda J. Titus,
- Anne Tjønneland,
- Louise Hansen,
- Marina Kvaskoff,
- Agnès Fournier,
- Francesca Romana Mancini,
- Heiner Boeing,
- Antonia Trichopoulou,
- Eleni Peppa,
- Anna Karakatsani,
- Domenico Palli,
- Sara Grioni,
- Amalia Mattiello,
- Rosario Tumino,
- Valentina Fiano,
- N. Charlotte Onland-Moret,
- Elisabete Weiderpass,
- Inger T. Gram,
- J. Ramón Quirós,
- Leila Lujan-Barroso,
- Maria-Jose Sánchez,
- Sandra Colorado-Yohar,
- Aurelio Barricarte,
- Pilar Amiano,
- Annika Idahl,
- Eva Lundin,
- Hanna Sartor,
- Kay-Tee Khaw,
- Timothy J. Key,
- David Muller,
- Elio Riboli,
- Marc Gunter,
- Laure Dossus,
- Britton Trabert,
- Nicolas Wentzensen,
- Rudolf Kaaks,
- Daniel W. Cramer,
- Shelley S. Tworoger,
- Kathryn L. Terry
Affiliations
- Naoko Sasamoto
- Obstetrics and Gynecology Epidemiology Center, Brigham and Women’s Hospital and Harvard Medical School
- Ana Babic
- Department of Medical Oncology, Dana-Farber Cancer Institute
- Bernard A. Rosner
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School
- Renée T. Fortner
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ)
- Allison F. Vitonis
- Obstetrics and Gynecology Epidemiology Center, Brigham and Women’s Hospital and Harvard Medical School
- Hidemi Yamamoto
- Laboratory of Genital Tract Biology, Department of Obstetrics, Gynecology and Reproductive Biology, Brigham and Women’s Hospital
- Raina N. Fichorova
- Laboratory of Genital Tract Biology, Department of Obstetrics, Gynecology and Reproductive Biology, Brigham and Women’s Hospital
- Linda J. Titus
- Departments of Epidemiology and Pediatrics, Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center
- Anne Tjønneland
- Diet, Genes and Environment, Danish Cancer Society Research Center
- Louise Hansen
- Diet, Genes and Environment, Danish Cancer Society Research Center
- Marina Kvaskoff
- CESP, Fac. de médecine - Univ. Paris-Sud, Fac. de médecine - UVSQ, INSERM, Université Paris-Saclay
- Agnès Fournier
- CESP, Fac. de médecine - Univ. Paris-Sud, Fac. de médecine - UVSQ, INSERM, Université Paris-Saclay
- Francesca Romana Mancini
- CESP, Fac. de médecine - Univ. Paris-Sud, Fac. de médecine - UVSQ, INSERM, Université Paris-Saclay
- Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke
- Antonia Trichopoulou
- Hellenic Health Foundation
- Eleni Peppa
- Hellenic Health Foundation
- Anna Karakatsani
- Hellenic Health Foundation
- Domenico Palli
- Cancer Risk Factors and Life-Style Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network - ISPRO
- Sara Grioni
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano
- Amalia Mattiello
- Dipartimento Di Medicina Clinica E Chirurgia, Federico II University
- Rosario Tumino
- Cancer Registry and Histopathology Department, “Civic - M.P. Arezzo”Hospital, ASP
- Valentina Fiano
- Unit of Cancer Epidemiology– CeRMS, Department of Medical Sciences, University of Turin
- N. Charlotte Onland-Moret
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University
- Elisabete Weiderpass
- International Agency for Research on Cancer
- Inger T. Gram
- Department of Community Medicine, University of Tromsø, The Arctic University of Norway
- J. Ramón Quirós
- Public Health Directorate
- Leila Lujan-Barroso
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO-IDIBELL)
- Maria-Jose Sánchez
- Andalusian School of Public Health (EASP)
- Sandra Colorado-Yohar
- CIBER of Epidemiology and Public Health (CIBERESP)
- Aurelio Barricarte
- CIBER of Epidemiology and Public Health (CIBERESP)
- Pilar Amiano
- CIBER of Epidemiology and Public Health (CIBERESP)
- Annika Idahl
- Department of Clinical Sciences, Obstetrics and Gynecology, Umeå University
- Eva Lundin
- Department of Medical Biosciences, Pathology, Umeå University
- Hanna Sartor
- Department of Medical Imaging and Physiology, Skåne University Hospital
- Kay-Tee Khaw
- Cancer Epidemiology Unit, University of Cambridge
- Timothy J. Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford
- David Muller
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London
- Elio Riboli
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London
- Marc Gunter
- International Agency for Research on Cancer
- Laure Dossus
- International Agency for Research on Cancer
- Britton Trabert
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health
- Nicolas Wentzensen
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health
- Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ)
- Daniel W. Cramer
- Obstetrics and Gynecology Epidemiology Center, Brigham and Women’s Hospital and Harvard Medical School
- Shelley S. Tworoger
- Department of Cancer Epidemiology, Moffitt Cancer Center
- Kathryn L. Terry
- Obstetrics and Gynecology Epidemiology Center, Brigham and Women’s Hospital and Harvard Medical School
- DOI
- https://doi.org/10.1186/s13048-019-0591-4
- Journal volume & issue
-
Vol. 12,
no. 1
pp. 1 – 12
Abstract
Abstract Background Cancer Antigen 125 (CA125) is currently the best available ovarian cancer screening biomarker. However, CA125 has been limited by low sensitivity and specificity in part due to normal variation between individuals. Personal characteristics that influence CA125 could be used to improve its performance as screening biomarker. Methods We developed and validated linear and dichotomous (≥35 U/mL) circulating CA125 prediction models in postmenopausal women without ovarian cancer who participated in one of five large population-based studies: Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO, n = 26,981), European Prospective Investigation into Cancer and Nutrition (EPIC, n = 861), the Nurses’ Health Studies (NHS/NHSII, n = 81), and the New England Case Control Study (NEC, n = 923). The prediction models were developed using stepwise regression in PLCO and validated in EPIC, NHS/NHSII and NEC. Result The linear CA125 prediction model, which included age, race, body mass index (BMI), smoking status and duration, parity, hysterectomy, age at menopause, and duration of hormone therapy (HT), explained 5% of the total variance of CA125. The correlation between measured and predicted CA125 was comparable in PLCO testing dataset (r = 0.18) and external validation datasets (r = 0.14). The dichotomous CA125 prediction model included age, race, BMI, smoking status and duration, hysterectomy, time since menopause, and duration of HT with AUC of 0.64 in PLCO and 0.80 in validation dataset. Conclusions The linear prediction model explained a small portion of the total variability of CA125, suggesting the need to identify novel predictors of CA125. The dichotomous prediction model showed moderate discriminatory performance which validated well in independent dataset. Our dichotomous model could be valuable in identifying healthy women who may have elevated CA125 levels, which may contribute to reducing false positive tests using CA125 as screening biomarker.
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