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Cancer Epidemiol Biomarkers Prev. 2019 Apr 4. pii: cebp.1120.2018. doi: 10.1158/1055-9965.EPI-18-1120. [Epub ahead of print]

Predicting circulating CA125 levels among healthy premenopausal women.

Author information

1
Obstetrics and Gynecology Epidemiology Center, Brigham and Women's Hospital, Harvard Medical School nsasamoto@bwh.harvard.edu.
2
Department of Medical Oncology, Dana-Farber Cancer Institute.
3
Dept. of Medicine, Brigham and Women's Hospital and Harvard Medical School.
4
Division of Cancer Epidemiology, Deutsches Krebsforschungszentrum (DKFZ).
5
Obstetrics and Gynecology Epidemiology Center,, Brigham and Women's Hospital / Harvard Medical School.
6
Laboratory of Genital Tract Biology, Ob/Gyn, Brigham and Women's Hospital.
7
Unit of Diet, Genes and Environment, Danish Cancer Society Research Center.
8
Diet, Genes and Environment, Danish Cancer Society Research Center.
9
Department of Public Health, Section for Epidemiology, Aarhus University.
10
Health across Generations Team, Inserm U1018, Gustave Roussy.
11
Health across generations team, INSERM, CESP Centre for Research in Epidemiology and Population Health, U1018, Univ Paris Sud.
12
CESP, INSERM.
13
Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke.
14
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.
15
Nutrition, Hellenic Health Foundation.
16
2nd Pulmonary Medicine Department, School of Medicine, National and Kapodistrian University of Athens, Hellenic Health Foundation.
17
Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network, ISPRO.
18
Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale Tumori.
19
Dipartimento di Medicina Clinica e Chirurgia, Federico II University.
20
Cancer Registry and Histopathology Unit, M.P.Arezzo Hospital.
21
Cancer Epidemiology Unit-CeRMS, Department of Medical Sciences, University of Turin, and CPO Piemonte, Turin, Italy, University of Turin.
22
Julius Center for Health Sciences and Primary Care, Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht.
23
Office of the Director, International Agency For Research On Cancer.
24
Public Health Directorate.
25
Unit of Nutrition and Cancer, Catalan Institute of Oncology (ICO-IDIBELL).
26
Granada Cancer Registry, Andalusian School of Public Health; Biomedical Research Institute of Granada (ibs.Granada), University of Granada; CIBER of Epidemiology and Public Health (CIBERESP).
27
Department of Epidemiology, Murcia Regional Health Council IMIB-Arrixaca. CIBER Epidemiología y Salud Pública (CIBERESP).
28
CIBER de Epidemiología y Salud Pública (CIBERESP).
29
Public Health Direction and CIBERESP-Biodonostia Research Institute, Basque Regional Health Department.
30
Department of Clinical Science, Obstetrics and Gynecology, Umea University.
31
Department of Medical Biosciences, Pathology, Umea University.
32
Department of Translational Medicine, Skåne University Hospital.
33
Cancer Epidemiology Unit, University of Cambridge.
34
Nuffield Department of Population Health, University of Oxford.
35
School of Public Health, Imperial College.
36
Nutrition and Metabolism, International Agency For Research On Cancer.
37
International Agency For Research On Cancer.
38
Obstetrics and Gynecology Epidemiology Center, Brigham and Women's Hospital and Harvard Medical School.
39
Cancer Epidemiology, Moffitt Cancer Center.
40
Department of Obstetrics, Gynecology, and Reproductive Biology, Brigham and Women's Hospital, Harvard Medical School.

Abstract

BACKGROUND:

CA125 is the most promising ovarian cancer screening biomarker to date. Multiple studies reported CA125 levels vary by personal characteristics, which could inform personalized CA125 thresholds. However, this has not been well described in premenopausal women.

METHODS:

We evaluated predictors of CA125 levels among 815 premenopausal women from the New England Case Control Study (NEC). We developed linear and dichotomous (≥ 35 U/ mL) CA125 prediction models and externally validated an abridged model restricting to available predictors among 473 premenopausal women in the European Prospective Investigation into Cancer and Nutrition Study (EPIC).

RESULTS:

The final linear CA125 prediction model included age, race, tubal ligation, endometriosis, menstrual phase at blood draw, and fibroids, which explained 7% of the total variance of CA125. The correlation between observed and predicted CA125 levels based on the abridged model (including age, race, and menstrual phase at blood draw) had similar correlation coefficients in NEC(r=0.22) and in EPIC(r=0.22). The dichotomous CA125 prediction model included age, tubal ligation, endometriosis, prior personal cancer diagnosis, family history of ovarian cancer, number of miscarriages, menstrual phase at blood draw and smoking status with AUC of 0.83. The abridged dichotomous model (including age, number of miscarriages, menstrual phase at blood draw, and smoking status) showed similar AUCs in NEC(0.73) and in EPIC(0.78).

CONCLUSIONS:

We identified a combination of factors associated with CA125 levels in premenopausal women.

IMPACT:

Our model could be valuable in identifying healthy women likely to have elevated CA125 and consequently improve its specificity for ovarian cancer screening.

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