Abstract

BackgroundCancer antigen 125 (CA125) is clinically used to monitor response to therapy in ovarian cancer and has been proposed for use in detecting ovarian cancer. This population-based study examines how demographic characteristics, gynecologic/reproductive history, chronic non-malignant medical conditions, history of non-ovarian cancer, lifestyle practices, and biomarkers of inflammation correlate with serum CA125 in both premenopausal and postmenopausal women without ovarian cancer across the United States.MethodsParticipants were identified from the National Health and Nutrition Examination Survey 2001–2002. Linear and logistic regression models were applied.ResultsHigher CA125 levels were found to correlate with younger age, Non-Hispanic White race/ethnicity, and lower body mass index. In premenopausal women (N = 1157), current smoking was associated with lower CA125 (− 24.95%, p = 0.008), and history of non-ovarian cancer was associated with higher CA125 (40.64%, p = 0.045) by multivariable linear regression; both current smoking (odds ratio (OR) = 0.42, p = 0.043) and oral contraceptive pill (OCP) use of 5–10 years (OR = 0.31, p = 0.032) were less likely to be associated with having CA125 level ≥ 35 U/ml by multivariable logistic regression. In postmenopausal women (N = 1116), coronary artery disease (CAD) history was associated with higher CA125 (28.27%, p = 0.047) by multivariable linear regression; history of CAD (OR = 5.00, p = 0.011), history of breastfeeding (OR = 2.46, p = 0.026), and increased CRP level (OR = 1.41, p = 0.042) were more likely to be associated with having CA125 level ≥ 35 U/ml by multivariable logistic regression.ConclusionsResults suggest CA125 is lower in premenopausal women who are current smokers and OCP users of moderately longer duration but higher in those with non-ovarian cancer. CA125 is higher in those postmenopausal women with CAD, history of breastfeeding and elevated CRP level. These associations can inform clinical interpretation of individual patients’ CA125 levels.

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