Abstract 2205: Prediction model of CA125 among premenopausal women

Abstract Background: Cancer antigen 125 (CA125) is a membrane-bound glycosylated mucin that has been reported to be the most promising biomarker for ovarian cancer screening, although results from two large randomized trials comparing screening using CA125 and transvaginal ultrasound to usual care have shown no clinically significant difference in ovarian cancer mortality. A major limitation of CA125 as an ovarian cancer screening biomarker has been low specificity and variation between individuals by personal characteristics. Identifying personal characteristics that influence CA125 levels could be used to create personalized thresholds for CA125 for each individual, thereby improving its performance as an ovarian cancer screening biomarker. However, reports on factors that influence CA125 among premenopausal women are limited. Methods: We evaluated the association between reproductive and lifestyle factors and CA125 among 828 premenopausal population-based controls enrolled in the New England Case-Control study between 1992 and 2008. CA125 was measured using the CA125II assay at the CERLab at Boston Children's Hospital. We developed a prediction model of log-transformed CA125 using stepwise linear regression with <0.15 as significance level for entry and stay considering factors associated with CA125 in postmenopausal women and ovarian cancer risk factors, such as age, body mass index (BMI), race, smoking status, age at menarche, oral contraceptive use and its duration, parity, endometriosis, tubal ligation, unilateral oophorectomy, hysterectomy, family history of ovarian cancer, previous history of cancer, genital powder use, and caffeine intake as candidate predictors. Results: In our univariate analyses, older age and endometriosis were associated with significantly higher CA125 while tubal ligation, hysterectomy, and time since last menstrual period were associated with significantly lower CA125 (p<0.05). Age, endometriosis, tubal ligation, hysterectomy, smoking status, caffeine intake, and interval days since last menstrual period were selected in our final prediction model, which explained 6% of the total variability of log-transformed CA125 levels. Conclusion: Efforts to validate this CA125 prediction model in an independent cohort of premenopausal women and evaluate whether using the personalized CA125 cutoff based on this prediction model discriminates cases and controls better than the single 35 cutoff are ongoing. Citation Format: Naoko Sasamoto, Ana Babic, Bernard A. Rosner, Allison F. Vitonis, Daniel W. Cramer, Shelley S. Tworoger, Kathryn L. Terry. Prediction model of CA125 among premenopausal women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2205.