Abstract 3498: Ovarian cancer risk factors multiply to create high risk in pre-menopausal women
Authors: Minh Tung Phung, Bhramar Mukherjee, Alice W. Lee, Penelope M. Webb, Harvey A. Risch, Jennifer Anne Doherty, Holly R. Harris, Marc T. Goodman, Roberta B. Ness, Francesmary Modugno, Allan Jensen, Susanne K. Kjaer, Kathryn L. Terry, Daniel W. Cramer, Argyrios Ziogas, Hoda Anton-Culver, Malcolm C. Pike, Anna H. Wu, Celeste Leigh Pearce
Journal: Cancer Research (2020)

Abstract Background: Ovarian cancer is the eighth-most common cancer among women. Although a number of established risk factors exist for this disease, analyses of these exposures have largely not taken into account potential interactions. We present an interaction analysis of eight ovarian cancer risk factors, followed by the creation of modifiable and non-modifiable risk scores for the disease. Methods: Data used in this analysis come from nine studies in the Ovarian Cancer Association Consortium (OCAC): one from Australia, one from Europe and seven from the US. Analyses were restricted to pre-menopausal women without first-degree family histories of ovarian cancer, leading to a final study population of 1504 cases and 3515 controls. Five potentially modifiable predictors (oral contraceptive (OC) use duration, body mass index, tubal ligation, hysterectomy and breastfeeding) and three non-modifiable predictors (parity, incomplete pregnancies and history of endometriosis) were considered. A complete analysis of interactions between the eight variables as well as with age, race/ethnicity, education level and study site was conducted. No statistically significant pairwise interactions were found with likelihood ratio statistics, thus suggesting no departure from multiplicativity in the odds ratios. The modifiable and non-modifiable risk scores were calculated as the product of the odds ratios for each group of exposures. Logistic regression was used to model the association between ovarian cancer and the risk scores. Age, race/ethnicity, education level and study site were included in the model. Results: The associations between the second, third and fourth quartiles of the modifiable risk score compared to the lowest quartile were 1.67 (95% CI 1.35-2.09), 2.18 (95% CI 1.76-2.71) and 3.72 (95% CI 3.04-4.57), respectively. The odds ratios for the non-modifiable risk score were 1.17 (95% CI 0.95-1.44), 1.24 (95% CI 0.99-1.54) and 2.06 (95% CI 1.68-2.53), respectively for the second, third and fourth quartiles compared to the first. Women in the highest quartiles of both the modifiable and non-modifiable risk scores, representing 14.6% of the women, had a 7.67-fold increased risk of ovarian cancer (95% CI 4.68-11.39) compared to women in the lowest quartiles for both risk scores (3.6% of the women). Conclusions: Pre-menopausal women in the highest risk quartiles have a substantially elevated risk of ovarian cancer based on these eight exposures. Modifiable factors contribute more than non-modifiable factors to ovarian cancer risk among pre-menopausal women with no family history in our study. Women in the highest risk group (fourth quartile of both risk scores) could reduce their risk by intervening on the modifiable exposures; for example, 63% of women in this group had not used oral contraceptives and 93% had not had tubal ligation. However, careful consideration of the risks and benefits of such prevention measures is needed. Citation Format: Minh Tung Phung, Bhramar Mukherjee, Alice W. Lee, Penelope M. Webb, Harvey A. Risch, Jennifer Anne Doherty, Holly R. Harris, Marc T. Goodman, Roberta B. Ness, Francesmary Modugno, Allan Jensen, Susanne K. Kjaer, Kathryn L. Terry, Daniel W. Cramer, Argyrios Ziogas, Hoda Anton-Culver, Malcolm C. Pike, Anna H. Wu, Celeste Leigh Pearce. Ovarian cancer risk factors multiply to create high risk in pre-menopausal women [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3498.