Introduction: Cancer continues to be a major cause of mortality worldwide and is the leading cause of death for women age 40-79. Gynecologic cancers (GYNC) account for 6.3% of all cancers, making it the 4th leading cause of cancer death among US women. Research has shown that cancers are linked to various demographic factors. Cancer incidence may differ among people of different race/ethnicity due to socioeconomic status; specifically, these variables can impact exposure to risk factors, access to health education, and early detection and treatment. Race/ethnicity is a known risk factor for GYNC. Due to the disparity in the US healthcare system, analysis of the association of various demographic variables with cancer diagnosis in women is imperative to better understand health outcomes for GYNC in this country. Methods: We used the female portion of the 2012 Florida State Inpatient Database of the Healthcare Cost and Utilization Project as our sample. The outcome variable was presence or absence of a cancer diagnosis identified by ICD-9 codes for the following cancers: ovary (OC), uterine (UC), and cervical (CC). Logistic regression analyses examined the patient-level factors of race/ethnicity, age, insurance type, income level, and other comorbidities as potential independent predictors of cancer diagnosis. Results: Logistic regression analysis demonstrated that the odds of CC is increased in women who are black (OR=1.4, 95% CI 1.2-1.5), middle age (OR=5.9, 95% CI 5.1-6.9), and have Medicaid (OR=2.2, 95% CI 3.5-4.9). The similar pattern observed with the OC and UC analysis suggests the presence of cancer disparity among women of lower socioeconomic status. Conclusions: In this study we found that cervical, ovarian, and uterine cancers were significantly associated with variables such as race and lack of reliable health insurance which can indicate disparity. One factor which could potentially contribute to any health disparity in this sample is the lack of ACA Medicaid expansion in Florida. Findings from this study highlight the importance of considering access to healthcare for women from various backgrounds to improve management of cancer and women's health at large.

Citation Format: Zahra Bahrani-Mostafavi, Patricia Koplas. Predictive analysis of demographic factors to examine disparity in gynecologic cancer [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-008.