Cancer and autoimmunity are two major chronic diseases among women. Based on previous studies that cancer and autoimmune diseases (AD) are both the accumulative effect of genetics and environmental exposures, it was imperative to recognize the profile of comorbidities and how they relate to patients’ characteristics. This dissertation research was conducted to investigate the association between patient-level predictors and gynecologic cancer (GYNC) among U.S. women with AD by examining 2 aims: 1) to evaluate the association between patient-level predictors and GYNC among AD patients and 2) to determine the various subpopulations of AD patients with increased likelihood of GYNC based on patients’ characteristics and comorbid conditions, using Classification Tree Analysis. This study was a secondary data analysis of 2007-2013 Florida State Inpatient Data samples of the Healthcare Cost and Utilization Project (HCUP). The study population included women with any AD diagnosis. The key predictors –including age, race/ethnicity, insurance type, length of stay in hospital, and median income level, in addition to 31 comorbidities used by Elixhauser et al.–were chosen based on previous findings in literature on their association with cancer globally. In this study, it was found that older age had decreased odds with GYNC among women with AD (45-65 years old: OR = 0.90, 95% CI: 0.82-0.99; and > 65 years old: OR = 0.79, 95% CI: 0.70-0.88). Medicaid holders and self-pay patients, and patients with GYN related procedures such as hysterectomy had increased odds of GYNC among patients with AD (Hysterectomy: OR = 41.38, 95% CI: 37.40-45.78). Comorbidities such as AIDS/HIV, coagulopathy, weight loss, fluid and electrolyte disorders, renal failure, and obesity were found to have strong associations with GYNC among women with AD. Using predictive analytics some comorbidities such as coagulopathy, rheumatoid arthritis, and chronic pulmonary disease along with hysterectomy showed to be strong predictors of GYNC among specific populations of ADs. The unique combinations of characteristics that described subgroups of patients at risk for GYNC can be used as a potential risk assessment for GYNC as well as for early detection and/or prevention tools. The strong correlation between potential predictors and GYNC may lead the women with AD to be recommended for yearly cancer screening for early detection, and better management of possible GYN cancer toward women health.