Identifying At-Risk Populations for Treatment Delays in Endometrioid Ovarian Carcinoma: A Nationally Representative...

Background: Endometrioid ovarian carcinoma is a subtype of epithelial ovarian carcinoma and is the second most common type of malignant ovarian neoplasm. Studies investigating delayed treatment of ovarian cancer have identified significant impacts on overall survival rates. This study utilizes the Surveillance, Epidemiology, and End Results (SEER) database to identify cases of endometrioid ovarian carcinomas and factors associated with delays in time to treatment (TTT) greater than one month. Methods: The SEER database was queried to identify females with biopsy-confirmed cases of ovarian endometrioid carcinoma from 2010 to 2015. Chi-square tests, two-sided Fisher's exact tests, and multivariable binary logistic regressions were completed using SPSS version 29.0.2. Statistical significance was confirmed when p < 0.05. Results: A total of 11,235 relevant patients were identified within the SEER database. A majority were Non-Hispanic White (69.2%), aged 50-59 (30.1%), had an annual income of $75,000+ (58.9%), resided in urban communities (90.0%), and were diagnosed with AJCC stage 1 disease (62.0%). When investigating treatment, 94.9% of patients received treatment within 1 month of diagnosis, while 5.1% experienced a delay of over 1 month before starting treatment. Multivariable binary logistic regression analysis demonstrated that American Indian and Alaksa Native (AIAN) patients independently experienced a +376% increased likelihood of treatment delays exceeding 1 month (aOR 4.76; 95% CI 1.32-17.08; p = 0.017). Patients diagnosed at AJCC stage III (aOR 1.88; 95% CI: 1.22-2.91; p = 0.004) or stage IV (aOR: 4.50; 95% CI: 2.75-7.38; p < 0.001) additionally had +88% and +350% higher odds of treatment delays greater than 1 month, respectively. Conclusions: AIAN patients and those presenting with later stage disease for endometrioid ovarian carcinoma face significantly longer TTT, indicating disparities in timely care. Our findings demonstrate an urgent need for targeted interventions to address systemic barriers contributing to delayed treatment in these populations.