The use of Immunotherapy (IO), and specifically immune checkpoint inhibitors, is increasingly common for the treatment of gynecologic cancer. Emerging evidence suggests that circadian rhythms may influence immune function, tumor behavior, and ultimately lead to variable response to IO based on the time of day in which these treatments were administered (Karaboué et al, 2024). In retrospective and prospective studies, administration of IO earlier in the day has shown significant improvement in progression free survival (PFS), as well as overall survival (OS) in renal cell carcinoma, melanoma and lung cancer (Huang et al., 2026). However, there are no studies to date which have studied cancer outcomes based on the time of day of IO agents in gynecologic cancers. In this retrospective study, we aim to determine if the time of day when IO is administered also impacts outcomes in gynecologic cancers. If earlier administration leads to better outcomes as we hypothesize, this could lead to changes in practice like scheduling IO therapies to earlier in the day.

This is a retrospective study of patients with gynecologic malignancy treated with immune checkpoint inhibitors at the University of Oklahoma Stephenson Cancer Center between January 2019 and March 2026. There are no additional sites where the study will take place.

Patients will be identified by a chart review. Patient information including but not limited to demographics, medical history, oncologic history, and other pertinent health information will be collected via chart review from the electronic medical record. All data will be stored in a password-protected RedCap database through the University of Oklahoma.

Patients must have a diagnosis of gynecologic malignancy defined as ovarian, endometrial, cervical, vaginal or vulvar cancer, and have been treated with at least one cycle of an immune checkpoint inhibitor at the Stephenson Cancer Center. Treatment must have started between January 2019 and March 2026. They must be at least 18 years of age.

We will use appropriate descriptive statistics to summarize the data.We may compute these descriptive statistics after stratification by various subject characteristics of interest such as age group, cancer stage, cancer type or co-morbidities. Other statistical tests will be applied as needed to describe the variables of interest. We anticipate that 500 patients will meet inclusion criteria.

Data collection ongoing