A novel surname-based methodology to improve the disaggregation of Asian American ethnic subgroups in patients with ovarian cancer

Objective: Over the last 30 years, only two-thirds of gynecologic oncology publications reported on race/ethnicity. Demographic reporting of disaggregated racial/ethnic groups can elucidate disparities and elicit unique insights into care. We aimed to improve the accuracy of race and ethnicity reporting in patients with ovarian cancer by integrating self-reported data with a novel surname-based methodology. Methods: Patients with ovarian cancer between 2011 and 2023 were identified from our tumor registry. Self-reported race/ethnicity data were extracted from electronic health records. A validated surname list derived from Social Security Administration files was used to disaggregate Asian American patients and those from Other/Unknown races into the following ethnic subgroups: Chinese, Filipino, Indian, Japanese, Korean, and Vietnamese. The effectiveness of ethnic subgroup disaggregation was assessed among Asian American patients. Results: Among 813 patients identified, the self-reported racial/ethnic distribution was: 10% (n = 81) Asian, 12% (n = 96) Hispanic, 1% (n = 7) Multiracial,