Cancer risk factors and cancer in transgender versus cisgender people: Real-world data from a tertiary health care institution.

Abstract

6538Background: Data are sparse regarding the prevalence of cancer and cancer risk factors among transgender people. Transgender people experience structural stigma and extreme rates of violence that may contribute to cancer through multiple mechanisms. The purpose of this study was to assess cancer risk factors and cancer in transgender people in a single institutional electronic health record (EHR) and compare the rates to those among cisgender, or non-transgender, people. Methods: Using a combination of structured gender identity data, diagnosis codes, and keyword searches, we identified a cohort of transgender people seen at our institution, a large tertiary care center. We next identified a cohort of cisgender people matched by age, year of first encounter in our EHR, and years of follow-up. Among these cohorts, we searched for cancer, premalignant lesions, human immunodeficiency virus (HIV), human papilloma virus (HPV), and hepatitis and assessed body mass index (BMI) and smoking status through structured EHR fields. Lastly, we compared the prevalence of cancer, premalignant lesions, and cancer risk factors between the two cohorts using chi-square tests. If expected cell sizes were <5, exact tests were used. Results: We identified cohorts of 923 transgender and 1846 cisgender people matched by age, follow-up time, and year of the first encounter. Rates of smoking (42 versus 34%, p < 0.0001), BMI ≥ 40 (21% versus 13%, p < 0.0001), and HIV (3 versus 0%, p < 0.0001) were significantly higher among transgender compared with cisgender people. Rates of premalignant lesions and cancer did not significantly differ between cohorts. Conclusions: In this large sample of patients seen at our institution, rates of several cancer risk factors were higher for transgender than cisgender people. No differences were demonstrated in prevalence of premalignant lesions and cancer between groups. These data require confirmation in larger national datasets. Interventions that decrease structural oppression and provide support for tobacco cessation, decreased transmission of HIV, and access to high-quality food and exercise are also called for. [Table: see text]