Trends in uterine cancer incidence and mortality: insights from a natural history model.

Abstract

Background: Uterine cancer incidence and mortality are increasing, with concomitant disparities in outcomes between racial groups. Natural history modeling can evaluate risk factors, predict future trends, and simulate approaches to reducing mortality and disparities.

Methods: We designed a natural history model of uterine cancer using a multistage clonal expansion design. The model is informed by National Health and Nutrition Examination Surveys (NHANES), National Health Examination Surveys (NHES), age, period, birth cohort, and birth certificate data on reproductive histories (RH) and body mass index (BMI), and is fit and calibrated to Surveillance, Epidemiology, and End Results (SEER) data by race/ethnicity and histologic subgroup. We projected future incidence and estimated the degree of contribution of BMI, RH, and competing hysterectomy to excess uterine cancer incidence.

Results: The model accurately replicated SEER incidence for endometrioid (EM), non-endometrioid (non-EM), and sarcoma subgroups for non-Hispanic Black (NHB) and non-Hispanic White (NHW) patients. For EM, non-EM, and Sarcomas, BMI-attributable risks are greater for NHW than NHB; RH-attributable risks are greater for NHB. Between 2018 and 2050, EM incidence is projected to rise by 64.9% in NHB and17.5% in NHW; non-EM projected rise is 41.4% in NHB and 22.5% in NHW; sarcoma incidence projected increase is 36% in NHB and 29.2% in NHW.

Conclusions: Uterine cancer risk is substantially explained by RH and BMI, with differences observed between NHB and NHW and future projections indicating perpetuation of disparities. Lower rates of hysterectomy and rising obesity rates will likely contribute to continued increases in uterine cancer incidence.