Abstract
Endometrial cancer (EC) incidence rates vary ~10‐fold worldwide, in part due to variation in EC risk factor profiles. Using an EC risk model previously developed in the European EPIC cohort, we evaluated the prevention potential of modified EC risk factor patterns and whether differences in EC incidence between a European population and low‐risk countries can be explained by differences in these patterns. Predicted EC incidence rates were estimated over 10 years of follow‐up for the cohort before and after modifying risk factor profiles. Risk factors considered were: body mass index (BMI, kg/m2), use of postmenopausal hormone therapy (HT) and oral contraceptives (OC) (potentially modifiable); and, parity, ages at first birth, menarche and menopause (environmentally conditioned, but not readily modifiable). Modeled alterations in BMI (to all ≤23 kg/m2) and HT use (to all non‐HT users) profiles resulted in a 30% reduction in predicted EC incidence rates; individually, longer duration of OC use (to all ≥10 years) resulted in a 42.5% reduction. Modeled changes in not readily modifiable exposures (i.e., those not contributing to prevention potential) resulted in ≤24.6% reduction in predicted EC incidence. Women in the lowest decile of a risk score based on the evaluated exposures had risk similar to a low risk countries; however, this was driven by relatively long use of OCs (median = 23 years). Our findings support avoidance of overweight BMI and of HT use as prevention strategies for EC in a European population; OC use must be considered in the context of benefits and risks.
Highlights
Endometrial cancer (EC) incidence rates show wide variation worldwide, with estimated age-standardized rates (ASR; standardized to World Health Organization (WHO) World Standard Population) of 15 per 100,000 women and higher in 2018 in Europe and North America but much lower rates reported by relatively high-quality cancer registries in parts of Africa and Asia, for example, in Algeria (ASR = 2.2/100,000) or India (ASR = 1.9/100,000).[1]
For women in the lowest decile of the relative risk score based on all risk factors except smoking, or based on Body mass index (BMI), oral contraceptives (OC) use and hormone therapy (HT) use, predicted EC incidence rates were only slightly higher than those observed in India (Fig. 1)
Across the 5-year age categories, the incidence rates from the prediction model closely matched those observed in European Prospective Investigation into Cancer and Nutrition (EPIC) and predicted for Europe (EU28; Supporting Information Fig. S2) and the India (Chennai) data from Globocan 2018 are in line with the India country-wide summary estimates and the low human development index (HDI) estimates from Globocan 2012
Summary
Established risk factors for EC include older age, overweight and obesity, nulliparity/low parity, a relatively young age at last full-term pregnancy, and having experienced a relatively early menarche and/or late menopause, reflecting a larger lifetime cumulative number of ovulatory menstrual cycles.[2] In addition, the use of postmenopausal hormone therapy (HT) can either increase or decrease risk, depending on both on its composition (estrogenonly, or estrogen-plus-progestin combinations)[3] and a woman’s degree of adiposity (i.e., high body mass index [BMI]).[4] long-term use of oral contraceptives (OC) is associated with marked reductions in EC risk, which persist for years after cessation of use,[5] and smoking has been associated with lower risk.[2] Based on these established risk (and protective) factors, we previously derived a statistical model to predict a woman’s absolute EC risk, in view of identifying high-risk women who may benefit from targeted prevention measures (risk stratification), using data from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.[6] Here, we extend our analyses, applying this previously derived risk model to the EPIC data to (i) estimate the theoretical potential for the prevention of EC in Western Europe, or in similar higher-risk populations, through risk factor avoidance or alterations in exposure patterns, and (ii) evaluate the extent to which the higher EC risk in the European population, as compared to a low-risk country such as India, can be explained by the prevalence of exposure to primary risk factors
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