An epidemiological model for prediction of endometrial cancer risk in Europe

Abstract

Endometrial cancer is the fourth most frequent cancer in women in Europe, and as its incidence is increasing, prevention strategies gain further pertinence. Risk prediction models can be a useful tool for identifying women likely to benefit from targeted prevention measures. On the basis of data from 201,811 women (mostly aged 30-65 years) including 855 incident endometrial cancer cases from eight countries in the European Prospective Investigation into Cancer and Nutrition cohort, a model to predict endometrial cancer (EC) was developed. A step-wise model selection process was used to select confirmed predictive epidemiologic risk factors. Piece-wise constant hazard rates in 5-year age-intervals were estimated in a cause-specific competing risks model, five-fold-cross-validation was applied for internal validation.Risk factors included in the risk prediction model were body-mass index (BMI), menopausal status, age at menarche and at menopause, oral contraceptive use, overall and by different BMI categories and overall duration of use, parity, age at first full-term pregnancy, duration of menopausal hormone therapy and smoking status (specific for pre, peri-and post-menopausal women). These variables improved the discriminating capacity to predict risk over 5 years from 71% for a model based on age alone to 77% (overall C statistic), and the model was wellcalibrated (ratio of expected to observed cases = 0.99).Our model could be used for the identification of women at increased risk of EC in Western Europe. To achieve an EC-risk model with general validity, a large-scale cohort-consortium approach would be needed to assess and adjust for population variation. Husing_EndometrCaRiskmodel_EurJEpidemiol_2015_authorversion4

Prediction models for endometrial cancer for the general population or symptomatic women: A systematic review

“…The two studies that developed risk models used data from population based cohorts; one study used the European EPIC cohort (Husing et al, 2016) and one study used a cohort from the United States (Pfeiffer et al, 2013) (US) ( Table 1). The data was collected using a Fig.…”

“…(Pfeiffer et al, 2013) and 201,811 (855 with cancer) (Husing et al, 2016). Inclusion criteria were similar for the two studies.…”

“…Cases were identified through record linkage with regional cancer registries, linkage to health insurance records, active follow-up of study subjects and systematic requests of patient records from pathology registries in the European study (Husing et al, 2016). Identification of cases in the other study was done via linkage with state cancer registries, annual study updates and reviews of medical records (Pfeiffer et al, 2013).…”

“…Both studies included predictors that were previously associated with endometrial cancer. The European study handled most of the continuous predictors as a linear term and centered them at the median (Husing et al, 2016), while the other study categorized all continuous predictors (Pfeiffer et al, 2013). Both studies investigated interaction effects between predictors and had an EPV above ten.…”

“…Several risk and diagnostics models for endometrial cancer have been developed (Pfeiffer et al, 2013;Wong et al, 2016;Husing et al, 2016;Burbos et al, 2010;Giannella et al, 2014). The models can be used for risk prediction for prevention purposes.…”