title: Identifying High-Risk Women for Endometrial Cancer Prevention Strategies: Proposal of an Endometrial Cancer Risk Prediction Model.
abstract: Already the fourth most common cancer in women in the developed world, the incidence of endometrial cancer is increasing rapidly, in line with the increasing prevalence of obesity. Relatively few studies have been undertaken of risk-reducing interventions aimed at limiting the impact of the disease on both individuals and the health service. Those that have been performed have demonstrated only modest results due to their application in relatively unselected populations. A validated risk prediction model is therefore urgently required to identify individuals at particularly high risk of endometrial cancer who may benefit from targeted primary prevention strategies and to guide trial eligibility. On the basis of a systematic review of the literature, the evidence for inclusion of measures of obesity, reproduction, insulin resistance, and genetic risk in such a model is discussed, and the strength of association between these risk factors and endometrial cancer is used to guide the development of a pragmatic risk prediction scoring system that could be implemented in the general population. Provisional cutoff values are described pending refinement of the model and external validation in large prospective cohorts. Potential risk-reducing interventions are suggested, highlighting the need for future studies in this area if the increasing tide of endometrial cancer is to be stemmed. Cancer Prev Res; 10(1); 1-13. ©2016 AACR.
authors.affiliation: Division of Molecular and Clinical Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, St Mary's Hospital, Manchester, United Kingdom.|Department of Obstetrics and Gynaecology, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom.
authors.forename: Sarah J
authors.initials: SJ
authors.lastname: Kitson
authors.affiliation: Centre for Genomic Medicine, Division of Evolution and Genomic Medicine, University of Manchester, St Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom.
authors.forename: D Gareth
authors.initials: DG
authors.lastname: Evans
authors.affiliation: Division of Molecular and Clinical Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, St Mary's Hospital, Manchester, United Kingdom. emma.crosbie@manchester.ac.uk.|Department of Obstetrics and Gynaecology, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom.
authors.forename: Emma J
authors.initials: EJ
authors.lastname: Crosbie
mesh_terms: D050218:Body Fat Distribution; D015992:Body Mass Index; D016889:Endometrial Neoplasms / Q000453:epidemiology* / Q000235:genetics / Q000517:prevention & control*; D005260:Female; D000071219:Global Burden of Disease; D006801:Humans; D015994:Incidence; D007333:Insulin Resistance; D016015:Logistic Models; D009765:Obesity / Q000453:epidemiology*; D018570:Risk Assessment / Q000379:methods; D012307:Risk Factors; D006113:United Kingdom / Q000453:epidemiology