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Eur J Epidemiol. 2016 Jan;31(1):51-60. doi: 10.1007/s10654-015-0030-9. Epub 2015 May 13.

An epidemiological model for prediction of endometrial cancer risk in Europe.

Author information

1
Division of Cancer Epidemiology (C020), German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120, Heidelberg, Germany. a.huesing@dkfz.de.
2
Inserm, Centre for Research in Epidemiology and Population Health (CESP), U1018, Nutrition, Hormones and Women's Health Team, 94805, Villejuif, France.
3
UnivParis Sud, UMRS 1018, 94805, Villejuif, France.
4
IGR, 94805, Villejuif, France.
5
International Agency for Research on Cancer, Lyon, France.
6
Danish Cancer Society Research Center, Copenhagen, Denmark.
7
Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, 3053, Australia.
8
Centre for Molecular, Environmental, Genetic, and Analytic Epidemiology, The University of Melbourne, Melbourne, 3010, Australia.
9
Division of Cancer Epidemiology (C020), German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.
10
Unit of Genetic Epidemiology, Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
11
German Institute of Human Nutrition in Potsdam-Rehbruecke, Potsdam, Germany.
12
Hellenic Health Foundation, 13 Kaisareias Street, 115 27, Athens, Greece.
13
Bureau of Epidemiologic Research, Academy of Athens, 23 Alexandroupoleos Street, 115 27, Athens, Greece.
14
Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, 75 M. Asias Street, Goudi, 115 27, Athens, Greece.
15
Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Via Venezian, 1, 20133, Milan, Italy.
16
Molecular and Nutritional Epidemiology Unit, Cancer Research and Prevention Institute - ISPO, Florence, Italy.
17
Dipartimento Di Medicina Clinica E Chirurgia, Federico II University, Naples, Italy.
18
Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
19
Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK.
20
National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
21
Department of Gastroenterology and Hepatology, University Medical Centre, Utrecht, The Netherlands.
22
Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, UiT The Arctic University of Norway, Tromsø, Norway.
23
Department of Research, Cancer Registry of Norway, Oslo, Norway.
24
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
25
Samfundet Folkhälsan, Helsinki, Finland.
26
Navarre Public Health Institute, Pamplona, Spain.
27
CIBER Epidemiology and Public Health CIBERESP, Madrid, Spain.
28
Unit of Nutrition, Environment and Cancer. Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO-IDIBELL), Barcelona, Spain.
29
Department of Epidemiology, Murcia Regional Health Council, Murcia, Spain.
30
Department of Health and Social Sciences, Universidad de Murcia, Murcia, Spain.
31
Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria de Granada (Granada.ibs), Granada, Spain.
32
Public Health Division of Gipuzkoa-BIODONOSTIA, Basque Regional Health Department, San Sebastián, Spain.
33
CTSU, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
34
School of Clinical Medicine, University of Cambridge, Cambridge, UK.
35
MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.

Abstract

Endometrial cancer (EC) 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 EC cases from eight countries in the European Prospective Investigation into Cancer and Nutrition cohort, a model to predict 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 well-calibrated (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.

KEYWORDS:

Endometrial cancer; Epidemiology; Prevention; Risk model

PMID:
25968175
DOI:
10.1007/s10654-015-0030-9
[Indexed for MEDLINE]
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