Format

Send to

Choose Destination
Br J Cancer. 2015 Mar 31;112(7):1257-65. doi: 10.1038/bjc.2015.22.

An epidemiologic risk prediction model for ovarian cancer in Europe: the EPIC study.

Author information

1
Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
2
The Danish Cancer Society Research Center, Copenhagen, Denmark.
3
1] Inserm, Centre for research in Epidemiology and Population Health (CESP), U1018, Nutrition, Hormones and Women's Health team, F-94805 Villejuif, France [2] University Paris Sud, UMRS 1018, F-94805 Villejuif, France.
4
German Institute of Human Nutrition in Potsdam-Rehbruecke, Potsdam, Germany.
5
Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece.
6
1] Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA [2] Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece [3] Hellenic Health Foundation, Athens, Greece.
7
1] Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece [2] Hellenic Health Foundation, Athens, Greece.
8
Molecular and Nutritional Epidemiology Unit, Cancer Research and Prevention Institute-ISPO, Florence, Italy.
9
Dipartimento di Medicina Clinica e Chirurgia, University of Naples Federico II, Naples, Italy.
10
Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
11
Cancer Registry and Histopathology Unit, 'Civic-M.P. Arezzo' Hospital, Ragusa, Italy.
12
Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
13
1] Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands [2] MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
14
Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
15
Department of Community Medicine, Faculty of Health Sciences, The Arctic University of Norway, Tromsø, Norway.
16
1] Department of Community Medicine, Faculty of Health Sciences, The Arctic University of Norway, Tromsø, Norway [2] Department of Research, Cancer Registry of Norway, Oslo, Norway [3] Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
17
1] Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria de Granada (Granada.ibs), Granada, Spain [2] CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
18
1] CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain [2] Department of Epidemiology, Murcia Regional Health Authority, Murcia, Spain.
19
Unit of Nutrition, Environment and Cancer Epidemiology Research Program, Bellvitge Biomedical Research Institute (IDIBELL), Catalan Institute of Oncology (ICO), Barcelona, Spain.
20
1] CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain [2] Navarre Public Health Institute, Pamplona, Spain.
21
Department of Clinical Sciences, Obstetrics and Gynecology and Department of Public Health and Clinical Medicine, Nutritional Research Umeå University, Umeå, Sweden.
22
Department of Medical Biosciences, Pathology Umeå University, Umeå, Sweden.
23
University of Cambridge, School of Clinical Medicine, Cambridge, UK.
24
Cancer Epidemiology Unit, Nuffield Department of Population Health University of Oxford, Oxford, UK.
25
Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK.
26
International Agency for Research on Cancer, Lyon, France.
27
1] Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA [2] Obstetrics and Gynecology Epidemiology Center, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Abstract

BACKGROUND:

Ovarian cancer has a high case-fatality ratio, largely due to late diagnosis. Epidemiologic risk prediction models could help identify women at increased risk who may benefit from targeted prevention measures, such as screening or chemopreventive agents.

METHODS:

We built an ovarian cancer risk prediction model with epidemiologic risk factors from 202,206 women in the European Prospective Investigation into Cancer and Nutrition study.

RESULTS:

Older age at menopause, longer duration of hormone replacement therapy, and higher body mass index were included as increasing ovarian cancer risk, whereas unilateral ovariectomy, longer duration of oral contraceptive use, and higher number of full-term pregnancies were decreasing risk. The discriminatory power (overall concordance index) of this model, as examined with five-fold cross-validation, was 0.64 (95% confidence interval (CI): 0.57, 0.70). The ratio of the expected to observed number of ovarian cancer cases occurring in the first 5 years of follow-up was 0.90 (293 out of 324, 95% CI: 0.81-1.01), in general there was no evidence for miscalibration.

CONCLUSION:

Our ovarian cancer risk model containing only epidemiological data showed modest discriminatory power for a Western European population. Future studies should consider adding informative biomarkers to possibly improve the predictive ability of the model.

PMID:
25742479
PMCID:
PMC4385951
DOI:
10.1038/bjc.2015.22
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Nature Publishing Group Icon for PubMed Central
Loading ...
Support Center