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

  1. Li, K
  2. Hüsing, A
  3. Fortner, R T
  4. Tjønneland, A
  5. Hansen, L
  6. Dossus, L
  7. Chang-Claude, J
  8. Bergmann, M
  9. Steffen, A
  10. Bamia, C
  11. Trichopoulos, D
  12. Trichopoulou, A
  13. Palli, D
  14. Mattiello, A
  15. Agnoli, C
  16. Tumino, R
  17. Onland-Moret, N C
  18. Peeters, P H
  19. Bueno-de-Mesquita, H B
  20. Gram, I T
  21. Weiderpass, E
  22. Sánchez-Cantalejo, E
  23. Chirlaque, M-D
  24. Duell, E J
  25. Ardanaz, E
  26. Idahl, A
  27. Lundin, E
  28. Khaw, K-T
  29. Travis, R C
  30. Merritt, M A
  31. Gunter, M J
  32. Riboli, E
  33. Ferrari, P
  34. Terry, K
  35. Cramer, D
  36. Kaaks, R

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WeightNameValue
1000 Titel
  • An epidemiologic risk prediction model for ovarian cancer in Europe: the EPIC study
1000 Autor/in
  1. Li, K |
  2. Hüsing, A |
  3. Fortner, R T |
  4. Tjønneland, A |
  5. Hansen, L |
  6. Dossus, L |
  7. Chang-Claude, J |
  8. Bergmann, M |
  9. Steffen, A |
  10. Bamia, C |
  11. Trichopoulos, D |
  12. Trichopoulou, A |
  13. Palli, D |
  14. Mattiello, A |
  15. Agnoli, C |
  16. Tumino, R |
  17. Onland-Moret, N C |
  18. Peeters, P H |
  19. Bueno-de-Mesquita, H B |
  20. Gram, I T |
  21. Weiderpass, E |
  22. Sánchez-Cantalejo, E |
  23. Chirlaque, M-D |
  24. Duell, E J |
  25. Ardanaz, E |
  26. Idahl, A |
  27. Lundin, E |
  28. Khaw, K-T |
  29. Travis, R C |
  30. Merritt, M A |
  31. Gunter, M J |
  32. Riboli, E |
  33. Ferrari, P |
  34. Terry, K |
  35. Cramer, D |
  36. Kaaks, R |
1000 Erscheinungsjahr 2015
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2015-03-05
1000 Erschienen in
1000 Quellenangabe
  • 112: 1257–1265
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2015
1000 Lizenz
1000 Verlagsversion
  • http://doi.org/10.1038/bjc.2015.22 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4385951/ |
1000 Ergänzendes Material
  • https://www.nature.com/bjc/journal/v112/n7/suppinfo/bjc201522s1.html?url=/bjc/journal/v112/n7/full/bjc201522a.html |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • 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.
1000 Sacherschließung
lokal risk model
lokal ovarian cancer
lokal reproductive risk factors
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
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1000 Label
1000 Förderer
  1. European Commission (DG-SANCO) |
  2. International Agency for Research on Cancer |
  3. Danish Cancer Society (Denmark) |
  4. Ligue contre le Cancer (France) |
  5. Deutsche Krebshilfe (Germany) |
  6. Deutsches Krebsforschungszentrum (Germany) |
  7. Federal Ministry of Education and Research (Germany) |
  8. Hellenic Health Foundation (Greece) |
  9. Italian Association for Research on Cancer (Italy) |
  10. National Research Council (Italy) |
  11. Dutch Ministry of Public Health, Welfare and Sports (The Netherlands) |
  12. Netherlands Cancer Registry (The Netherlands) |
  13. LK Research Funds (The Netherlands) |
  14. Dutch Prevention Funds (The Netherlands) |
  15. Dutch ZON (Zorg Onderzoek Nederland)(The Netherlands) |
  16. World Cancer Research Fund (The Netherlands) |
  17. Norwegian Research Council (Norway) |
  18. Norwegian Cancer Society (Norway) |
  19. Nordforsk (Norway) |
  20. Nordic Centre of Excellence programme on Food, Nutrition and Health (Norway) |
  21. Health Research Fund (FIS)(Spain) |
  22. Spanish Ministry of Health (Spain) |
  23. Catalan Institute of Oncology (Spain) |
  24. Regional Government of Andalucia (Spain) |
  25. Regional Government of Asturias (Spain) |
  26. Regional Government of Basque Country (Spain) |
  27. Regional Government of Murcia (Spain) |
  28. Navarra (Spain) |
  29. ISCIII RETIC (Spain) |
  30. Swedish Cancer Society (Sweden) |
  31. Swedish Scientific Council (Sweden) |
  32. Regional Government of Skane and Vasterbotten (Sweden) |
  33. Cancer Research UK (United Kingdom) |
  34. Medical Research Council (United Kingdom) |
  35. NIH |
  36. Mutuelle Generale de l'Education Nationale (France) |
  37. Institut National de la Sante et de la Recherche Medicale (France) |
  38. Statistics Netherlands (The Netherlands) |
  39. ERC-AdG |
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  35. Screening and Risk Biomarkers for Ovarian Cancer in EPIC Specimens
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1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6403207.rdf
1000 Erstellt am 2017-06-26T10:11:18.777+0200
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1000 Zuletzt bearbeitet 2022-10-21T12:25:21.876+0200
1000 Objekt bearb. Fri Oct 21 12:25:21 CEST 2022
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