Endometrial cancer risk prediction including serum-based biomarkers: results from the EPIC cohort.

Autor: Fortner RT; Division of Cancer Epidemiology, German Cancer Research Center (DFKZ), Heidelberg, Germany., Hüsing A; Division of Cancer Epidemiology, German Cancer Research Center (DFKZ), Heidelberg, Germany., Kühn T; Division of Cancer Epidemiology, German Cancer Research Center (DFKZ), Heidelberg, Germany., Konar M; Division of Cancer Epidemiology, German Cancer Research Center (DFKZ), Heidelberg, Germany.; Department of Biostatistics, Hacettepe University, Ankara, Turkey., Overvad K; Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark., Tjønneland A; Unit of Diet, Genes and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark., Hansen L; Unit of Diet, Genes and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark., Boutron-Ruault MC; INSERM, Centre for Research in Epidemiology and Population Health (CESP), U1018, Nutrition, Hormones and Women's Health team, Villejuif, France.; Université Paris Sud, UMRS 1018, Villejuif, France.; Gustave Roussy, Villejuif, France., Severi G; INSERM, Centre for Research in Epidemiology and Population Health (CESP), U1018, Nutrition, Hormones and Women's Health team, Villejuif, France.; Université Paris Sud, UMRS 1018, Villejuif, France.; Gustave Roussy, Villejuif, France.; Human Genetics Foundation (HuGeF), Torino, Italy., Fournier A; INSERM, Centre for Research in Epidemiology and Population Health (CESP), U1018, Nutrition, Hormones and Women's Health team, Villejuif, France.; Université Paris Sud, UMRS 1018, Villejuif, France.; Gustave Roussy, Villejuif, France., Boeing H; Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany., Trichopoulou A; Hellenic Health Foundation, Athens, Greece.; WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece., Benetou V; Hellenic Health Foundation, Athens, Greece.; WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece., Orfanos P; Hellenic Health Foundation, Athens, Greece.; WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece., Masala G; Cancer Risk Factors and Life-Style Epidemiology Unit, Cancer Research and Prevention Institute-ISPO, Florence, Italy., Agnoli C; Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy., Mattiello A; Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy., Tumino R; Cancer Registry and Histopathology Unit, 'Civic-M.P.Arezzo' Hospital, ASP Ragusa, Italy., Sacerdote C; Unit of Cancer Epidemiology, Città della Salute e della Scienza University-Hospital and Center for Cancer Prevention (CPO), Turin, Italy., Bueno-de-Mesquita HB; Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.; Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, United Kingdom.; Department of Social & Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia., Peeters PH; Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands.; MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, United Kingdom., Weiderpass E; Department of Community Medicine, University of Tromsø, The Arctic University of Norway, Tromsø, Norway.; Department of Research, Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway.; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.; Genetic Epidemiology Group, Folkhälsan Research Center, Helsinki, Finland., Gram IT; Department of Community Medicine, University of Tromsø, The Arctic University of Norway, Tromsø, Norway., Gavrilyuk O; Department of Community Medicine, University of Tromsø, The Arctic University of Norway, Tromsø, Norway.; Department of Obstetrics and Gynecology, University Hospital Northern Norway, Tromsø, Norway., Quirós JR; Public Health Directorate, Asturias, Spain., Maria Huerta J; Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain.; CIBER Epidemiología y Salud Pública (CIBERESP), Spain., Ardanaz E; CIBER Epidemiología y Salud Pública (CIBERESP), Spain.; Navarra Public Health Institute, Pamplona, Spain.; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain., Larrañaga N; CIBER Epidemiología y Salud Pública (CIBERESP), Spain.; Public Health Division of Gipuzkoa, Regional Government of the Basque Country, Donostia, Spain., Lujan-Barroso L; Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain., Sánchez-Cantalejo E; CIBER Epidemiología y Salud Pública (CIBERESP), Spain.; Escuela Andaluza de Salud Pública. Instituto de Investigación Biosanitaria ibs.Granada. Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain., Butt ST; Division of Surgery, Clinical Sciences Malmö, Lund University, Lund, Sweden., Borgquist S; Division of Oncology and Pathology, Clinical Sciences, Lund University, Lund, Sweden., Idahl A; Department of Clinical Sciences, Obstetrics and Gynecology, Umeå University, Umeå, Sweden.; Department of Public Health and Clinical Medicine, Nutritional Research, Umeå University, Umeå, Sweden., Lundin E; Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden., Khaw KT; Cancer Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom., Allen NE; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Cambridge, United Kingdom., Rinaldi S; International Agency for Research on Cancer, Lyon, France., Dossus L; International Agency for Research on Cancer, Lyon, France., Gunter M; International Agency for Research on Cancer, Lyon, France., Merritt MA; School of Public Health, Imperial College London, London, United Kingdom., Tzoulaki I; School of Public Health, Imperial College London, London, United Kingdom., Riboli E; School of Public Health, Imperial College London, London, United Kingdom., Kaaks R; Division of Cancer Epidemiology, German Cancer Research Center (DFKZ), Heidelberg, Germany.
Jazyk: angličtina
Zdroj: International journal of cancer [Int J Cancer] 2017 Mar 15; Vol. 140 (6), pp. 1317-1323.
DOI: 10.1002/ijc.30560
Abstrakt: Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimination. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigated for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selection process; biomarkers were retained at p < 0.157 indicating improvement in the Akaike information criterion (AIC). Improvement in discrimination was assessed using the C-statistic for all biomarkers alone, and change in C-statistic from addition of biomarkers to preexisting absolute risk estimates. We used internal validation with bootstrapping (1000-fold) to adjust for over-fitting. Adiponectin, estrone, interleukin-1 receptor antagonist, tumor necrosis factor-alpha and triglycerides were selected into the model. After accounting for over-fitting, discrimination was improved by 2.0 percentage points when all evaluated biomarkers were included and 1.7 percentage points in the model including the selected biomarkers. Models including etiologic markers on independent pathways and genetic markers may further improve discrimination.
(© 2016 UICC.)
Databáze: MEDLINE
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