Christina C. Dahm

Development and validation of a lifestyle-based model for colorectal cancer risk prediction: the LiFeCRC score

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • Krasimira Aleksandrova, German Institute of Human Nutrition Potsdam-Rehbruecke, University of Potsdam, Leibniz Institute for Prevention Research and Epidemiology
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  • Robin Reichmann, German Institute of Human Nutrition Potsdam-Rehbruecke, University of Potsdam
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  • Rudolf Kaaks, German Cancer Research Center
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  • Mazda Jenab, International Agency for Research on Cancer
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  • H. Bas Bueno-de-Mesquita, National Institute of Public Health and the Environment, Imperial College London
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  • Christina C. Dahm
  • Anne Kirstine Eriksen, Danish Cancer Society
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  • Anne Tjønneland, Danish Cancer Society
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  • Fanny Artaud, Universite Paris-Saclay, Institut Gustave Roussy
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  • Marie Christine Boutron-Ruault, Universite Paris-Saclay, Institut Gustave Roussy
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  • Gianluca Severi, Universite Paris-Saclay, Institut Gustave Roussy, University of Florence
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  • Anika Hüsing, German Cancer Research Center
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  • Antonia Trichopoulou, Helenic Health Foundation
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  • Anna Karakatsani, Helenic Health Foundation, University of Athens
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  • Eleni Peppa, Helenic Health Foundation
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  • Salvatore Panico, University of Naples Federico II
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  • Giovanna Masala, Institute for the Study and Prevention of Cancer
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  • Sara Grioni, IRCCS Fondazione Istituto Nazionale per lo studio e la cura dei tumori - Milano
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  • Carlotta Sacerdote, Azienda Ospedaliera - Universitaria Città della Salute e della Scienza di Torino, Center for Cancer Prevention, Turin, Italy.
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  • Rosario Tumino, Provincial Health Authority (ASP)
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  • Sjoerd G. Elias, Utrecht University
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  • Anne M. May, Utrecht University
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  • Kristin B. Borch, UiT The Arctic University of Norway
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  • Torkjel M. Sandanger, UiT The Arctic University of Norway
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  • Guri Skeie, UiT The Arctic University of Norway
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  • Maria Jose Sánchez, Escuela Andaluza de Salud Publica, Instituto de Investigación Biosanitaria (ibs.GRANADA), CIBER - Center for Biomedical Research Network, University of Granada
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  • José María Huerta, CIBER - Center for Biomedical Research Network, Murcia Regional Health Council
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  • Núria Sala, Institute Catala Oncologia, Bellvitge Biomedical Research Institute
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  • Aurelio Barricarte Gurrea, CIBER - Center for Biomedical Research Network, Navarra Public Health Institute, Navarra Institute for Health Research (IdiSNA)
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  • José Ramón Quirós, Public Health Directorate
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  • Pilar Amiano, CIBER - Center for Biomedical Research Network, Instituto de Investigación Sanitaria Biodonostia
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  • Jonna Berntsson, Lund University
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  • Isabel Drake, Lund University
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  • Bethany van Guelpen, Umeå University
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  • Sophia Harlid, Umeå University
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  • Tim Key, University of Oxford
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  • Elisabete Weiderpass, International Agency for Research on Cancer
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  • Elom K. Aglago, International Agency for Research on Cancer
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  • Amanda J. Cross, Imperial College London
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  • Konstantinos K. Tsilidis, Imperial College London, University of Ioannina
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  • Elio Riboli, Imperial College London
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  • Marc J. Gunter, International Agency for Research on Cancer

Background: Nutrition and lifestyle have been long established as risk factors for colorectal cancer (CRC). Modifiable lifestyle behaviours bear potential to minimize long-term CRC risk; however, translation of lifestyle information into individualized CRC risk assessment has not been implemented. Lifestyle-based risk models may aid the identification of high-risk individuals, guide referral to screening and motivate behaviour change. We therefore developed and validated a lifestyle-based CRC risk prediction algorithm in an asymptomatic European population. Methods: The model was based on data from 255,482 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) study aged 19 to 70 years who were free of cancer at study baseline (1992–2000) and were followed up to 31 September 2010. The model was validated in a sample comprising 74,403 participants selected among five EPIC centres. Over a median follow-up time of 15 years, there were 3645 and 981 colorectal cancer cases in the derivation and validation samples, respectively. Variable selection algorithms in Cox proportional hazard regression and random survival forest (RSF) were used to identify the best predictors among plausible predictor variables. Measures of discrimination and calibration were calculated in derivation and validation samples. To facilitate model communication, a nomogram and a web-based application were developed. Results: The final selection model included age, waist circumference, height, smoking, alcohol consumption, physical activity, vegetables, dairy products, processed meat, and sugar and confectionary. The risk score demonstrated good discrimination overall and in sex-specific models. Harrell’s C-index was 0.710 in the derivation cohort and 0.714 in the validation cohort. The model was well calibrated and showed strong agreement between predicted and observed risk. Random survival forest analysis suggested high model robustness. Beyond age, lifestyle data led to improved model performance overall (continuous net reclassification improvement = 0.307 (95% CI 0.264–0.352)), and especially for young individuals below 45 years (continuous net reclassification improvement = 0.364 (95% CI 0.084–0.575)). Conclusions: LiFeCRC score based on age and lifestyle data accurately identifies individuals at risk for incident colorectal cancer in European populations and could contribute to improved prevention through motivating lifestyle change at an individual level.

Original languageEnglish
Article number1
JournalBMC Medicine
Volume19
Issue1
Number of pages19
ISSN1741-7015
DOIs
Publication statusPublished - Jan 2021

    Research areas

  • Cancer prevention, Colorectal cancer, Lifestyle behaviour, Risk prediction, Risk screening

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