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Title: Development and validation of a lifestyle-based model for colorectal cancer risk prediction: the LiFeCRC score
Author: Aleksandrova, Krasimira
Reichmann, Robin
Kaaks, Rudolf
Jenab, Mazda
Bueno de Mesquita, H. Bas
Dahm, Christina C.
Eriksen, Anne Kirstine
Tjønneland, Anne
Artaud, Fanny
Boutron-Ruault, Marie-Christine
Severi, Gianluca
Hüsing, Anika
Trichopoulou, Antonia
Karakatsani, Anna
Peppa, Eleni
Panico, Salvatore
Masala, Giovanna
Grioni, Sara
Sacerdote, Carlotta
Tumino, Rosario
Elias, Sjoerd G.
May, Anne M.
Borch, Kristin B.
Sandanger, Torkjel M.
Skeie, Guri
Sánchez, Maria Jose
Huerta Castaño, José María
Sala Serra, Núria
Barricarte, Aurelio
Quirós, J. Ramón
Amiano, Pilar
Berntsson, Jonna
Drake, Isabel
van Guelpen, Bethany
Harlid, Sophia
Key, Tim
Weiderpass, Elisabete
Aglago, Elom K.
Cross, Amanda J.
Tsilidis, Konstantinos K.
Riboli, Elio
Gunter, Marc J.
Keywords: Càncer colorectal
Estils de vida
Colorectal cancer
Issue Date: 4-Dec-2021
Publisher: BioMed Central
Abstract: 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.
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It is part of: BMC Medicine, 2021, vol. 19
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Appears in Collections:Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))

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