RT Journal Article
T1 Development and validation of a lifestyle-based model for colorectal cancer risk prediction: the LiFeCRC score
A1 Aleksandrova, Krasimira
A1 Reichmann, Robin
A1 Kaaks, Rudolf
A1 Jenab, Mazda
A1 Bueno-de-Mesquita, H. Bas
A1 Dahm, Christina C.
A1 Eriksen, Anne Kirstine
A1 Tjønneland, Anne
A1 Artaud, Fanny
A1 Boutron-Ruault, Marie-Christine
A1 Severi, Gianluca
A1 Hüsing, Anika
A1 Trichopoulou, Antonia
A1 Karakatsani, Anna
A1 Peppa, Eleni
A1 Panico, Salvatore
A1 Masala, Giovanna
A1 Grioni, Sara
A1 Sacerdote, Carlotta
A1 Tumino, Rosario
A1 Elias, Sjoerd G.
A1 May, Anne M.
A1 Borch, Kristin B.
A1 Sandanger, Torkjel M.
A1 Skeie, Guri
A1 Sanchez-Perez, Maria-Jose
A1 Huerta, José María
A1 Sala, Núria
A1 Gurrea, Aurelio Barricarte
A1 Quirós, José Ramón
A1 Amiano, Pilar
A1 Berntsson, Jonna
A1 Drake, Isabel
A1 van Guelpen, Bethany
A1 Harlid, Sophia
A1 Key, Tim
A1 Weiderpass, Elisabete
A1 Aglago, Elom K.
A1 Cross, Amanda J.
A1 Tsilidis, Konstantinos K.
A1 Riboli, Elio
A1 Gunter, Marc J.
K1 Colorectal cancer
K1 Risk prediction
K1 Lifestyle behaviour
K1 Risk screening
K1 Cancer prevention
K1 Neoplasias colorrectales
K1 Riesgo
K1 Estilo de vida
K1 Prevención de Enfermedades
AB 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.
PB BioMed Central, Springer Nature
YR 2021
FD 2021-01-04
LK http://hdl.handle.net/10668/3881
UL http://hdl.handle.net/10668/3881
LA en
NO Aleksandrova K, Reichmann R, Kaaks R, Jenab M, Bueno-de-Mesquita HB, Dahm CC, et al. Development and validation of a lifestyle-based model for colorectal cancer risk prediction: the LiFeCRC score. BMC Med. 2021 Jan 4;19(1):1
DS RISalud
RD May 9, 2025