Dataset Information

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

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.

SUBMITTER: Aleksandrova K

PROVIDER: S-EPMC7780676 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

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

Aleksandrova Krasimira K Reichmann Robin R Kaaks Rudolf R Jenab Mazda M Bueno-de-Mesquita H Bas HB Dahm Christina C CC Eriksen Anne Kirstine AK Tjønneland Anne A Artaud Fanny F Boutron-Ruault Marie-Christine MC Severi Gianluca G Hüsing Anika A Trichopoulou Antonia A Karakatsani Anna A Peppa Eleni E Panico Salvatore S Masala Giovanna G Grioni Sara S Sacerdote Carlotta C Tumino Rosario R Elias Sjoerd G SG May Anne M AM Borch Kristin B KB Sandanger Torkjel M TM Skeie Guri G Sánchez Maria-Jose MJ Huerta José María JM Sala Núria N Gurrea Aurelio Barricarte AB Quirós José Ramón JR Amiano Pilar P Berntsson Jonna J Drake Isabel I van Guelpen Bethany B Harlid Sophia S Key Tim T Weiderpass Elisabete E Aglago Elom K EK Cross Amanda J AJ Tsilidis Konstantinos K KK Riboli Elio E Gunter Marc J MJ

BMC medicine 20210104 1

<h4>Background</h4>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 ...[more]

PMID: 33390155

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Project description:BackgroundEffective risk stratification tools for post-polypectomy colorectal cancer (PPCRC) are lacking. We aimed to develop an effective risk stratification tool for the prediction of PPCRC in three large population-based cohorts and to validate the tool in a clinical cohort.MethodsLeveraging the integrated endoscopic, histopathologic and epidemiologic data in three U.S population-based cohorts of health professional (the Nurses' Health Study (NHS) I, II and Health Professionals Follow-up Study (HPFS)), we developed a risk score to predict incident PPCRC among 26,741 patients with a polypectomy between 1986 and 2017. We validated the PPCRC score in the Mass General Brigham (MGB) Colonoscopy Cohort (Boston, Massachusetts, U.S) of 76,603 patients with a polypectomy between 2007 and 2018. In all four cohorts, we collected detailed data on patients' demographics, endoscopic history, polyp features, and lifestyle factors at polypectomy. The outcome, incidence of PPCRC, was assessed by biennial follow-up questionnaires in the NHS/HPFS cohorts, and through linkage to the Massachusetts Cancer Registry in the MGB cohort. In all four cohorts, individuals who were diagnosed with CRC or died before baseline or within six months after baseline were excluded. We used Cox regression to calculate the hazard ratio (HR), 95% confidence interval (CI) and assessed the discrimination using C-statistics and reclassification using the Net Reclassification Improvement (NRI).FindingsDuring a median follow-up of 12.8 years (interquartile range (IQR): 9.3, 16.7) and 5.1 years (IQR: 2.7, 7.8) in the NHS/HPFS and MGB cohorts, we documented 220 and 241 PPCRC cases, respectively. We identified a PPCRC risk score based on 11 predictors. In the validation cohort, the PPCRC risk score showed a strong association with PPCRC risk (HR for high vs. low, 3.55, 95% CI, 2.59-4.88) and demonstrated a C-statistic (95% CI) of 0.75 (0.70-0.79), and was discriminatory even within the low- and high-risk polyp groups (C-statistic, 0.73 and 0.71, respectively) defined by the current colonoscopy surveillance recommendations, leading to a NRI of 45% (95% CI, 36-54%) for patients with PPCRC.InterpretationWe developed and validated a risk stratification model for PPCRC that may be useful to guide tailored colonoscopy surveillance. Further work is needed to determine the optimal surveillance interval and test the added value of other predictors of PPCRC beyond those included in the current study, along with implementation studies.FundingUS National Institutes of Health, the American Cancer Society, the South-Eastern Norway Regional Health Authority, the Deutsche Forschungsgemeinschaft.

Dataset Information

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

Background

Methods

Results

Conclusions

Publications

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

Similar Datasets

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