Lifestyle factors and colorectal cancer prediction: A nomogram-based model

Abstract Background Lifestyle factors are important contributors to the risk of colorectal cancer (CRC). This study developed and validated an age-based CRC risk-prediction model incorporating lifestyle factors using the National Health Insurance Service (NHIS)-National Sample Cohort database. Metho...

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Main Authors: Wooin Seo, Se Young Jung, Yeonhoon Jang, Kiheon Lee
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Cancer
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Online Access:https://doi.org/10.1186/s12885-025-14674-z
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author Wooin Seo
Se Young Jung
Yeonhoon Jang
Kiheon Lee
author_facet Wooin Seo
Se Young Jung
Yeonhoon Jang
Kiheon Lee
author_sort Wooin Seo
collection DOAJ
description Abstract Background Lifestyle factors are important contributors to the risk of colorectal cancer (CRC). This study developed and validated an age-based CRC risk-prediction model incorporating lifestyle factors using the National Health Insurance Service (NHIS)-National Sample Cohort database. Methods Individuals who underwent the National Health Examination between 2009 and 2012 were eligible as study participants. Among them, 119,700 (30.38%) were aged 20–39, 190,645 (48.39%) were aged 40–59, and 83,611 (21.22%) were aged ≥ 60. Using the LASSO regression algorithm, we selected risk factors and fitted a Cox proportional hazards model to predict the 10-year CRC incidence. Nomogram-based risk scores were calculated for each age group. Candidate risk factors included sex, age, abdominal obesity, BMI, smoking, alcohol consumption, physical activity, presence of abnormal liver function, hypertension, hypercholesterolemia, and type 2 diabetes mellitus. Results In each age group, higher risk scores had a higher incidence probability of CRC. In the discriminatory analysis, the concordance indices of the three models ranged from 0.60 to 0.70, indicating moderate discrimination power. The calibration plot from 10-fold cross-validation showed that the observed proportions of events and predicted probabilities overlapped the entire range of probabilities fairly well. Kaplan-Meier plots demonstrated that individuals in the high-risk group were more likely to develop CRC within 10 years than those in the low-risk group. Conclusion Lifestyle factors were identified as significant predictors of CRC incidence, with slight differences across age groups. Nomogram-based risk scores could be used as a tailored intervention to motivate individuals to modify their lifestyles.
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spelling doaj-art-e6a303dc74f74868b359c10b26e25efc2025-08-20T03:43:22ZengBMCBMC Cancer1471-24072025-07-0125111010.1186/s12885-025-14674-zLifestyle factors and colorectal cancer prediction: A nomogram-based modelWooin Seo0Se Young Jung1Yeonhoon Jang2Kiheon Lee3Office of Hospital Information, Seoul National University Bundang HospitalOffice of Hospital Information, Seoul National University Bundang HospitalOffice of Hospital Information, Seoul National University Bundang HospitalDepartment of Family Medicine, Seoul National University Bundang HospitalAbstract Background Lifestyle factors are important contributors to the risk of colorectal cancer (CRC). This study developed and validated an age-based CRC risk-prediction model incorporating lifestyle factors using the National Health Insurance Service (NHIS)-National Sample Cohort database. Methods Individuals who underwent the National Health Examination between 2009 and 2012 were eligible as study participants. Among them, 119,700 (30.38%) were aged 20–39, 190,645 (48.39%) were aged 40–59, and 83,611 (21.22%) were aged ≥ 60. Using the LASSO regression algorithm, we selected risk factors and fitted a Cox proportional hazards model to predict the 10-year CRC incidence. Nomogram-based risk scores were calculated for each age group. Candidate risk factors included sex, age, abdominal obesity, BMI, smoking, alcohol consumption, physical activity, presence of abnormal liver function, hypertension, hypercholesterolemia, and type 2 diabetes mellitus. Results In each age group, higher risk scores had a higher incidence probability of CRC. In the discriminatory analysis, the concordance indices of the three models ranged from 0.60 to 0.70, indicating moderate discrimination power. The calibration plot from 10-fold cross-validation showed that the observed proportions of events and predicted probabilities overlapped the entire range of probabilities fairly well. Kaplan-Meier plots demonstrated that individuals in the high-risk group were more likely to develop CRC within 10 years than those in the low-risk group. Conclusion Lifestyle factors were identified as significant predictors of CRC incidence, with slight differences across age groups. Nomogram-based risk scores could be used as a tailored intervention to motivate individuals to modify their lifestyles.https://doi.org/10.1186/s12885-025-14674-zColorectal cancerNomogramsLifestyleRisk factors
spellingShingle Wooin Seo
Se Young Jung
Yeonhoon Jang
Kiheon Lee
Lifestyle factors and colorectal cancer prediction: A nomogram-based model
BMC Cancer
Colorectal cancer
Nomograms
Lifestyle
Risk factors
title Lifestyle factors and colorectal cancer prediction: A nomogram-based model
title_full Lifestyle factors and colorectal cancer prediction: A nomogram-based model
title_fullStr Lifestyle factors and colorectal cancer prediction: A nomogram-based model
title_full_unstemmed Lifestyle factors and colorectal cancer prediction: A nomogram-based model
title_short Lifestyle factors and colorectal cancer prediction: A nomogram-based model
title_sort lifestyle factors and colorectal cancer prediction a nomogram based model
topic Colorectal cancer
Nomograms
Lifestyle
Risk factors
url https://doi.org/10.1186/s12885-025-14674-z
work_keys_str_mv AT wooinseo lifestylefactorsandcolorectalcancerpredictionanomogrambasedmodel
AT seyoungjung lifestylefactorsandcolorectalcancerpredictionanomogrambasedmodel
AT yeonhoonjang lifestylefactorsandcolorectalcancerpredictionanomogrambasedmodel
AT kiheonlee lifestylefactorsandcolorectalcancerpredictionanomogrambasedmodel