Development and validation of a prediction model for early screening of people at high risk for colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a serious threat worldwide. Although early screening is suggested to be the most effective method to prevent and control CRC, the current situation of early screening for CRC is still not optimistic. In China, the incidence of CRC in the Yangtze River Delta region is increasing dramatically, but few studies have been conducted. Therefore, it is necessary to develop a simple and efficient early screening model for CRC.

AIM

To develop and validate an early-screening nomogram model to identify individuals at high risk of CRC.

METHODS

Data of 64448 participants obtained from Ningbo Hospital, China between 2014 and 2017 were retrospectively analyzed. The cohort comprised 64448 individuals, of which, 530 were excluded due to missing or incorrect data. Of 63918, 7607 (11.9%) individuals were considered to be high risk for CRC, and 56311 (88.1%) were not. The participants were randomly allocated to a training set (44743) or validation set (19175). The discriminatory ability, predictive accuracy, and clinical utility of the model were evaluated by constructing and analyzing receiver operating characteristic (ROC) curves and calibration curves and by decision curve analysis. Finally, the model was validated internally using a bootstrap resampling technique.

RESULTS

Seven variables, including demographic, lifestyle, and family history information, were examined. Multifactorial logistic regression analysis revealed that age [odds ratio (OR): 1.03, 95% confidence interval (CI): 1.02-1.03, P < 0.001], body mass index (BMI) (OR: 1.07, 95%CI: 1.06-1.08, P < 0.001), waist circumference (WC) (OR: 1.03, 95%CI: 1.02-1.03 P < 0.001), lifestyle (OR: 0.45, 95%CI: 0.42-0.48, P < 0.001), and family history (OR: 4.28, 95%CI: 4.04-4.54, P < 0.001) were the most significant predictors of high-risk CRC. Healthy lifestyle was a protective factor, whereas family history was the most significant risk factor. The area under the curve was 0.734 (95%CI: 0.723-0.745) for the final validation set ROC curve and 0.735 (95%CI: 0.728-0.742) for the training set ROC curve. The calibration curve demonstrated a high correlation between the CRC high-risk population predicted by the nomogram model and the actual CRC high-risk population.

CONCLUSION

The early-screening nomogram model for CRC prediction in high-risk populations developed in this study based on age, BMI, WC, lifestyle, and family history exhibited high accuracy.

Metal/metalloid levels in hair of Shenzhen residents and the associated influencing factors

129 Shenzhen residents' hair samples were collected and the metal/metalloid concentrations of Hg, As, Pb, Cd, Cr, Cu, Mn, Zn, Fe and Ni were detected. Meanwhile, the relationships between metal/metalloid contents in human hair and gender, age, seafood diet habit, smoking habit, as well as the housing type (dwelling environment) were analyzed. Results showed that the average content of Hg, As, Pb, Cd, Cr, Cu, Mn, Zn, Fe and Ni in human hair of Shenzhen residents was 0.76 ± 0.96, 0.10 ± 0.04, 5.25 ± 4.88, 0.25 ± 0.33, 0.60 ± 0.31, 13.84 ± 3.67, 2.82 ± 2.01, 196.90 ± 145.01, 12.20 ± 5.10 and 0.34 ± 0.32 μg/g, respectively. Compared with other regions at home and abroad, most metal/metalloids in Shenzhen residents were at a moderate level, and the highly toxic elements (i.e. Pb, Cd, As and Hg) didn't exceed the upper limit of normal values in China. Statistical analysis showed that the young male people contained significantly higher (p < 0.05) level of Pb (in age group of 20-30 years old) and Fe (in age group of 20-40 years old) in hair than the female people. Smokers had significantly (p < 0.05) higher level of Cd (0.35 μg/g) but lower level of Zn (101.24 µg/g) than non-smokers (Cd: 0.17 μg/g; Zn: 252.63 µg/g). Hg and Pb contents in hair of Shenzhen people were positively related with the frequencies of seafood consumption and the age, respectively. Moreover, residents lived in private buildings (well decorated house) accumulated significantly higher (p < 0.05) levels of Pb, Cr, Fe and Ni as compared with those lived in public rental house and village house (no decoration or simple decoration), suggesting that decoration material was also an important way for human exposure to heavy metals.