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.

Comparison of Gut Microbiome in Human Colorectal Cancer in Paired Tumor and Adjacent Normal Tissues.

BACKGROUND: To understand the biological effect of gut microbiome on the progression of colorectal cancer (CRC), we sequenced the V3-V4 region of the 16S rRNA gene to illustrate the overall structure of microbiota in the CRC patients. METHODS: In this study, a total of 66 CRC patients were dichotomized into different groups based on the following characteristics: paired tumor and adjacent normal tissues, distal and proximal CRC segments, MMR (-) and MMR (+), different TNM staging and clinic tumor staging. RESULTS: By sequencing and comparing the microbial assemblages, our results indicated that 7 microbe genus (Fusobacterium, Faecalibacterium, Akkermansia, Ruminococcus2, Parabacteroides, Streptococcus, and f_Ruminococcaceae) were significantly different between tumor and adjacent normal tissues; and 5 microbe genus (Bacteroides, Fusobacterium, Faecalibacterium, Parabacteroides, and Ruminococcus2) were significantly different between distal and proximal CRC segments; only 2 microbe genus (f_Enterobacteriaceae and Granulicatella) were significantly different between MMR (-) and MMR (+); but there was no significant microbial difference were detected neither in the TNM staging nor in the clinic tumor staging. CONCLUSION: All these findings implied a better understanding of the alteration in the gut microbiome, which may offer new insight into diagnosing and therapying for CRC patients.

Ultrasound-assisted synthesis of pyrroles catalyzed by zirconium chloride under solvent-free conditions.

A straightforward synthesis of substituted pyrroles using zirconium chloride-catalyzed modified Paal-Knorr method has been accomplished under ultrasound irradiation. Compared to known methods, this new method provides as easy access to various substituted pyrroles in good to excellent yields with short reaction times.