Development and validation of a risk prediction model for post-polypectomy colorectal cancer in the USA: a prospective cohort study

Health-promoting lifestyle among Chinese patients with colorectal polyps: a cross-sectional study

This study aims to investigate the level of health-promoting lifestyles and its influencing factors in Chinese patients with colorectal polyps. A total of 169 colorectal polyps patients from three tertiary care hospitals in Nanchong and Deyang, China, were recruited. Data were collected using the Impact of Health-Promoting Lifestyle Profile-II (HPLP-IIR), Colorectal Cancer Knowledge Questionnaire, Colorectal Cancer Health Belief Scale, the Chinese version of the Health Information Literacy Self-Rating Scale, and a demographic questionnaire. Factors influencing health-promoting lifestyles in patients with colorectal polyps were analyzed using multiple linear regression analysis. The mean HPLP-IIR score was 96.02 ± 14.42, indicating a moderate level of health promotion. Multiple linear regression analysis revealed that the total score of health information literacy, colorectal cancer knowledge and health beliefs were significantly associated with the total score of health promotion lifestyle in Chinese patients with colorectal polyps (P < 0.001), explaining 36.1% of the total variance. The health-promoting lifestyle of colorectal polyp patients was at an intermediate level. Health information literacy, colorectal cancer health knowledge, and colorectal cancer health beliefs were identified as key factors influencing their health-promoting lifestyles. Efforts should focus on improving health information literacy, increasing colorectal cancer health knowledge, and promoting positive health beliefs to establish a better health-promoting lifestyle.

Construction and validation of machine learning-based predictive model for colorectal polyp recurrence one year after endoscopic mucosal resection

BACKGROUND

Colorectal polyps are precancerous diseases of colorectal cancer. Early detection and resection of colorectal polyps can effectively reduce the mortality of colorectal cancer. Endoscopic mucosal resection (EMR) is a common polypectomy procedure in clinical practice, but it has a high postoperative recurrence rate. Currently, there is no predictive model for the recurrence of colorectal polyps after EMR.

AIM

To construct and validate a machine learning (ML) model for predicting the risk of colorectal polyp recurrence one year after EMR.

METHODS

This study retrospectively collected data from 1694 patients at three medical centers in Xuzhou. Additionally, a total of 166 patients were collected to form a prospective validation set. Feature variable screening was conducted using univariate and multivariate logistic regression analyses, and five ML algorithms were used to construct the predictive models. The optimal models were evaluated based on different performance metrics. Decision curve analysis (DCA) and SHapley Additive exPlanation (SHAP) analysis were performed to assess clinical applicability and predictor importance.

RESULTS

Multivariate logistic regression analysis identified 8 independent risk factors for colorectal polyp recurrence one year after EMR (P < 0.05). Among the models, eXtreme Gradient Boosting (XGBoost) demonstrated the highest area under the curve (AUC) in the training set, internal validation set, and prospective validation set, with AUCs of 0.909 (95%CI: 0.89-0.92), 0.921 (95%CI: 0.90-0.94), and 0.963 (95%CI: 0.94-0.99), respectively. DCA indicated favorable clinical utility for the XGBoost model. SHAP analysis identified smoking history, family history, and age as the top three most important predictors in the model.

CONCLUSION

The XGBoost model has the best predictive performance and can assist clinicians in providing individualized colonoscopy follow-up recommendations.

Systematic review: risk prediction models for metachronous advanced colorectal neoplasia after polypectomy

BACKGROUND AND AIM

Colorectal cancer (CRC) is the fourth leading cause of cancer death globally. CRC surveillance is a common indication for colonoscopy, representing a considerable burden for endoscopy services. Accurate identification of high-risk patients who would benefit from more intensive surveillance, as well as low-risk patients suitable for less frequent follow-up, could improve the effectiveness of surveillance protocols and resource use. Our aim was to identify and critically appraise published risk models for the occurrence of metachronous advanced colorectal neoplasia (ACN), defined here as CRC or advanced adenomas detected during surveillance colonoscopy.

METHODS

We searched PubMed and EMBASE for primary research studies reporting the development and/or validation of multivariable models that predict metachronous ACN risk. Screening of studies for inclusion, data extraction, and risk of bias assessment were conducted by two researchers independently.

RESULTS

We identified nine studies describing nine risk models. Six models were internally validated and two were externally validated. No model underwent both internal and external validation. Good model discrimination (concordance index > 0.7) was reported for two models during internal validation and for one model during external validation. Calibration was acceptable when assessed (n = 4). Methodological limitations and a high risk of bias were observed for all studies.

CONCLUSIONS

Several published models predicting metachronous ACN risk showed some promise. However, adherence to methodological standards was limited, and only two models were externally validated. Head-to-head comparisons of existing models using populations independent from model development cohorts should be prioritized to identify models suitable for use in clinical practice.

Identification and validation of Rab GTPases RAB13 as biomarkers for peritoneal metastasis and immune cell infiltration in colorectal cancer patients

Background

As one of the most common cancer, colorectal cancer (CRC) is with high morbidity and mortality. Peritoneal metastasis (PM) is a fatal state of CRC, and few patients may benefit from traditional therapies. There is a complex interaction between PM and immune cell infiltration. Therefore, we aimed to determine biomarkers associated with colorectal cancer peritoneal metastasis (CRCPM) and their relationship with immune cell infiltration.

Methods

By informatic analysis, differently expressed genes (DEGs) were selected and hub genes were screened out. RAB13, one of the hub genes, was identificated from public databases and validated in CRC tissues. The ESTIMATE, CEBERSORT and TIMER algorithms were applied to analyze the correlation between RAB13 and immune infiltration in CRC. RAB13's expression in different cells were analyzed at the single-cell level in scRNA-Seq. The Gene Set Enrichment Analysis (GSEA) was performed for RAB13 enrichment and further confirmed. Using oncoPredict algorithm, RAB13's impact on drug sensitivity was evaluated.

Results

High RAB13 expression was identified in public databases and led to a poor prognosis. RAB13 was found to be positively correlated with the macrophages and other immune cells infiltration and from scRNA-Seq, RAB13 was found to be located in CRC cells and macrophages. GSEA revealed that high RAB13 expression enriched in a various of biological signaling, and oncoPredict algorithm showed that RAB13 expression was correlated with paclitaxel sensitivity.

Conclusion

Our study indicated clinical role of RAB13 in CRC-PM, suggesting its potential as a therapeutic target in the future.

Gut microbiome: decision-makers in the microenvironment of colorectal cancer

Colorectal cancer (CRC) is a common malignancy of the gastrointestinal tract, accounting for the second most common cause of gastrointestinal tumors. As one of the intestinal barriers, gut bacteria form biofilm, participate in intestinal work, and form the living environment of intestinal cells. Metagenomic next-generation sequencing (mNGS) of the gut bacteria in a large number of CRC patients has been established, enabling specific microbial signatures to be associated with colorectal adenomato-carcinoma. Gut bacteria are involved in both benign precursor lesions (polyps), in situ growth and metastasis of CRC. Therefore, the term tumorigenic bacteria was proposed in 2018, such as Escherichia coli, Fusobacterium nucleatum, enterotoxigenic Bacteroides fragilis, etc. Meanwhile, bacteria toxins (such as cytolethal distending toxin (CDT), Colibactin (Clb), B. fragilis toxin) affect the tumor microenvironment and promote cancer occurrence and tumor immune escape. It is important to note that there are differences in the bacteria of different types of CRC. In this paper, the role of tumorigenic bacteria in the polyp-cancer transformation and the effects of their secreted toxins on the tumor microenvironment will be discussed, thereby further exploring new ideas for the prevention and treatment of CRC.