A clinical nomogram incorporating salivary level and oral hygiene index for predicting colorectal cancer.

Background: Emerging evidence demonstrates that the salivary microbiome could serve as a biomarker for various diseases. To date, the oral microbiome's role in the diagnosis of colorectal cancer (CRC) has not been fully elucidated. We aimed to illustrate the salivary microbiome's role in diagnosing and predicting the risk of CRC.

Methods: We collected preoperational saliva from 237 patients [95 healthy controls (HCs) and 142 CRC patients] who underwent surgical resections or colorectal endoscopy in Renji Hospital from January 2018 to January 2020. Clinical demographics, comorbidities, and oral health conditions were obtained from medical records or questionnaires. Salivary microbial biomarkers were detected using quantitative polymerase chain reaction (qPCR) after DNA extraction. Multivariate logistic regression analysis was employed to analyze the risk factors for CRC. A predictive model for the risk of developing CRC was constructed based on logistic regression analysis. Predictive accuracy was internally validated by bootstrap resampling. A clinical nomogram was constructed to visualize the predictive model.

Results: Logistic regression analysis demonstrated that the risk factors associated with CRC included age at diagnosis, male sex, poor oral hygiene, and relative salivary abundance. The predictive model had good discriminative (0.866) and calibration abilities (0.834) after bias correction.

Conclusions: The model based on age, sex, oral hygiene index (OHI), and the salivary level, which is visualized by a clinical nomogram, can predict the risk of CRC. Developing good oral hygiene habits might reduce the risk of CRC.