Development and validation of a tongue image-clinical nomogram for detection of advanced colorectal adenoma

Abstract

BACKGROUND

Colorectal cancer largely arises from advanced adenomas (AA), yet current noninvasive risk stratification tools, including the Asia-Pacific colorectal screening (APCS) score, exhibit limited discriminatory ability, particularly for AA detection. Traditional Chinese medicine tongue diagnosis, supported by emerging evidence of the oral-gut axis and microbial translocation, offers a potential noninvasive phenotypic marker. Computerized tongue image analysis enables objective quantification of tongue features. We hypothesized that a nomogram integrating quantitative tongue-image characteristics with clinical risk factors would improve AA detection beyond established APCS-based risk scores.

AIM

To develop and validate a tongue image-clinical nomogram for AA detection and compare it with conventional risk scores.

METHODS

This prospective observational study randomly divided 880 adults into training and validation cohorts (7:3). Quantitative tongue phenotypes were extracted via deep learning from standardized images. Univariate analysis, least absolute shrinkage and selection operator regression, and multivariate analysis established the nomogram. Calibration curves, the area under the receiver operating characteristic curve (AUC), and decision curve analysis assessed discrimination, accuracy, and clinical utility. Additionally, fixed-specificity classification was applied within the high-risk (APCS score ≥ 4) subgroup.

RESULTS

In the training cohort (n = 616; 226 AA), the nomogram achieved an AUC of 0.739, significantly superior to the tongue-only model (0.694), APCS score (0.663), and modified APCS (M-APCS) score (0.658) (all P < 0.002). In the validation cohort (n = 264; 92 AA), the nomogram maintained an AUC of 0.711, exceeding conventional scores (AUC: 0.640-0.654). Within the high-risk subgroup (APCS score ≥ 4; n = 213), the nomogram retained moderate discrimination (AUC: 0.75-0.76) and performance comparable to the tongue-only model, whereas conventional scores approached chance levels (AUC: 0.52-0.57). Using cutoffs targeting approximately 80% specificity in the high-risk validation subset, the nomogram detected 58.33% of AA vs 19.44% for APCS score and 25.00% for M-APCS score.

CONCLUSION

The tongue image-clinical nomogram may complement conventional scores for noninvasive AA risk refinement, especially in APCS-defined high-risk individuals.

Keywords: Advanced adenoma; Colorectal cancer screening; Tongue imaging; Predictive model; Nomogram; Opportunistic screening

Core Tip: This study developed and internally validated a noninvasive nomogram integrating quantitative tongue phenotypes with clinical factors for advanced adenoma detection. In the validation cohort, the nomogram showed higher discrimination than the Asia-Pacific colorectal screening (APCS) and modified APCS scores. In the high-risk subgroup (APCS ≥ 4), where conventional scores had limited discriminative value, the nomogram maintained moderate performance and detected 2-3 times as many advanced adenomas as the conventional scores did at approximately 80% specificity, suggesting potential as a noninvasive risk-refinement tool for opportunistic screening.