Training and validation of a nomogram for predicting synchronous distant organ metastasis in patients with very-early-onset colorectal cancer.

[BACKGROUND] Colorectal cancer (CRC) ranks among the leading causes of cancer-related mortality, with a sharp rise in incidence among patients diagnosed before age 40, a group classified as having very-early-onset CRC (VEO-CRC). Because synchronous distant organ metastasis (DOM) at diagnosis is common and worsens survival, this study aimed to identify predictors of DOM, develop and internally validate a nomogram to estimate individual DOM risk, and evaluate its potential clinical utility.

[METHODS] Utilizing data from the Surveillance, Epidemiology, and End Results (SEER) database spanning 2010 to 2020, we identified patients diagnosed with malignant colorectal adenocarcinoma under 40 years. Patients who met the inclusion criteria were randomly assigned to the training set and the validation set. Logistic regression analyses were performed to identify risk factors for DOM, which were subsequently used to construct a nomogram. The model's performance was assessed through receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA).

[RESULTS] A total of 8,097 VEO-CRC patients were assigned to training (n=5,667) and validation (n=2,430) cohorts. DOM among patients with malignant colorectal adenocarcinoma under 40 years was 23.04%. Multivariate analysis revealed seven independent risk factors for DOM: race, tumor size, primary tumor location, histopathological grade, tumor (T) stage, node (N) stage, and carcinoembryonic antigen (CEA) level. The nomogram demonstrated an area under the curve (AUC) of 0.846 [95% confidence interval (CI): 0.834-0.858] for the training cohort and 0.833 (95% CI: 0.813-0.852) for the validation cohort, indicating strong predictive accuracy. The clinical utility of the nomogram was verified in the DCA.

[CONCLUSIONS] The predictive nomogram, derived from demographic, clinical, and pathological data from the SEER database, provides an estimation of the DOM risk in VEO-CRC patients. This is a promising tool to improve outcomes for young patients by assisting physicians in early risk stratification and bespoke treatment planning. At prespecified risk thresholds, the predicted probabilities may assist early risk stratification and inform imaging and follow-up decisions, though their clinical application will require confirmation through rigorous external validation.