Risk stratification in colorectal cancer: A retrospective cohort study of nomograms based on inflammatory and...

ObjectiveInflammation and immunohematological biomarkers are recognized as contributing factors in the progression of solid tumors. This study aimed to develop nomograms incorporating inflammatory and immunohematological biomarkers to predict the prognosis of colorectal cancer.MethodsWe retrospectively enrolled 432 patients with colorectal cancer at Yunnan Cancer Hospital from January 2019 to December 2022. Clinicopathologic data and blood samples were obtained at initial diagnosis before any treatment, and therapy was initiated within 3 days. Patients with prior therapy, secondary cancers, or systemic conditions affecting hematology were excluded. Metastases were confirmed by pathology or imaging, and overall survival and progression-free survival were recorded through follow-up. Multivariate logistic and Cox regression analyses, nomogram construction, and internal validation with 1000-bootstrap resampling were performed using R, with risk groups defined by receiver operating characteristic curve-derived cutoffs.ResultsIn the training cohort, the model accuracy for predicting distant metastasis was 66.25%. The concordance index values for the three nomograms were 0.791 (95% confidence interval, 0.745-0.838), 0.752 (95% confidence interval, 0.699-0.806), and 0.687 (95% confidence interval, 0.647-0.726), respectively. Calibration plots showed strong agreement between predicted and observed outcomes, while decision curve analysis indicated potential clinical utility. Subgroup analyses confirmed that the nomograms were effective prognostic indicators across stage I-IV colorectal cancer patients (P < 0.05).ConclusionSingle or combined hematological indicators are readily obtainable and feasible and possess high prognostic value. Nomograms based on cancer-associated inflammatory factors and immunohematological biomarkers demonstrated robust accuracy in predicting distant metastasis, overall survival, and progression-free survival in patients with colorectal cancer. These tools may assist clinicians in risk stratification and treatment decision-making, ultimately supporting improved oncological outcomes.