Development and validation of a nomogram prediction model for overall survival in patients with rectal cancer

Rectal cancer is prevalent and associated with substantial morbidity and mortality.

To develop a nomogram prediction model for overall survival (OS) in patients with rectal cancer by leveraging a comprehensive analysis of demographic, clinicopathological, haematological, and follow-up data to identify independent prognostic factors.

We conducted a prospective cohort study in China involving rectal cancer patients and applied Cox regression and least absolute shrinkage and selection operator regression to assess the significance of various variables as independent prognostic factors for OS. The identified factors were integrated into a nomogram model, which was evaluated for predictive accuracy via the C-index, area under the curve (AUC), calibration curve, and decision curve analysis (DCA).

Multivariate analysis revealed independent predictors of OS, including the Karnofsky performance status, age, sex, TNM stage, chemotherapy, surgery, targeted therapy, β2-microglobulin, lactate dehydrogenase, and the neutrophil-to-lymphocyte ratio. The nomogram demonstrated a C-index of 0.80 for the training and validation cohorts, with AUC values indicating high predictive accuracy for 1-year, 3-year, and 5-year OS. The calibration curves confirmed the model's excellent agreement with the observed survival rates, and DCA revealed the superior clinical utility of the nomogram over the TNM staging system.

In this study, a novel prognostic model that accurately predicts the OS of rectal cancer patients was developed. The model exhibited excellent discriminatory and calibration capabilities, thus offering a reliable tool for health care professionals to estimate patient survival.