Construction and validation of a nomogram model for predicting the overall survival of colorectal cancer patients.

Background: Colorectal cancer (CRC) is a frequent cancer worldwide with varied survival outcomes.

Objective: We aimed to develop a nomogram model to predict the overall survival (OS) of CRC patients after surgery.

Design: This is a retrospective study.

Setting: This study was conducted from 2015 to 2016 in a single tertiary center for CRC.

Patients: CRC patients who underwent surgery between 2015 and 2016 were enrolled and randomly assigned into the training (n = 480) and validation (n = 206) groups. The risk score of each subject was calculated based on the nomogram. All participants were categorized into two subgroups according to the median value of the score.

Main Outcome Measures: The clinical characteristics of all patients were collected, significant prognostic variables were determined by univariate analysis. Least absolute shrinkage and selection operator (LASSO) regression was applied for variable selection. The tuning parameter (λ) for LASSO regression was determined by cross-validation. Independent prognostic variables determined by multivariable analysis were used to establish the nomogram. The predictive capacity of the model was assessed by risk group stratification.

Results: Infiltration depth, macroscopic classification, BRAF, carbohydrate antigen 19 - 9 (CA-199) levels, N stage, M stage, TNM stage, carcinoembryonic antigen levels, number of positive lymph nodes, vascular tumor thrombus, and lymph node metastasis were independent prognostic factors. The nomogram established based on these factors exhibited good discriminatory capacity. The concordance indices for the training and validation groups were 0.796 and 0.786, respectively. The calibration curve suggested favorable agreement between predictions and observations. Moreover, the OS of different risk subgroups was significantly different.

Limitations: The limitations of this work included small sample size and single-center design. Also, some prognostic factors could not be included due to the retrospective design.

Conclusions: A prognostic nomogram for predicting the OS of CRC patients after surgery was developed, which might be helpful for evaluating the prognosis of CRC patients.