# Prognostic nomogram in patients with right-sided colon cancer after colectomy: a surveillance, epidemiology, and end results–based study

## TL;DR

This study created a new tool to predict survival in right-sided colon cancer patients after surgery, which is more accurate than the standard staging system.

## Contribution

A novel nomogram for predicting survival in right-sided colon cancer patients that outperforms the TNM staging system.

## Key findings

- The nomogram showed strong discriminative ability with C-index values of 0.851 in training and 0.860 in internal validation.
- The model was externally validated with a C-index of 0.834 and demonstrated high consistency in survival predictions.
- Decision Curve Analysis confirmed the nomogram's superior net benefit over the TNM staging system.

## Abstract

This study aimed to develop and validate a nomogram for predicting overall survival (OS) in patients undergoing surgery for right-sided colon cancer (RCC).

We collected 25,203 patients with RCC from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided them into 7:3 training and internal validation set. Utilizing the Cox proportional hazards regression model, we constructed a nomogram based on prognostic risk factors. Furthermore, for external validation, we retrospectively followed up with 228 patients from Jiaxing First Hospital and assessed and calibrated the nomogram using the C-index and calibration curves.

After identifying independent prognostic factors through univariate and multivariate analyses, a nomogram was developed. The c-index values of this nomogram differed as follows: 0.851 (95% CI: 0.845-0.857) in the training set, 0.860 (95% CI: 0.850-0.870) in the internal validation set, and 0.834 (95% CI: 0.780-0.888) in the external validation set, indicating the model’s strong discriminative ability. Calibration curves for 1-year, 3-year, and 5-year overall survival (OS) probabilities exhibited a high level of consistency between predicted and actual survival rates. Furthermore, Decision Curve Analysis (DCA) demonstrated that the new model consistently outperformed the TNM staging system in terms of net benefit.

We developed and validated a survival prediction model for patients with RCC. This novel nomogram outperforms the traditional TNM staging system and can guide clinical practitioners in making optimal clinical decisions.