Related Experiment Video
Updated: May 2, 2026
Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Development and validation of a CT-based radiomics nomogram for predicting overall survival in primary tracheal
Shuchao Wang1, Yu Zhang2, Zhongfeng Xie1
1Department of Radiology, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China.
Objectives:
Primary tracheal malignancies (PTMs) are rare and histologically diverse, leading to complex and contentious prognostic factors. Consequently, accurately predicting the survival outcomes of these patients is challenging. This study aimed to develop a radiomics-based prognostic model for individual prediction of survival risk in PTM patients.
Methods:
A total of 115 patients with PTM were reviewed retrospectively and divided into the training cohort (n = 85) and validation cohort (n = 30). Radiomics features associated with overall survival (OS) were selected using the least absolute shrinkage and selection operator (LASSO) method and combined to form the radiomics score (Radscore). Multivariable analyses were used to identify clinical and CT features as independent risk factors for OS. Radscore and identified risk factors were combined to construct a radiomics nomogram. The predictive efficacy and clinical net benefit of the prognostic models were assessed using the C-index and decision curve analysis (DCA).
Results:
Seven radiomics features were selected by LASSO to form a Radscore. Longitudinal length was identified as an independent prognostic factor for OS. Compared with longitudinal length (C-index: 0.59; 95% confidence interval [CI]: 0.47-0.70), both the Radscore (C-index: 0.75; 95% CI, 0.63-0.87) and nomogram (C-index: 0.79; 95% CI, 0.69-0.88) demonstrated better predictive performance and were confirmed in the validation cohort. In addition, DCA indicated that both the Radscore and nomogram provided favorable clinical net benefits.
Conclusions:
The CT-based nomogram, which combined Radscore and longitudinal length, could individually predict the survival outcomes of PTM patients, aiding clinical decision-making.
