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Updated: Jul 14, 2025
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and validation of a nomogram to predict lung metastasis in patients with testicular germ cell tumors
Sheng Li1,2, Situ Xiong1,2, Lin Yang1,2
1Department of Urology, First Affiliated Hospital of Nanchang University, Nanchang, 330000, China.
Background:
Lung metastatic tumor (LM) is one of testicular germ cell tumors' most common metastatic sites. Our study aimed to develop a nomogram for predicting the risk of LM among patients with testicular germ cell tumors (TGCTs).
Methods:
Clinicopathological information of 4078 patients with TGCT between 2010 and 2015 was obtained from SEER. Univariate and multivariate logistic regression analyses were performed to identify risk factors for LM, and a nomogram was developed based on these factors. Calibration curves, area under the receiver operating curve (AUC), and decision curve analysis (DCA) were used to evaluate the accuracy and discrimination of the model.
Results:
Study participants included 4078 people with TGCTs, including 305 people with LM. They were randomly divided into two groups (training cohort = 2854 and validation cohort = 1224) at a ratio of 7:3. The following variables were incorporated in the nomogram: marital status, tumor histological type, T stage, brain metastasis, liver metastasis, lactate dehydrogenase (LDH), and chemotherapy. Besides, the AUC of it was 0.922 in the training cohort, while was 0.930 in the validation cohort. Training and validation cohort calibrations showed that the nomogram had excellent predictive abilities. DCA suggested it was more clinically relevant than the traditional TN staging.
Conclusion:
We have established a nomogram to predict the risk of LM in patients with TGCTs. Doctors and patients can use this nomogram to monitor and identify lung metastasis of tumors through active monitoring and follow-up.
