Related Experiment Video
Updated: Jun 9, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Prognostic nomograms for young breast cancer: A retrospective study based on the SEER and METABRIC databases
Yongxin Li1, Xinlong Tao1, Yinyin Ye1
1Breast Disease Diagnosis and Treatment Center of Affiliated Hospital of Qinghai University & Affiliated Cancer Hospital of Qinghai University Xining Qinghai China.
Background:
Young breast cancer (YBC) is a subset of breast cancer that is often more aggressive, but less is known about its prognosis. In this study, we aimed to generate nomograms to predict the overall survival (OS) and breast cancer-specific survival (BCSS) of YBC patients.
Methods:
Data of women diagnosed with YBC between 2010 and 2020 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The patients were randomly allocated into a training cohort (n = 15,227) and internal validation cohort (n = 6,526) at a 7:3 ratio. With the Cox regression models, significant prognostic factors were identified and used to construct 3-, 5-, and 10-year nomograms of OS and BCSS. Data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database were used as an external validation cohort (n = 90).
Results:
We constructed nomograms incorporating 10 prognostic factors for OS and BCSS. These nomograms demonstrated strong predictive accuracy for OS and BCSS in the training cohort, with C-indexes of 0.806 and 0.813, respectively. The calibration curves verified that the nomograms have good prediction accuracy. Decision curve analysis demonstrated their practical clinical value for predicting YBC patient survival rates. Additionally, we provided dynamic nomograms to improve the operability of the results. The risk stratification ability assessment also showed that the OS and BCSS rates of the low-risk group were significantly better than those of the high-risk group.
Conclusions:
Here, we generated and validated more comprehensive and accurate OS and BCSS nomograms than models previously developed for YBC. These nomograms can help clinicians evaluate patient prognosis and make clinical decisions.
More Related Videos
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
07:41Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Related Concept Videos
Cancer Survival Analysis
Kaplan-Meier Approach