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Updated: May 22, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Personalized survival prediction in young Asian American breast cancer
Fei Xu1, Zhi-Li Chen2, Yu-Ling Zhang3
1Department of Radiation Oncology, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, China.
Background:
Young Asian American women with breast cancer present unique prognostic challenges, yet predictive tools specifically designed for this population are lacking. This study aimed to develop and validate a comprehensive nomogram to predict overall survival (OS) in young Asian American breast cancer patients.
Methods:
Using the Surveillance, Epidemiology, and End Results (SEER) database [2000-2021], we included 3,172 Asian American breast cancer patients aged ≤40 years from an initial population of 109,317 cases. The cohort was randomly divided into training (n=2,224) and validation (n=948) sets. A nomogram incorporating clinicopathological factors was developed using multivariate Cox regression analysis.
Results:
Integrating T stage, N stage, molecular subtype, and surgical approach, the nomogram demonstrated reasonable predictive capability for OS [concordance index (C-index) =0.759; 95% confidence interval (CI): 0.719-0.799], surpassing that of the conventional staging system (C-index =0.736; 95% CI: 0.678-0.793). The findings underwent internal validation within a split-sample cohort.
Conclusions:
We developed and validated the novel prognostic nomogram specifically designed for young Asian American breast cancer patients. This tool shows reasonable predictive performance and facilitates personalized treatment planning and risk stratification in this unique population. As our model was evaluated using internal split-sample validation, future true external validation in distinct clinical cohorts is warranted to confirm its generalizability.
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