Related Experiment Video
Updated: Jun 25, 2025
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and Validation of a Prognostic Nomogram for HR+ HER- Breast Cancer
Jie-Yu Zhou1, Cheng-Geng Pan1, Yang Ye1
1Department of Thyroid and Breast Surgery, The Wenzhou Central Hospital, Wenzhou, Zhejiang, 325000, People's Republic of China.
Purpose:
We aimed to develop a nomogram to predict prognosis of HR+ HER2- breast cancer patients and guide the application of postoperative adjuvant chemotherapy.
Methods:
We identified 310 eligible HR+ HER- breast cancer patients and randomly divided the database into a training group and a validation group. The endpoint was disease free survival (DFS). Concordance index (C-index), area under the curve (AUC) and calibration curves were used to evaluate predictive accuracy and discriminative ability of the nomogram. We also compared the predictive accuracy and discriminative ability of our nomogram with the eighth AJCC staging system using overall data.
Results:
According to the training group, platelet-to-lymphocyte ratio (PLR), tumor size, positive lymph nodes and Ki-67 index were used to construct the nomogram of DFS. The C-index of DFS was 0.708 (95% CI: 0.623-0.793) in the training group and 0.67 (95% CI: 0.544-0.796) in the validation group. The calibration curves revealed great consistencies in both groups.
Conclusion:
We have developed and validated a novel and practical nomogram that can provide individual prediction of DFS for patients with HR+ HER- breast cancer. This nomogram may help clinicians in risk consulting and guiding the application of postoperative adjuvant chemotherapy.
