A Novel Prognostic Nomogram for Predicting Survival of Hormone Receptor-Positive and HER2 Negative Advanced Breast Cancer Among the Han-Population - Zhu, Yimin; Wang, Jiayu; Xu, Binghe (Frontiers in Oncology, 2022)
Purpose: We developed a nomogram model to predict overall survival in HR+/Her- subtype advanced breast cancer. Methods: A total of 3577 ABC (advanced breast cancer) patients from 21 hospitals in China was involved in this study from January 2012 to December 2014. 1671 HR+/HER2- ABC patients were extracted from all ABC patients and enrolled in our study. A nomogram was built based on univariable and multivariable Cox regression analyses, identifying independent predictors. The discriminatory and predictive capacities of the nomogram were assessed using ROC (receiver operating characteristic) curve and calibration plots. Results: Univariable and multivariable analysis found that ER (estrogen receptor) status, MFI (metastatic-free interval), First-line therapy option, Number of metastatic sites, Whether choose local therapy to metastatic sites were significantly related to overall survival (all P < 0.05). These variables were incorporated into a nomogram to predict the 2- year, 3-year, and 5-year OS (overall survival) of ABC patients. The AUC (the area under the curve) of the nomogram was 0.748 (95% CI (confidence interval):0.693-0.804) for 5-year OS in the training Cohort and 0.732 (95% CI: 0.676-0.789) for the validation Cohort. The calibration curves revealed good consistency between actual survival and nomogram prediction in the training and validation cohorts. Additionally, the nomogram showed an excellent ability to stratify patients into different risk cohorts. Conclusion: We established a nomogram that provided a more straightforward predictive model for HR+/HER2- ABC subtype patients' future outcomes and to some extent assisted physicians in making the personalized therapeutic option.