Overall Survival and Prognostic Factors in De Novo Metastatic Human Epidermal Growth Factor Receptor (HER)-2-Positive...

Background: About 15-20% of breast cancers are HER2 positive. Approximately 15-24% of individuals with localized HER2-positive cancer develop metastatic disease after curative treatment, while 3-10% present with de novo metastasis. Survival has significantly improved with various anti-HER2 agents, but there is considerable heterogeneity at the individual level. Our study aims to identify factors influencing survival in de novo metastatic HER2-positive breast cancer using a large sample from the National Cancer Database (NCDB). Methods: Women with metastatic HER2-positive breast cancer diagnosed from 2010 to 2020 in the NCDB were included. Demographic, clinicopathological, treatment data, and overall survival (OS) were collected. Kaplan-Meier curves estimated OS. The log-rank test identified OS differences between groups in univariate analysis. The Cox proportional hazard model with backward elimination identified factors affecting OS in multivariate analysis. The 12-month, 36-month, and 60-month survival estimates, 95% confidence intervals (CIs), and adjusted hazard ratios were reported. Results: Among 5376 women with metastatic HER2-positive breast cancer from 2010 to 2020, the median OS was 55.95 months (95% CI 53.55-NE). Multivariate analysis identified age, Charlson-Deyo comorbidity score, histology, HER2 IHC expression, hormone receptor status, the number of metastatic sites, metastasis location, first-line chemotherapy, anti-HER2 therapy, hormone-blocking therapy, surgery at primary/non-primary sites, and palliative treatment as significant factors affecting OS. Race and radiation receipt were not significant. Conclusions: This is the largest analysis of overall survival estimates in de novo metastatic HER2-positive breast cancer to date in the real-world setting. We identified several independent prognostic factors influencing OS in this population. These findings will help individualize prognostication at diagnosis, optimize treatment strategies, and facilitate patient stratification in future trials.