Validation study of a nomogram for predicting probability of low risk of MammaPrint results in women with clinically high-risk breast cancer

Background MammaPrint (MMP) helps clinicians identify the ideal time for adjuvant treatment for patients with early HR+/HER2- breast cancer. We aimed to validate a nomogram designed to predict probability of low risk of MMP results and to evaluate the difference in survival outcome between two groups divided by nomogram score.Methods In this retrospective cohort study, we evaluated 172 patients from Asan Medical Center, Seoul, Korea, who underwent breast cancer surgery and MMP during 2020-2021. First, we validated the nomogram by calculating the area under the curve (AUC) and using calibration. Additionally, with the data of 1,835 T1-3N0-1M0 HR+/HER2- patients from Asan Medical Center during 2010-2013, we compared the disease-free survival (DFS), overall survival (OS), and breast cancer-specific survival (BCSS) rates by Kaplan-Meier analysis between the two groups divided by nomogram total point (TP) of 183.Results The AUC calculated by validation of 172 patients was 0.73 (95% confidence interval [CI], 0.66-0.81). The discrimination and calibration of the prediction model were satisfactory following additional validation of 1835 patients. The high-risk and low-risk groups had different 5-year OS (97.9% vs. 98.1%, p = 0.056), DFS (98.6% vs. 99.4%, p = 0.008), and BCSS rates (98.6% vs. 99.4%, p = 0.002).Conclusion For treatment decision-making among clinically high-risk patients with HR+/HER2- and node-positive disease, the nomogram showed satisfactory performance in predicting patients with low genomic risk. Survival outcome significantly differed between two groups divided by nomogram TP. More studies are needed to validate this model in international cohorts and large prospective cohorts from other institutions.

Automated summary

This study aimed to validate a nomogram for predicting low-risk patients and evaluate the difference in survival outcomes between different nomogram scores. The findings showed satisfactory performance of the nomogram in predicting low genomic risk patients and significant differences in survival outcomes based on nomogram scores. Further studies are needed to validate the model in international cohorts and large prospective cohorts from other institutions.