Establishing a risk stratification model to identify clinically high-risk N0 breast cancer who could benefit from regional nodal irradiation: a single institute analysis.

BACKGROUND

The purpose of this real-world study was to investigate the risk factors for developing recurrence among patients with pathological T1-3N0 breast cancer (BC) treated with breast-conserving surgery (BCS) followed by whole breast irradiation alone (WBI) and identify those clinically high-risk BCs who could benefit from regional nodal irradiation (RNI).

MATERIALS AND METHODS

Female BC patients treated at Shanghai Ruijin hospital from 2009 to 2016 were retrospectively reviewed. The disease-free survival (DFS), breast cancer specific survival (BCSS) and overall survival (OS) were estimated by the Kaplan-Meier method, and survival differences were compared with the log-rank test. Univariate and multivariate analysis was performed using Cox proportional hazards regression analysis. An external validation was conducted by using SEER database.

RESULTS

A total of 622 BC patients treated with BCS+WBI alone were included. With a median follow-up of 82 months, the 7-year OS, BCSS and DFS for the entire cohort was 97%, 99% and 91%, respectively. Multivariable Cox analysis indicated that tumor size (=0.006), tumor location (=0.033), lymphovascular invasion (LVI) status (=0.0028) and Ki-67 index (=0.051) were independent risk factors for DFS. A scoring system was developed using these four factors and the 7-year DFS and OS were 97% and 96% for patients with 0-1 risk factors, 95% and 82% for patients with ≥2 risk factors (<0.0001 for DFS, and =0.0063 for OS). Based on tumor size and tumor location, an external validation by demonstrated that the 7-year OS was 90% and 88% for patients with 0-1 risk factor, which was significantly better than those defined as high-risk BC patients (82%, <0.0001).

CONCLUSION

By using our institute database, we establish a risk stratification system for identifying sub-group of pN0 BC patients, who are at high risk for developing recurrence. The results of our study support tailored RT decision-making according to individual risks, which needed to be confirmed in further studies.