Treatment response as predictor for brain metastasis in triple negative breast cancer: A score-based model

Abstract

Background: Triple negative breast cancer (TNBC) has worse prognosis than other subtypes of breast cancer, and many patients develop brain metastasis (BM). We developed a simple predictive model to stratify the risk of BM in TNBC patients receiving neo-adjuvant chemotherapy (NAC), surgery, and radiation therapy (RT).

Methods: Patients with TNBC who received NAC, surgery, and RT were included. Cox proportional hazards method was used to evaluate factors associated with BM. Significant factors predictive for BM on multivariate analysis (MVA) were used to develop a risk score. Patients were divided into three risk groups: low, intermediate, and high. A receiver operating characteristic (ROC) curve was drawn to evaluate the value of the risk group in predicting BM. This predictive model was externally validated.

Results: A total of 160 patients were included. The median follow-up was 47.4 months. The median age at diagnosis was 49.9 years. The 2-year freedom from BM was 90.5%. Persistent lymph node positivity, HR 8.75 (1.76-43.52, P = 0.01), and lack of downstaging, HR 3.46 (1.03-11.62, P = 0.04), were significant predictors for BM. The 2-year rate of BM was 0%, 10.7%, and 30.3% (P < 0.001) in patients belonging to low-, intermediate-, and high-risk groups, respectively. Area under the ROC curve was 0.81 (P < 0.001). This model was externally validated (C-index = 0.79).

Conclusions: Lack of downstaging and persistent lymph node positivity after NAC are associated with development of BM in TNBC. This model can be used by the clinicians to stratify patients into the three risk groups to identify those at increased risk of developing BM and potentially impact surveillance strategies.

Keywords: brain metastasis; breast cancer; neoadjuvant chemotherapy; risk score; triple negative breast cancer.