Risk scoring model to predict recurrence in locally advanced breast cancer (LABC) treated with neoadjuvant chemotherapy (NACT).

Abstract

98 Background: Complete response (CR) to NACT portends favorable long term outcomes in LABC. There is a need for a tool to risk categorise patients for recurrence risk (RR), so that intensification of treatment can be offered to women with high risk of recurrence. Methods: A prospectively maintained database of LABC (between January 2007 to December 2012), who received NACT followed by definitive surgery, radiotherapy and endocrine therapy in endocrine sensitive disease was retrospectively analyzed for clinico-pathological and treatment factors affecting disease free survival (DFS). A risk scoring model was developed on the basis of beta coefficients of identified independent risk factors for DFS. Results: The incidence of loco-regional relapse was 8% and that of distant metastases was 32% in a dataset of 206 patients at a median follow-up of 47 months (IQR 24-62 mo). The independent risk factors for recurrence were index T stage [HR 1.8 (0.9-3.6)], N stage [HR 1.7 (0.4 – 4.7)], grade [HR 1.8 (0.8-4.2)], age less than and more than 40 years [HR 1.6 (0.4-0.9)], pathologic CR [HR 4.3 (1.7- 10.7)], intrinsic subtype [HR 2.2 (1.3-3.7)], and type of surgery (BCS vs MRM) [HR 2.2 (1.3-3.6)]. The ROC of the model for the prediction of recurrence was 0.67 (95 % CI: 0.61-0.75). The results of this model were validated by dividing the population into 3 risk groups: low risk (score less than 12), intermediate risk group (score between 13-15), high risk group (score 16 or more). The chances of recurrence are 16% versus 34% versus 57% in low, intermediate and high risk group respectively. Presence of three risk factors implies low risk, five intermediate and more than five high risk. Conclusions: The risk scoring model developed by us predicts RR and can be used for selecting patients for treatment intensification in high risk category.