Neoadjuvant radiotherapy in the approach of locally advanced breast cancer. (9th March 2020) - Sousa, Cláudia; Cruz, Mafalda; Neto, Ana; Pereira, Kayla; Peixoto, Marta; Bastos, Joana; Henriques, Mónica; Roda, Domingos; Marques, Rui; Miranda, Cristina; Melo, Gilberto; Sousa, Gabriela; et al.
Abstract : Background: Approximately 4% of European patients are diagnosed with locally advanced breast cancer (LABC), a clinical condition commonly associated with poorer prognosis. Systemic therapy is the recommended initial treatment and when inoperability criteria prevails, radiotherapy (RT) should be used for tumour downstaging. This study intends to evaluate the impact of neoadjuvant radiotherapy (NART) in the treatment of inoperable LABC. Methods: A retrospective study of female patients, submitted to the NART between January 2014 and December 2018 at our institution. The evaluation of pathological response (pR) was made based on Pinder criteria. Primary endpoint: pR. Secondary endpoints: overall survival (OS) and progression-free survival (PFS). OS and PFS were calculated using the Kaplan-Meier method. Differences between groups were compared using Student's t-test, ANOVA (Analysis of variance) and χ 2 test. The statistical analyses were performed using Stata (V.13). Results: A total of 76 patients were included, 18% with breast complete response. The 5 years OS was 54% and PFS was 61%. Subgroup analysis showed that pR >90% is correlated with a better OS (p=0.004). Basal-like intrinsic subtype is correlated with worse OS and PFS (p<0.05). No relation was found between response and age, intrinsic subtype, treatment performed and clinical T stage. Conclusion: Our study confirms that NART is an effective downsizing treatment in inoperable LABC, allowing for a surgical resection regardless of the systemic treatment performed. Response to NART is independent of the intrinsic subtype and pR >90% is correlated with a better OS. Prospective studies to explore predictive response biomarkers are necessary in order to improve patient selection and optimisation of the treatment.