The prognostic role of tumor size in early breast cancer in the era of molecular biology

Abstract

Background: The prognosis of early breast cancer (EBC) depends on patient and tumor characteristics. The association between tumor size, the largest diameter in TNM staging, and prognosis is well recognized. According to TNM, tumors classified as T2, could have very different volumes; e.g. a tumor of 2.1 cm has a volume of 4500 mm3, while a tumor of 4.9 cm has a volume of 60.000 mm3 even belonging to the same class. The aim of the study is to establish if the prognostic role of tumor size, expressed as diameter and volume, has been overshadowed by other factors. Methods: The primary objective is to evaluate the association between tumor dimensions and overall survival (OS) / disease free survival (DFS), in our institution from January 1st 2005 to September 30th 2013 in a surgical T1-T2 population. Volume was evaluated with the measurement of three half-diameters of the tumor (a, b and c), and calculated using the following formula: 4/3π x a x b x c. Results: 341 patients with T1-T2 EBC were included. 86.5% were treated with conservative surgery. 85.1% had a Luminal subtype, 9.1% were Triple negative and 7.4% were HER2 positive. Median volume was 942 mm3 (range 0.52–31.651.2). 44 patients (12.9%) relapsed and 23 patients died. With a median follow-up of 6.5 years, the univariate analysis for DFS showed an association between age, tumor size, volume, histological grading and molecular subtype. The multivariate analysis confirmed the statistically significant association only for molecular subtype (p 0.005), with a worse prognosis for Triple negative and HER2 positive subtypes compared with Luminal (HR: 2.65; 95%CI: 1.34–5.22). Likewise for OS, an association was shown by the multivariate analysis solely for molecular subtype (HER2 and Triple negative vs. Luminal. HR: 2.83; 95% CI:1.46–5.49; p 0.002). Conclusions: In our study, the only parameter that strongly influences survival is molecular subtype. These findings encourage clinicians to choose adjuvant treatment not based on dimensional criteria but on biological features.