Basal-like invasive breast cancer is an important clinical group because of its association with a triple-negative phenotype defined by the lack of expression of estrogen, progesterone and human epidermal growth factor receptors 2, relative lack of therapeutic options and poor prognosis. However, depending on the method used to define these lesions, morphological assessment, immunohistochemical markers or gene expression, a different set of tumors is captured. The aim of this study was to investigate the consequences of using different methodological approaches to define basal-like lesions among triple-negative breast carcinomas with regard to their clinicopathological features and patient outcome. The cohort consisted of 142 invasive breast cancers with a triple-negative receptor status. First, each was reviewed histologically and those with morphological basal-like features were characterized as 'Path-Basal'. Second, the 'Core Basal' immunohistochemical lesions, defined as cytokeratin 5/6 and/or epidermal growth factor receptor 1 positive, within the triple-negative breast cancers were identified, and third their classification based on gene expression profiling was retrieved and those in the molecular 'PAM50 basal-like' subtype recorded. A total of 116 basal-like breast cancers were identified among the 142 triple-negative breast cancers by at least one of these three classifications (80%), but only 13 samples were defined as basal-like with all three methods. None of these 13 tumors were associated with lymphovascular invasion. The 34 morphological 'Path-Basal' lesions were significantly associated with a lack of nodal metastases. Comparing the estimates of death in the three classifications, the highest risk of death was seen for the 'Core Basal' group. In this study, we highlight that the definition of basal-like breast cancer based on different methodologies varies significantly and does not identify the same lesions. This incomplete overlap of cases emphasizes the need for consistent or new approaches to improve precise identification.