Genomic analysis through various platforms is an essential tool for determining prognosis and treatment in a significant subgroup of early-stage breast cancer patients with hormone receptor-positive and human epidermal growth factor receptor 2 (HER2)-negative status. Additionally, combined clinical and pathological characteristics can accurately predict the recurrence score (RS), as demonstrated by the University of Tennessee risk nomogram. In this study, we aimed to identify classical clinical-pathological factors associated with high RS in a local population, including modern parameters such as current abemaciclib treatment recommendations, HER2-low status, different Ki-67 cutoff values, and samples obtained from secondary primary tumours. This is a retrospective single-institution study that analysed a total of 215 tumour samples. Among lymph node-negative patients (n = 179), age, Ki67 values, and progesterone receptor status predicted RS after multivariate analysis. HER2-low status was not associated with RS differences (p = 0.41). Among lymph node-positive patients (n = 36), MonarchE inclusion criteria (15) were not associated with a higher RS (p = 0.61), and HER2-low did not reach statistical significance. However, tumours classified as secondary primaries numerically exhibited a higher RS. Based on these findings from our real-world sample, the mere application of clinical and pathological parameters is insufficient to predict RS outcomes. Modern parameters such as HER2-low status or adjuvant abemaciclib recommendations were not associated with RS differences. Regarding the observation of secondary tumours, more evidence is needed to understand whether prior hormone therapy exposure impacts the biological risk of secondary primary tumours.