Abstract
Breast cancer radiotherapy has evolved significantly, driven by decades of research into fractionation schedules aimed at optimizing treatment efficacy and minimizing toxicity. Initial trials such as NSABP B-06 and EBCTCG meta-analyses established the benefits of adjuvant whole-breast irradiation in reducing local recurrence and improving survival rates. The linear-quadratic (LQ) model provided a framework to understand tissue response to radiation, highlighting the importance of the α/β ratio in determining fractionation sensitivity. The present scoping review aimed to identify and describe hypofractionation regimens for whole breast radiotherapy and evaluate dose differences using the LQ model across proposed α/β ratios. A comprehensive PubMed search for clinical trials published since 2010 on hypo-fractionated regimens was performed. Studies discussing α/β ratios for breast cancer have been also searched. Data on dose, fractions and α/β ratios were collected, and biologically effective dose (BED) and equivalent dose in 2 Gy fractions were calculated. The coefficient of variation for BED varied with α/β ratios, showing the lowest variability for an α/β ratio of ~3 without tumor repopulation and increased with repopulation (BED-kT; k is a constant that depends on the repopulation rate of the tumor, and T is the total treatment time in days). Significant differences in BED variances were observed across α/β ratios (F-statistic 219.6, P<0.0001). START trials (P, A, and B) established α/β ratios of 3-4 Gy for breast cancer and normal tissues, confirming that hypofractionation is as effective as standard fractionation with potentially fewer late toxicities. Subsequent trials, such as FAST and FAST-Forward, demonstrated that ultra-hypofractionation is equivalent in tumor compared with conventional regimens. Further research is needed to gain a stronger understanding of radiobiological properties of breast cancer cells. Advances in radiotherapy technologies and the integration of biomarkers, radiomics and genomics are transforming treatment, moving towards precision medicine.