Managing RT Schedules of Early-Stage Breast Cancer Patients with a Genetic-Dosimetric Validated Model for Late Fibrosis

Abstract

Define a multifactorial risk prediction model for RT-induced fibrosis and investigate the benefit of a personalized approach for breast cancer (BC) patients (pts) treated with whole breast RT. In a previous study, we confirmed the predictive role of 30 SNPs from the literature and built an interaction aware Polygenic Risk Score (PRS, following the methods from Franco RO 2021) for Late Fibrosis (FG2+) on a cohort of 1500 pts from the REQUITE EU/USA prospective observational study. The PRS weights the radiosensitive (RS) and radioresistant (RR) genetic components and can be included in NTCP models. In a subgroup from the same cohort (390 pts), we have also confirmed an NTCP model based on biologically Equivalent Uniform Dose (BEUD) from PTV DVHs for pts treated at 40-50 Gy and no RT boost. Here, we combine PRS and BEUD into a sigmoid model allowing PRS to modulate BEUD50 (BEUD leading to 50% FG2+), i.e., we permitted a personalized BEUD50. We can also consider this as translating the PRS into a personalized equivalent BEUD, which is added/subtracted to the treatment BEUD. We evaluated model performances through ROC-AUC, calibration plot and Precision-Recall AUC. A total of 381 pts had complete dosimetric/genetic data, prescribed dose 40-50 Gy, and no fibrotic alteration at RT start. We scored FG2+ in 87 pts (23%). PRS ranged from -13 (more RR pts) to 7 (more RS), and a unit in PRS corresponds to 5.3 Gy BEUD or 3 Gy in EQ EUD2 Gy. Table 1 summarizes model performances, with details for subgroups below/above the quartiles I/III of the BEUD distribution. The PRS-only model correctly describes the toxicity rates in the whole population (calibration slope/offset = 0/1). Still, it overestimates/underestimates the absolute risks in the low/high dose ranges. The integrated model improves AUC-ROC and AUC-PRC by 5% and 10% and guarantees a better calibration in pts receiving low/high BEUD to the PTV. We developed a multifactorial model for FG2+ based on two previously validated models and reported the improvement against single-factor models. The BEUD+PRS model is suitable for assisting clinicians in managing early-stage BC pts. The number of fractions or the daily dose could be reduced for RS pts. The integrated model resulted in a possible quantitative tool for driving the planning decision process. Also, it showed a better performance in the high BEUD region, suggesting the potential value of its extension toward RT including boost or ultra hypofractionation. We are testing this extension in the whole REQUITE cohort.