External validation of Cardiac disease, Hypertension, and Logarithmic Left anterior descending coronary artery radiation dose (CHyLL) for predicting major adverse cardiac events after lung cancer radiotherapy

Abstract

Background and purpose: Major adverse cardiac events(MACE) are prevalent in patients with locally advanced-non-small cell lung cancer(LA-NSCLC) following radiotherapy(RT). The CHyLL model, incorporating coronary heart disease(CHD),Hypertension(HTN),Logarithmic LADV15 was developed and internally-validated to predict MACE among LA-NSCLC patients. We sought to externally validate CHyLL to predict MACE in an independent LA-NSCLC cohort. Patients and methods: Patients with LA-NSCLC treated with RT were included. CHyLL score was calculated:5.51CHD + 1.28HTN + 1.48ln(LADV15 + 1)-1.36CHD*ln(LADV15 + 1). CHyLL performance in predicting MACE was assessed and compared to mean heart dose(MHD) using Cox-proportional hazard(PH) analyses and Harrel’s concordance(C)-indices. MACE and overall survival(OS) among low-vs high-risk groups(CHyLL < 5 vs ≥ 5) were compared. Results: In the external validation cohort(N = 102), the median age was 71 years and 55% were females. Most(n = 74,73%), had clinical Stage III disease and 35(34%) underwent surgery. CHyLL demonstrated good MACE prediction with C-index of 0.73(95% Confidence Interval(CI):0.58–0.89), while MHD did not (C-index = 0.46 (95% CI:0.30–0.62)). Per CHyLL, 32(31%) and 70(69%) patients were considered low-and high-risk for MACE, respectively. CHyLL consistently identified lower MACE rates in the low-vs high-risk group(log-rank p = 0.108):0 vs 8%(12 months),5 vs 16%(24 months),5 vs 16%(36 months),and 5 vs 19%(48 months) post-RT. In the pooled internal and external validation cohort(N = 303), MACE rates in low-vs high-risk groups were statistically significantly different(log-rank p = 0.01):1 vs 6%(12 months),3 vs 12%(24 months),6 vs 19%(36 months),and 6 vs 21%(48 months). Conclusions: CHyLL was externally validated and superior to MHD in predicting MACE. CHyLL has the potential to identify high-risk patients who may benefit from cardio-oncology optimization and to estimate personalized LADV15 constraints based on cardiac risk factors and acceptable MACE thresholds.