The Prediction of Cardiac Events Using Contemporary Risk Prediction Models after Radiation Therapy for Head and Neck Cancer

Simple Summary Radiation therapy is associated with an increased risk for atherosclerotic cardiovascular disease (ASCVD). Contemporary risk prediction models accurately predict ASCVD in general populations. Whether these models adequately capture ASCVD risk after radiation therapy (RT) is unknown. Our data show that these standard risk scores do not reliably differentiate between those who will and those who will not have an ASCVD event after RT and underestimate the risk for ASCVD among patients receiving RT for HNCA. This study aims to evaluate the efficacy of the Pooled Cohort Equation (PCE), U.S. Preventative Services Task Force (USPSTF), and Framingham Risk Score (FRS) models in predicting ASCVD events among patients receiving radiation therapy (RT) for head and neck cancer (HNCA). From a large cohort of HNCA patients treated with RT, ASCVD events were adjudicated. Observed vs. predicted ASCVD events were compared. We compared rates by statin eligibility status. Regression models and survival analysis were used to identify the relationship between predicted risk and post-RT outcomes. Among the 723 identified patients, 274 (38%) were statin-eligible based on USPSTF criteria, 359 (49%) based on PCE, and 234 (32%) based on FRS. During follow-up, 17% developed an ASCVD, with an event rate of 27 per 1000 person-years, 68% higher than predicted (RR 1.68 (95% CI: 1.02, 2.12), p < 0.001). In multivariable regression, there was no difference in event rates by statin eligibility status (p > 0.05). Post-RT, the observed event rate was higher than the predicted ASCVD risk across all grades of predicted risk (p < 0.05) and the observed risk of an ASCVD event was high even among patients predicted to have a low risk of ASCVD. In conclusion, current ASCVD risk calculators significantly underestimate the risk for ASCVD among patients receiving RT for HNCA.