Novel risk score for predicting acute cardiovascular and cerebrovascular events after chest radiotherapy in patients with breast or lung cancer.

Abstract

Aims: Radiation therapy (RT) is an integral component of cancer therapy but associated with adverse events. Our goal was to establish risk prediction models for major adverse cardiovascular and cerebrovascular events (MACCE) after chest RT.

Methods and results: A retrospective study of lung/breast cancer patients who had chest RT with planning CT at Mayo Clinic between 01/2010 and 01/2014. Predictive models were developed based on weighted independent predictors using a derivation (406 lung and 711 breast cancer) and validation cohort (179 lung and 234 breast cancer). Patient characteristics, pre-RT CT for coronary artery calcification (CAC), and post-RT MACCE data were reviewed. Post-RT MACCE occurred in 6.1 and 5.6% in the derivation and validation cohort over a mean follow-up of 42 ± 13 months. Post-therapy model (C2AD2) included CAC (two points), MACCE history (two points), age ≥74 (three points), DM (two points), and mean heart radiation dose ≥ 850 mGy (two points), and pre-therapy model (C2AD) included post-therapy model parameters minus mean heart radiation dose. Both models stratified patients into three risk groups: low (0-2), intermediate (3-5), and high (≥6). Post-RT MACCE across these groups were 2.7, 8.9, and 19.8% in the derivation, and 3.9, 6.6, and 16.4% in the validation cohort for post-therapy model (C2AD2) and 2.8, 9.2, and 20.4% in the derivation and 3.7, 9.2, and 13.2% in the validation cohort for pre-therapy model. Both models showed statistically significant graded survival outcome.

Conclusion: Post-therapy (C2AD2) and pre-therapy (C2AD) models are simple, easy to use and effective tools to stratify breast and lung cancer patients undergoing chest radiation for post-RT MACCE.