Presence and utility of electrocardiographic abnormalities in long-term childhood cancer survivors

Background We assessed the prevalence and diagnostic value of ECG abnormalities for cardiomyopathy surveillance in childhood cancer survivors. Methods In this cross-sectional study, 1381 survivors ( >= 5 years) from the Dutch Childhood Cancer Survivor Study part 2 and 272 siblings underwent a long-term follow-up ECG and echocardiography. We compared ECG abnormality prevalences using the Minnesota Code between survivors and siblings, and within biplane left ventricular ejection fraction (LVEF) categories. Among 880 survivors who received anthracycline, mitoxantrone or heart radiotherapy, logistic regression models using least absolute shrinkage and selection operator identified ECG abnormalities associated with three abnormal LVEF categories (<52% in male/<54% in female, <50% and <45%). We assessed the overall contribution of these ECG abnormalities to clinical regression models predicting abnormal LVEF, assuming an absence of systolic dysfunction with a <1% threshold probability. Results 16% of survivors (52% female, mean age 34.7 years) and 14% of siblings had major ECG abnormalities. ECG abnormalities increased with decreasing LVEF. Integrating selected ECG data into the baseline model significantly improved prediction of sex-specific abnormal LVEF (c-statistic 0.66 vs 0.71), LVEF <50% (0.66 vs 0.76) and LVEF <45% (0.80 vs 0.86). While no survivor met the preset probability threshold in the first two models, the third model used five ECG variables to predict LVEF <45% and was applicable for ruling out (sensitivity 93%, specificity 56%, negative predictive value 99.6%). Calibration and internal validation tests performed well. Conclusion A clinical prediction model with ECG data (left bundle branch block, left atrial enlargement, left heart axis, Cornell's criteria for left ventricular hypertrophy and heart rate) may aid in ruling out LVEF <45%.