Enhancing Prediction of Cancer Therapy-Related Cardiomyopathy From Surveillance Echocardiograms: A Children's Oncology Group Study.

BACKGROUND

Early echocardiographic indicators of cardiac remodeling may enhance cardiomyopathy risk prediction in childhood cancer survivors (CCS).

OBJECTIVES

The objective of the study was to assess whether influential echocardiographic measures can be combined to develop a robust cardiomyopathy risk prediction model in CCS.

METHODS

Multicenter retrospective study of ≥1-year CCS with digitally archived surveillance echocardiograms, enrolled cardiomyopathy cases (left ventricular [LV] fractional shortening ≤28% or LV ejection fraction ≤50% on ≥2 occasions) and noncases (≥5-year CCS who maintained fractional shortening ≥ 30% and ejection fraction ≥55% without initiation of cardiac medications). Echocardiograms were centrally quantitated in a blinded fashion. Least absolute shrinkage and selection operator regression identified the most influential 2-year predictors of cardiomyopathy among 27 echocardiographic parameters. Logistic regression was used to generate ORs with 95% CIs. Estimates were applied to the training and test data sets to generate area under the receiver operating characteristic curves (AUC).

RESULTS

Data from 146 CCS (52 cases; 94 noncases) with a median follow-up of 9.3 years post-cancer diagnosis and a total of 281 echocardiograms were included. A set of 7 echocardiographic measures were identified as the most influential predictors, with AUC of 0.82 (95% CI: 0.74-0.89) and 0.85 (95% CI: 0.74-0.95) in the training and test data sets, respectively. LV end-systolic dimension (ORmm: 1.2; 95% CI: 1.1-1.4), apical 4-chamber longitudinal strain (OR%: 1.2; 95% CI: 1.0-1.3), and septal A' velocity (ORcm/s: 1.3; 95% CI: 1.1-1.6) were strongly predictive of cardiomyopathy. AUCs were similar if cancer treatment exposures were included.

CONCLUSIONS

Early abnormalities in echocardiographic parameters of structure and function predict subsequent cardiomyopathy in CCS and can identify high-risk survivors who warrant early intervention.