Distinct Latent Trajectory Phenotypes of Left Ventricular Function Associated with Differential Survival Among Children Treated for Acute Myeloid Leukemia: A Report from the Children's Oncology Group

Background: Children treated for acute myeloid leukemia (AML) receive high doses of anthracyclines that may cause substantial short- and long-term morbidity and mortality. Thus, understanding its natural history and impact on treatment outcomes is crucial. Prior evaluations of cardiotoxicity in pediatric AML have focused on occurrence of incident declines below a left ventricular (LV) ejection fraction (EF) threshold (e.g., EF <50%). Broadening the focus to longitudinal EF trajectories may provide a mechanism to better characterize high-risk phenotypes, inform prognosis, and identify critical windows for intervention.

Methods: Between June 2011 and September 2018, AAML1031 enrolled patients aged <30 years with de novo AML. Echocardiographic evaluations were required before each treatment course, at the end of protocol therapy, and annually during off-protocol follow-up. The resulting EF measures were prospectively collected. Group-based trajectory modeling was used to identify latent subgroups with distinct patterns of longitudinal change in EF from baseline. Analyses were restricted to patients with a baseline measure of EF and at least two additional EF measures over the study period. The maximum number of potential EF trajectory classes was limited a priori to five. First, a single quadratic trajectory was modeled, and its fit statistics were compared to 2-, 3-, 4- and 5-group models. Then, the shapes of the changes in EF over time were modeled comparing fit statistics for models consisting of all combinations of linear, quadratic, and cubic trajectories. Individual patients were assigned to a single trajectory group based on their maximum posterior probability of membership. Average posterior probabilities of group membership were computed for each identified latent trajectory phenotype; average posterior probabilities >0.70 indicate that the model adequately discriminates between individuals with different trajectories. Distributions of demographic and clinical characteristics were compared for trajectory groups identified by the final model. Multivariable adjusted Cox regressions compared event-free (EFS) and overall survival (OS) for the identified EF trajectory groups. Analyses restricted to patients who completed all planned therapy on AAML1031 were also performed.

Results: 1063 patients contributed a total of 7284 EF measurements (median 6, IQR: 5-11 per person). The final model identified three distinct latent groups, one linear and two cubic trajectories (Figure 1), with 47% of patients categorized into Group 1 (preserved EF), 47% into Group 2 (moderate persistent reduction in EF), and 6% into Group 3 (dramatic EF decline with incomplete recovery). Average posterior probabilities were 0.87, 0.86, and 0.90 for Groups 1-3, respectively. The proportion of infants decreased from Group 1 to Group 3 (G1: 23%, G2: 16%, G3:11%; p<0.01). Group 3 had a higher proportion of Non-Hispanic Black patients (G1: 12%, G2: 11%, G3: 24% v, p=0.02) and slightly higher proportions of females (G1: 49%, G2: 46%, G3: 58%; p=0.17) compared to Groups 1 and 2. Groups 2 and 3 were less likely to have received dexrazoxane compared to Group 1 (G1: 17%, G2: 7%, G3: 7% v, p<0.001). There were no significant differences in distributions of insurance, weight status, risk classification or treatment arm. Group 2 EFS (G1: 48%, G2: 47%; p=0.72) and OS (G1: 68%, G2:64% v, p=0.22) were comparable to Group 1 whereas Group 3 EFS (G1: 48%, G3: 30%; p=0.003) and OS (G1: 68%, G3: 38%; p<0.001) were significantly reduced (Figure 2). Analyses restricted to patients completing AAML1031 therapy identified comparable trajectories but with higher average posterior probabilities (G1: 0.89, G2: 0.90, and G3: 0.94) as these patients had more complete capture of LVEF measurements in the study database.Conclusions: Group-based trajectory methods identified distinct EF trajectory phenotypes with differential EFS and OS. Prediction models focused on trajectory-defined phenotypes may elucidate genomic and environmental determinants of anthracycline-associated cardiotoxicity more effectively than investigations of incident occurrence alone. Accurate prediction of EF trajectory phenotypes may inform personalization of prognosis, treatment, and echo monitoring for pediatric patients treated for AML. Work is ongoing to identify supportive care practices that may modify distinct EF trajectory phenotypes.

No relevant conflicts of interest to declare.