Summary
Develop prediction models for early and persistent cardiac toxicity in pediatric acute myeloid leukemia (AML) patients, using existing clinical trial data to inform personalized treatment and monitoring strategies.
Predicting and Monitoring for Cardiac Toxicity in Pediatric AML
US · IL
NIH
grant
awarded
#nih-5R01HL163657-03
What they want
Develop a highly unique dataset combining detailed demographic, clinical, genomic, treatment, and toxicity data with longitudinal indices of left ventricular (LV) size, diastolic, and systolic function from all clinical surveillance echocardiograms for patients enrolled on two Children’s Oncology Group (COG) AML trials, AAML0531 and AAML1031. Utilize novel, sophisticated analytic methods to develop models that: (1) continually update predictions of early cardiotoxicity risk during frontline therapy, (2) predict LV functional trajectories leading to persistent or worsening LVSD in the early/moderate time window after AML therapy, and (3) compare cancer treatment outcomes (EFS and OS) and detection of LVSD for three cardiotoxicity monitoring schedules with different echo frequencies in pediatric AML patients.
Deliverables
- Highly unique dataset combining demographic, clinical, genomic, treatment, toxicity, and longitudinal echocardiogram data
- Model for continually updating predictions of early cardiotoxicity risk during frontline therapy
- Model for predicting LV functional trajectories leading to persistent or worsening LVSD after AML therapy
- Analysis comparing cancer treatment outcomes and LVSD detection for three cardiotoxicity monitoring schedules
Technical requirements
- Novel, sophisticated analytic methods
