A Clinical Prediction Model of Asymptomatic Left Ventricular Dysfunction in Survivors of Childhood Cancer in Ontario, Canada

Moderator

Roaa Shoukry, The Hospital for Sick Children, Toronto, ON, Canada

Speakers

Valerie Liu; Danielle Weidman; Sameera Ahmed; Paaladinesh Thavendiranathan; Aasthaa Bansal, MS, PhD; David Hodgson; Petros Pechlivanoglou, MSc, PhD, The Hospital for Sick Children, Toronto, ON, Canada

OBJECTIVES: Childhood cancer survivors (CCS) treated with anthracycline chemotherapy or radiation are at increased risk of developing cardiomyopathy and heart failure. A clinical prediction model can identify survivors at high risk for asymptomatic left ventricular dysfunction (ALVD), which precedes heart failure, supporting medical decision-making and improving CCS health outcomes. A clinical prediction model for ALVD risk in CCS was developed and evaluated using patient data from Ontario, Canada. Its results will inform a cost-utility analysis over a lifetime horizon to estimate the incremental costs and health outcomes of different cardiac screening schedules for CCS.
METHODS: Longitudinal data from Princess Margaret Cancer Centre in Ontario, Canada were used in a landmark analysis. The cohort comprised CCS who were treated with anthracyclines or chest radiation between 0-20 years and received at least one post-treatment echocardiogram between 1980/01/01 to 2022/05/31. ALVD was defined by ejection fraction (EF) percent < 51% in males and < 53% in females. Landmark times were set every two years over 22 years to train the model, with two-year predictions of ALVD risk. A Cox proportional hazards model was then fitted to interval-censored data. Calibration and time-dependent dynamic AUCt scores were used to assess predictive performance at each landmark time.
RESULTS: In this cohort, 94 survivors (n = 901) experienced ALVD. Fixed predictors included age at cancer diagnosis, time between diagnosis and first screening, and cardiomyopathy risk from treatment. Time-varying predictors included age, number of past screenings, and EF at screening, with interactions with landmark times (linear and quadratic). The model produced AUCt scores of 77.3% (95% CI 72.6, 81.9).
CONCLUSIONS: This prediction model demonstrated high predictive performance of ALVD in CCS using standard clinical parameters. The time-varying hazard ratios generated will be used in the microsimulation-based cost-utility analysis for routine echocardiographic screening in cancer survivors in Canada.

Conference/Value in Health Info

2025-05, ISPOR 2025, Montréal, Quebec, CA

Value in Health, Volume 28, Issue S1

Code

CO37

Topic

Clinical Outcomes

Topic Subcategory

Relating Intermediate to Long-term Outcomes

Disease

SDC: Cardiovascular Disorders (including MI, Stroke, Circulatory), SDC: Oncology, SDC: Pediatrics

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