Development and Validation of Risk Prediction Models for Coronary Heart Disease and Heart Failure After Treatment for

Simone de Vries1, Miriam L Haaksma2, Katarzyna Jóźwiak3

  • 1Department of Epidemiology, The Netherlands Cancer Institute, Amsterdam, the Netherlands.

Insights

This study developed prediction models for heart disease and heart failure in Hodgkin lymphoma survivors. These models help identify individuals needing targeted cardiovascular screening and early risk factor management.

Area of Science:

  • Oncology
  • Cardiology
  • Epidemiology

Background:

  • Previous cardiovascular disease (CVD) risk prediction models primarily focused on childhood cancer survivors.
  • Hodgkin lymphoma (HL) survivors face significant risks of treatment-related cardiovascular complications.

Purpose of the Study:

  • To develop and validate prediction models for coronary heart disease (CHD) and heart failure (HF) in adolescent and adult Hodgkin lymphoma survivors.
  • To identify individuals at higher risk for targeted cardiovascular screening and intervention.

Main Methods:

  • Utilized a multicenter cohort of 1,433 HL survivors (treated 1965-2000) with detailed treatment and follow-up data.
  • Employed cause-specific hazard models to estimate cumulative incidences of CHD and HF, accounting for competing risks.
  • Included age at diagnosis, sex, smoking, radiotherapy, and anthracyclines as predictors; externally validated CHD model in a Canadian cohort.

Main Results:

  • After a median 24-year follow-up, 341 survivors developed CHD and 102 developed HF.
  • Models predicted 20- and 30-year risks of CHD and HF with moderate to good calibration (AUC: 0.68-0.74).
  • External validation confirmed CHD model performance (AUC: 0.73-0.74); 30-year CHD risk varied from 4% to 78% based on risk factors.

Conclusions:

  • Developed and validated prediction models for CHD and HF in HL survivors with good calibration and moderate discrimination.
  • These models enable identification of survivors who could benefit from tailored CVD screening and proactive management of risk factors.
Abstract