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An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
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.
Purpose:
Previous efforts to predict absolute risk of treatment-related cardiovascular diseases (CVDs) have mostly focused on childhood cancer survivors. We aimed to develop prediction models for risk of coronary heart disease (CHD) and heart failure (HF) for survivors of adolescent/adult Hodgkin lymphoma (HL).
Methods:
For model development, we used a multicenter cohort including 1,433 5-year HL survivors treated between 1965 and 2000 and age 18-50 years at HL diagnosis, with complete data on administered chemotherapy regimens, radiotherapy volumes and doses, and cardiovascular follow-up. Using cause-specific hazard models, covariate-adjusted cumulative incidences for CHD and HF were estimated in the presence of competing risks of death because of other causes than CHD and HF. Age at HL diagnosis, sex, smoking status, radiotherapy, and anthracycline treatment were included as predictors. External validation for the CHD model was performed using a Canadian cohort of 708 HL survivors treated between 1988 and 2004 and age 18-50 years at HL diagnosis.
Results:
After a median follow-up of 24 years, 341 survivors had developed CHD and 102 had HF. We were able to predict CHD and HF risk at 20 and 30 years after treatment with moderate to good overall calibration and moderate discrimination (areas under the curve: 0.68-0.74), which was confirmed by external validation for the CHD model (areas under the curve: 0.73-0.74). On the basis of our model including prescribed mediastinal radiation dose, 30-year risks ranged from 4% to 78% for CHD and 3% to 46% for HF, depending on risk factors.
Conclusion:
We developed and validated prediction models for CHD and HF with good overall calibration and moderate discrimination. These models can be used to identify HL survivors who might benefit from targeted screening for CVD and early treatment for CVD risk factors.
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