A Biomarker-Based Diagnostic Model for Cardiac Dysfunction in Childhood Cancer Survivors
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View abstract on PubMed
Summary
This summary is machine-generated.A new model combining cardiac biomarkers and clinical data can help rule out left ventricular dysfunction in childhood cancer survivors. This may reduce the need for lifelong echocardiographic surveillance in these patients.
Area Of Science
- Cardiology
- Oncology
- Biomarker Research
Background
- Childhood cancer survivors require lifelong cardiac surveillance due to heart failure risk.
- Previous biomarkers like NT-proBNP and hs-cTnT showed limited accuracy for left ventricular (LV) dysfunction.
- Combining biomarkers with clinical data may improve diagnostic accuracy for LV dysfunction.
Purpose Of The Study
- To develop and validate a diagnostic model for LV dysfunction in childhood cancer survivors.
- The model integrates cardiac biomarkers (NT-proBNP, hs-cTnT) with clinical characteristics.
- To effectively rule in or rule out LV dysfunction in this high-risk population.
Main Methods
- A multicenter cross-sectional study included 1,334 survivors and 278 siblings.
- Logistic regression models were developed and validated using bootstrapping.
- Biomarkers (NT-proBNP, hs-cTnT) were combined with clinical data.
Main Results
- The combined model improved prediction of LV dysfunction (C statistic increased from 0.69 to 0.73 for LVEF <50%).
- More severe LV dysfunction prediction also improved (C statistic from 0.80 to 0.86 for LVEF <45%).
- The model effectively ruled out LV dysfunction in a significant proportion of survivors, with high sensitivity and negative predictive values.
Conclusions
- A biomarker-based diagnostic model can effectively rule out LV dysfunction in childhood cancer survivors.
- This approach may reduce the need for extensive echocardiographic surveillance.
- External validation is recommended to confirm the model's utility.
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