Phenotypic Clustering of Beta-Thalassemia Intermedia Patients Using Cardiovascular Magnetic Resonance

Area of Science:

• Cardiology
• Hematology
• Medical Imaging

Background:

• Beta-thalassemia intermedia (β-TI) is a complex genetic disorder.
• Cardiac complications significantly impact morbidity and mortality in β-TI patients.
• Accurate risk stratification is crucial for managing β-TI.

Purpose of the Study:

• To identify distinct patient phenogroups in β-TI using integrated data.
• To assess the prognostic value of identified phenogroups regarding cardiovascular events.

Main Methods:

• Unsupervised hierarchical clustering of demographic, clinical, and cardiac magnetic resonance (CMR) data.
• Analysis of 138 β-TI patients from the MIOT Network.
• Utilized T2* for iron overload, cine imaging for cardiac structure/function, and late gadolinium enhancement for fibrosis detection.

Main Results:

• Three phenogroups (PGs) were identified: PG1 (women), PG2 (myocardial fibrosis, altered ventricular function), and PG3 (men, altered ventricular function without fibrosis).
• Hematochemical and iron levels did not define phenogroups.
• PG2 demonstrated a substantially higher risk of future cardiovascular events (heart failure, arrhythmias, pulmonary hypertension) compared to PG1 and PG3.

Conclusions:

• Unsupervised clustering effectively stratifies β-TI patients into phenogroups with distinct clinical and prognostic profiles.
• This approach aids in identifying high-risk patients for targeted cardiovascular monitoring and intervention.
• Phenogroup identification offers a novel tool for risk stratification in β-TI.