December 8, 2025Blood

Machine learning–driven prognostication of overall survival at 6 months after CAR-T cell therapy

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Prognostic model demonstrates improved survival prediction in hematologic malignancies, suggesting better patient management post CAR-T infusion.

A multimodal model predicts overall survival with a mean AUC of 0.87, highlighting significant prognostic capabilities.
Key features include vital signs, laboratory values, and radiomics data, enhancing the model's predictive accuracy.
Gradient-boosting models trained on patient data offer real-time risk stratification for patients undergoing CAR-T therapy.
Integration of this ML model into clinical workflows may facilitate proactive patient management and improved outcomes.

Villasboas et al. (2025) studied this question.

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December 8, 2025Blood

View Full Paper

Ask AI

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Authors

Prognostic model demonstrates improved survival prediction in hematologic malignancies, suggesting better patient management post CAR-T infusion.

A multimodal model predicts overall survival with a mean AUC of 0.87, highlighting significant prognostic capabilities.
Key features include vital signs, laboratory values, and radiomics data, enhancing the model's predictive accuracy.
Gradient-boosting models trained on patient data offer real-time risk stratification for patients undergoing CAR-T therapy.
Integration of this ML model into clinical workflows may facilitate proactive patient management and improved outcomes.

Villasboas et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark