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October 11, 2025HemaSphereOpen Access

Machine learning risk stratification strategy for multiple myeloma: Insights from the EMN–HARMONY Alliance platform

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Authors

AOAdrián Mosquera OrgueiraMGMarta Sonia GonzálezMDMattia D’Agostino

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Overview

This analysis demonstrates new machine learning prognostic scores for multiple myeloma, indicating improved risk stratification accuracy beyond traditional methods.

Key Points

  • New machine learning models predict survival outcomes, improving personalized risk management in multiple myeloma.
  • The comprehensive model achieved a C-index of 0.667 for overall survival, indicating effective predictive power.
  • Utilizing the EMN–HARMONY cohort data of over 14,000 patients allowed for robust model validation and evaluation.
  • These ML-based scores surpass traditional staging systems, showing effectiveness across different patient populations.

Cite This Study

Orgueira et al. (2025) studied this question.

synapsesocial.com/papers/68e9b1b5ba7d64b6fc132120https://doi.org/10.1002/hem3.70228
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