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ASCO 2026 | A machine learning-based six-gene signature for risk stratification in multiple myeloma
Shahzad Raza, MD, Cleveland Clinic, Cleveland, OH, shares insight into a machine learning (ML)-based six-gene signature for risk stratification in patients with TP53-mutated multiple myeloma (MM). Dr Raza highlights that his research identified the CoxBoost model as the best-fitted model for predicting patient outcomes, suggesting that integrating machine learning with genomic and clinical data will likely be the future in myeloma care. This interview took place during the 2026 American Society of Clinical Oncology (ASCO) Meeting in Chicago, IL.
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