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Artificial Intelligence

Treatment Decisions in Multiple Myeloma.

| Source: The New England journal of medicine

Revolutions in transplantation and targeted and immune therapies have transformed multiple myeloma from a disease with an associated survival of a few years into one for which functional cure is an emerging goal. This abundance of effective therapies has created clinical complexity. Here we provide a practical framework, anchored in trial evidence and informed by emerging biologic discoveries, for the navigation of treatment decisions across the disease spectrum. We outline how cytogenetic and g

Revolutions in transplantation and targeted and immune therapies have transformed multiple myeloma from a disease with an associated survival of a few years into one for which functional cure is an emerging goal. This abundance of effective therapies has created clinical complexity. Here we provide a practical framework, anchored in trial evidence and informed by emerging biologic discoveries, for the navigation of treatment decisions across the disease spectrum. We outline how cytogenetic and genomic risk stratification, functional fitness, and measurable residual disease status individualize therapy in newly diagnosed disease, in which quadruplet induction therapy is now standard and the role of autologous transplantation is being reevaluated. Regarding relapse, we address the sequencing of B-cell maturation antigen-directed chimeric antigen receptor (CAR) T cells, bispecific antibodies, and antibody-drug conjugates, emphasizing T-cell fitness and multiantigen targeting to counter exhaustion and antigen escape. We also consider early interception in high-risk smoldering myeloma. Throughout, we underscore that enrollment of patients in clinical trials should be considered in order to ensure continued progress.

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