Early Treatment Failure in Real-World Bispecific-Antibody Therapy for Relapsed or Refractory Multiple Myeloma: Pathways, Determinants, and Measurement Gaps

T-cell–redirecting bispecific antibodies have substantial antimyeloma activity in relapsed or refractory multiple myeloma, but their effectiveness in routine practice depends on patients reaching treatment and maintaining exposure long enough to achieve disease control. Clinical deterioration before dosing, incomplete step-up dosing, interrupted exposure, progression before response, infection, and early death can limit benefit. This narrative review integrates clinical trials, commercial cohorts, translational studies, and treatment-delivery evidence to examine these failures from treatment selection to durable benefit. Commercial cohorts show substantial early post-initiation mortality, predominantly associated with progressive myeloma. Drug-specific observations distinguish delayed response in clinically stable patients from established progression, relate residual tumor burden after cytoreduction to subsequent disease control, and place prior BCMA-directed therapy in the context of the preceding treatment course. Host and marrow reserve, immune fitness, and infection are examined in relation to disease control and treatment continuity. Current studies commonly begin at first administration and report response among evaluable patients, incompletely capturing pre-initiation loss and reasons for non-evaluability. Future datasets should link treatment-intended and treatment-initiated populations, retain reasons for missed transitions, record actual exposure, and distinguish unplanned interruption from response-adapted dose modification. Analyses should align time origin with the clinical question and account for response, supportive interventions, and dose modification as time-dependent variables when appropriate. As bispecific antibodies move earlier, prognostic associations from heavily pretreated cohorts require reassessment. Reporting across treatment stages can complement response and survival endpoints by distinguishing aggressive disease, insufficient exposure, competing morbidity, and treatment-delivery constraints.