Toward more accurate adverse event attribution in multiple myeloma clinical trials

Adverse event (AE) attribution and reporting in multiple myeloma (MM) clinical trials rely on frameworks developed for cytotoxic chemotherapy that are poorly suited to the modern therapeutic landscape. This review identifies systematic limitations at every stage of AE reporting and proposes a comprehensive reform framework tailored to MM. Errors begin at AE identification and accumulate through each subsequent stage - terminology classification, severity grading, and causality attribution. The five-tier causality attribution system produces inconsistent and often uninformative assessments, and current grading frameworks cannot adequately characterize novel toxicities or capture the cumulative burden of AEs that wax and wane with disease control and treatment response. These challenges are amplified in MM, where older patients with disease-related symptom burden, combination regimens with overlapping toxicities, continuous treatment until progression, and racial differences in baseline physiology create attribution complexities that existing systems cannot address. We propose transitioning to a simplified two-tier attribution system, mandating comprehensive baseline assessments with longitudinal reassessment to capture dynamic changes with treatment response, integrating patient-reported outcomes with MM-specific symptom items, adopting objective criteria for determining clinical significance of laboratory abnormalities, implementing longitudinal toxicity analysis methods, enforcing standardized reporting requirements, and developing AI-based decision support tools. These reforms aim to improve consistency, accuracy, and clinical relevance of safety data in MM trials, ultimately supporting better patient care and more informed regulatory decisions.