Serious Adverse Events in Oncology Trials: Novel Risk Assessment and Management Approaches

Abstract

Serious adverse events (SAEs) remain a critical concern in oncology clinical trials, directly impacting patient safety and the development of new therapies. With the growing use of targeted treatments and immunotherapies, treatment-related toxicities have become more complex and less predictable than with conventional chemotherapy. Traditional reactive approaches are increasingly inadequate, necessitating proactive strategies for early identification and management of SAEs. Advances in artificial intelligence (AI) and predictive analytics have enabled the early detection of adverse events and the identification of high-risk patients (6,7,20). Additionally, decentralized trials and wearable technologies now allow continuous, real-world patient monitoring (16). Despite these innovations, challenges such as data quality, algorithm transparency, and evolving regulatory frameworks limit their widespread adoption. This review synthesizes current knowledge on SAE risk factors, discusses monitoring and management strategies, and highlights emerging technologies aimed at enhancing patient safety in oncology trials.

Ähnliche Arbeiten