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<p>Older adults with acute myeloid leukemia (AML) face disproportionately poor outcomes, driven by a combination of high-risk disease biology and functional vulnerabilities that are often overlooked by conventional oncology assessments. Geriatric assessment (GA) offers a multidimensional approach to uncover these impairments—spanning physical function, cognitive status, comorbidity burden, and emotional well-being—and provides critical information that independently predicts survival and treatment tolerance. Early studies demonstrate that GA can personalize treatment intensity decisions, inform supportive care interventions, and improve quality of life, yet its incorporation into routine AML care remains limited. Barriers to broader implementation include the need for streamlined workflows, clinician training, and large-scale validation. Future efforts should focus on integrating GA with biological markers of aging and disease to refine risk stratification, and leveraging digital tools and artificial intelligence to enhance feasibility and scalability. Ultimately, optimizing the management of older adults with AML will require a personalized, goal-concordant approach that combines GA-driven risk assessment with emerging therapeutic and supportive care strategies, ensuring that treatment intensity is matched to both disease biology and individual patient resilience.</p>

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Care of Older Adults with Acute Myeloid Leukemia: The Role of Geriatric Assessment

  • 期刊论文

  • 发表日期：

    2025年9月24日

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  • Ojbindra KC,
  • Moataz Ellithi,
  • Vijaya Raj Bhatt

摘要

Older adults with acute myeloid leukemia (AML) face disproportionately poor outcomes, driven by a combination of high-risk disease biology and functional vulnerabilities that are often overlooked by conventional oncology assessments. Geriatric assessment (GA) offers a multidimensional approach to uncover these impairments—spanning physical function, cognitive status, comorbidity burden, and emotional well-being—and provides critical information that independently predicts survival and treatment tolerance. Early studies demonstrate that GA can personalize treatment intensity decisions, inform supportive care interventions, and improve quality of life, yet its incorporation into routine AML care remains limited. Barriers to broader implementation include the need for streamlined workflows, clinician training, and large-scale validation. Future efforts should focus on integrating GA with biological markers of aging and disease to refine risk stratification, and leveraging digital tools and artificial intelligence to enhance feasibility and scalability. Ultimately, optimizing the management of older adults with AML will require a personalized, goal-concordant approach that combines GA-driven risk assessment with emerging therapeutic and supportive care strategies, ensuring that treatment intensity is matched to both disease biology and individual patient resilience.