Cost-Effectiveness Analyses in AML: What Have We Learned, How Should This Impact Patient Care, and What Needs to Be Done in the Future?

Abstract

Acute myeloid leukemia (AML) is the most common acute leukemia in adults in the United States and has seen the approval of several novel agents over the past decade. Similar to treatments for other hematologic and solid malignancies, these novel agents are costly. In the setting of finite financial resources in the healthcare system, the concept of cost-effectiveness analyses has been developed to compare the estimated costs and associated benefits expected with different interventions (eg, drugs, diagnostic tests, procedures). Although drug approvals in the United States are not based on budgetary considerations, cost-effectiveness analyses can inform health policy decisions, resource allocation, and societal debates. However, such analyses are only capturing parts of the costs and benefits to the healthcare system, payers, and consumers, and are based on modeling assumptions with inherent limitations. In addition, cost-effectiveness analyses for several of the novel agents approved for treatment of AML are limited and have reported conflicting results. This review uses cost-effectiveness analyses of azacitidine/venetoclax and liposomal cytarabine/daunorubicin as examples to review considerations and best practices when conducting and interpreting such studies. To ensure adequate interpretability of cost-effectiveness studies, transparency in the model inputs/assumptions, data sources, and funding is of great importance, as evidenced by the discrepant conclusions across studies. Furthermore, the perspective and the healthcare system from which a cost-effectiveness analysis is conducted are important to consider because practice patterns and drug prices between countries can be variable. However, with advances in health economic modeling techniques, adherence to best practices, and increasing public interest in these types of studies, cost-effectiveness analyses can become an important tool to inform various stakeholders in the healthcare system to allocate limited resources most efficiently.

Effective Prognostic Model for Therapy Response Prediction in Acute Myeloid Leukemia Patients

“…The past decades have been marked by an increasing progress in the scientific understanding of AML biology, leading to enhanced prognostication tools and risk assessments [ 5 , 29 ]. Due to a combination of advances in supportive care and the availability of novel, often molecularly targeted, therapies, the life expectancy of AML patients continues to improve [ 30 , 31 ]. However, despite obvious progress in the diagnosis and management of AML, some obstacles in the successful achievement of the therapy response exist, one of which is the initial resistance of leukemic cells to cytotoxic drugs [ 3 , 32 ].…”

Analysis of prognostic biomarker models of TXNIP/NLRP3/IL1B inflammasome pathway in patients with acute myeloid leukemia

“…Acute myeloid leukemia (AML) is a genetically heterogeneous disease, characterized by abnormal hematopoiesis, differentiation blockade and inadequate production of blood cells 1 , 2 . It is the most common myeloid leukemia in adults 3 , 4 . Previous research in our laboratory have shown that the prognosis of AML is closely related to immune checkpoints 5 - 7 .…”