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Systematic review of health state utility values for acute myeloid leukemia

期刊

CLINICOECONOMICS AND OUTCOMES RESEARCH
卷 10, 期 -, 页码 83-92

出版社

DOVE MEDICAL PRESS LTD
DOI: 10.2147/CEOR.S153286

关键词

acute myeloid leukemia; EQ-5D; health-related quality of life; utility; systematic review; economic analysis; QALY

资金

  1. Novartis

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Background: Cost-utility analyses for acute myeloid leukemia (AML) require health state utility values (HSUVs) in order to calculate quality-adjusted life-years (QALYs) for each health state. Aim: This study reviewed AML-related HSUVs that could be used in economic evaluation studies. Materials and methods: EMBASE, MEDLINE, and Cochrane databases were searched from January 2000 to November 2016 for relevant studies that reported quality of life (QoL) and HSUVs in AML. Identified relevant European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 values were mapped to HSUVs. HSUVs for each health state in the AML treatment pathway were then collated. Results: Ten relevant studies were identified. Six were cost-effectiveness analyses utilizing HSUVs for calculation of QALYs, one was an effectiveness analysis (incremental QALY), and two were QoL studies reporting AML-specific utilities. An additional study reported QoL for patients undergoing stem cell transplantation (SCT). Since no study reported HSUVs for relapse, values from a study of secondary AML patients who failed prior treatment for myelodysplastic syndrome were used. Where multiple HSUVs were available, collected values were given priority over assumed values. AML treatment (induction, consolidation, or SCT) was associated with decreased HSUV, while post-treatment complete remission led to increased HSUV. Conclusion: There are some methodologically robust HSUVs that can be directly used in economic evaluations for AML. Careful interpretation is advised considering significant differences in methodologies and patient population (inclusion, size). We need to develop HSUVs with larger-sized studies, making greater use of condition-specific data.

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