Published Mar 31, 2014

York, UK - Acute myeloid leukaemia (AML) is an aggressive cancer, with treatments ranging from supportive care (mainly blood product transfusion) to intensive chemotherapy and stem cell transplantation. These treatments can be expensive, particularly when the costs of managing toxicities and relapse are included. Despite the potentially long-term economic burden of this on health resources, there have been no attempts to accurately predict the long-term medical costs for this disease alongside patients’ response to therapy and life expectancy. A team of researchers at the University of York recently addressed these issues by developing a hybrid model combining a decision tree with several Markov models. This approach uses population-based data from a specialist UK registry - the Haematological Malignancy Research Network (www.HMRN.org). Expected five-year medical costs and life expectancy ranged from £8,170 to £81,636 and 3.03 to 34.74 months respectively, highlighting the heterogeneity of this disease. This innovative approach of using data from a population-based study, rather than a randomized controlled trial, accurately reflects current clinical practice. This is particularly important when evaluating the cost-effectiveness of new interventions and determining the efficient allocation of health resources. Han-I Wang, lead author of the study said, “This robust model could be used to evaluate new treatments for AML, potentially enabling policy makers to make more informed decisions.” The full study, “Long-Term Medical Costs and Life Expectancy of Acute Myeloid Leukemia: A Probabilistic Decision Model” is published inValue in Health.

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