Title: TPMT Testing in Azathioprine: A "Cost-effective Use of Healthcare Resources"?
Authors: PAYNE KatherineGURWITZ DavidIBARRETA RUIZ DoloresNEWMAN WilliamPHILLIPS Kathryn
Citation: PERSONALIZED MEDICINE vol. 6 no. 1 p. 103-113
Publication Year: 2009
JRC N°: JRC48363
ISSN: 1741-0541
URI: http://www.futuremedicine.com
DOI: 10.2217/17410541.6.1.103
Type: Articles in periodicals and books
Abstract: This study aimed to critically appraise the current level of economic evidence available for thiopurine methyl-transferase (TPMT) testing of thiopurine drugs, such as azathioprine. Six economic evaluations of testing were identified, which all recommended that TPMT testing is a cost-effective use of healthcare resources. Critical appraisal, using published guidelines, showed potential limitations in model structures, approaches to data analysis and input parameters, which were mainly based on expert opinion. Where data did exist these were from retrospective studies. To conduct economic evaluations with more robust findings, decision analysts need good quality data for the following key parameters: current prevalence of profound neutropaenia among patients prescribed thiopurine drugs, mean length of related hospitalisation and clinical outcome; impact of introducing the test on clinical pathways in terms of resource use; clinical effectiveness data in terms of number of cases of neutropaenia averted and subsequent impact on mortality and health related quality of life. An iterative approach may be used to stimulate the production of a sufficient evidence base for innovative technologies, such as pharmacogenetic testing. Such an iterative approach involves starting with simple models using available existing clinical and resource use data, as in the case of TPMT testing. The use of formal value of information methods may guide the decision whether prospective studies are required to address uncertainties in the key parameters driving the model results. The results from well designed prospective studies can then be used to populate more complex economic models.
JRC Directorate:Growth and Innovation

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