Cooper, K., Bryant, J., Picot, J., Clegg, A., Roderick, P. R., Rosenberg, W. M. and Patch, C.
A decision analysis model for diagnostic strategies using DNA testing for hereditary haemochromatosis in at risk populations.
QJM: An International Journal of Medicine, 101, (8), . (doi:10.1093/qjmed/hcn070).
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BACKGROUND: New techniques for diagnosing hereditary haemochromatosis (HHC) have become available alongside traditional tests such as liver biopsy and serum iron studies. AIM: To evaluate DNA tests in people suspected of having haemochromatosis at clinical presentation compared to liver biopsy, and in family members of those diagnosed with haemochromatosis compared to phenotypic iron studies in UK. METHODS: Decision analytic models were constructed to compare the costs and consequences of the diagnostic strategies for a hypothetical cohort of people with suspected haemochromatosis. For each strategy, the number of cases of haemochromatosis identified and treated and the resources used were estimated. RESULTS: For diagnostic strategies in people suspected clinically of having haemochromatosis, the DNA strategy is cost saving compared to liver biopsy (cost saved per case detected, 123 pounds) and continues to be so across all ranges of parameters. For family testing, the DNA strategy is cost saving for the offspring of the proband but not for siblings. If the DNA test cost were to reduce by 40% to 60 pounds or, if in the phenotypic model, those with initially normal iron indices were retested twice instead of once, the DNA strategy would be the cheaper one. CONCLUSION: Diagnostic strategies involving DNA testing are likely to be cost saving in clinical cases with iron overload and in the offspring of index cases. This study supports the UK guideline recommendations for the use of DNA testing in UK
|Digital Object Identifier (DOI):
|| research support, pathology, risk, model, economics, hemochromatosis, cohort, iron, family, blood, strategies,analysis, biopsy, trace elements, male, genetics, cost-benefit analysis, serum, humans, liver, diagnosis, people, dna, phenotype, sensitivity and specificity, health technology assessment, population, health, great britain, genetic screening, decision support techniques, iron overload, evaluation studies, decision trees, female, research, genetic markers, methods
||University Structure - Pre August 2011 > School of Medicine > Community Clinical Sciences
|Accepted Date and Publication Date:
||13 Jan 2010
||31 Mar 2016 12:58
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