OBJECTIVE: We review the published economic evaluation studies applied to genetic technologies in the EU to know the main diseases addressed by these studies, the ways the studies were conducted and to assess the efficiency of these new technologies. The final aim of this review was to understand the possibilities of the economic evaluations performed up to date as a tool to contribute to decision making in this area. METHODS: We have reviewed a set of articles found in several databases until March 2010. Literature searches were made in the following databases: PubMed; Euronheed; Centre for Reviews and Dissemination of the University of York-Health Technology Assessment, Database of Abstracts of Reviews of Effects, NHS Economic Evaluation Database; and Scopus. The algorithm was "(screening or diagnosis) and genetic and (cost or economic) and (country EU27)". We included studies if they met the following criteria: (1) a genetic technology was analysed; (2) human DNA must be tested for; (3) the analysis was a real economic evaluation or a cost study, and (4) the articles had to be related to any EU Member State. RESULTS: We initially found 3,559 papers on genetic testing but only 92 articles of economic analysis referred to a wide range of genetic diseases matched the inclusion criteria. The most studied diseases were as follows: cystic fibrosis (12), breast and ovarian cancer (8), hereditary hemochromatosis (6), Down's syndrome (7), colorectal cancer (5), familial hypercholesterolaemia (5), prostate cancer (4), and thrombophilia (4). Genetic tests were mostly used for screening purposes, and cost-effectiveness analysis is the most common type of economic study. The analysed gene technologies are deemed to be efficient for some specific population groups and screening algorithms according to the values of their cost-effectiveness ratios that were below the commonly accepted threshold of 30,000€. CONCLUSIONS: Economic evaluation of genetic technologies matters but the number of published studies is still rather low as to be widely used for most of the decisions in different jurisdictions across the EU. Further, the decision bodies across EU27 are fragmented and the responsibilities are located at different levels of the decision process for what it is difficult to find out whether a given decision on genetic tests was somehow supported by the economic evaluation results.
OBJECTIVE: We review the published economic evaluation studies applied to genetic technologies in the EU to know the main diseases addressed by these studies, the ways the studies were conducted and to assess the efficiency of these new technologies. The final aim of this review was to understand the possibilities of the economic evaluations performed up to date as a tool to contribute to decision making in this area. METHODS: We have reviewed a set of articles found in several databases until March 2010. Literature searches were made in the following databases: PubMed; Euronheed; Centre for Reviews and Dissemination of the University of York-Health Technology Assessment, Database of Abstracts of Reviews of Effects, NHS Economic Evaluation Database; and Scopus. The algorithm was "(screening or diagnosis) and genetic and (cost or economic) and (country EU27)". We included studies if they met the following criteria: (1) a genetic technology was analysed; (2) human DNA must be tested for; (3) the analysis was a real economic evaluation or a cost study, and (4) the articles had to be related to any EU Member State. RESULTS: We initially found 3,559 papers on genetic testing but only 92 articles of economic analysis referred to a wide range of genetic diseases matched the inclusion criteria. The most studied diseases were as follows: cystic fibrosis (12), breast and ovarian cancer (8), hereditary hemochromatosis (6), Down's syndrome (7), colorectal cancer (5), familial hypercholesterolaemia (5), prostate cancer (4), and thrombophilia (4). Genetic tests were mostly used for screening purposes, and cost-effectiveness analysis is the most common type of economic study. The analysed gene technologies are deemed to be efficient for some specific population groups and screening algorithms according to the values of their cost-effectiveness ratios that were below the commonly accepted threshold of 30,000€. CONCLUSIONS: Economic evaluation of genetic technologies matters but the number of published studies is still rather low as to be widely used for most of the decisions in different jurisdictions across the EU. Further, the decision bodies across EU27 are fragmented and the responsibilities are located at different levels of the decision process for what it is difficult to find out whether a given decision on genetic tests was somehow supported by the economic evaluation results.
Authors: Judith Balmaña; Judit Sanz; Xavier Bonfill; Alfonso Casado; Montse Rué; Ignasi Gich; Orland Díez; Josep M Sabaté; Montserrat Baiget; M Carmen Alonso Journal: Int J Cancer Date: 2004-11-20 Impact factor: 7.396
Authors: Elizabeth J J Berm; Margot de Looff; Bob Wilffert; Cornelis Boersma; Lieven Annemans; Stefan Vegter; Job F M van Boven; Maarten J Postma Journal: PLoS One Date: 2016-01-11 Impact factor: 3.240