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Data on Utility in Cost-Utility Analyses of Genetic Screen-and-Treat Strategies for Breast and Ovarian Cancer.
Simões Corrêa Galendi, Julia; Vennedey, Vera; Kentenich, Hannah; Stock, Stephanie; Müller, Dirk.
Afiliação
  • Simões Corrêa Galendi J; Institute of Health Economics and Clinical Epidemiology, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Gleueler Str. 174-176, 50923 Cologne, Germany.
  • Vennedey V; Institute of Health Economics and Clinical Epidemiology, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Gleueler Str. 174-176, 50923 Cologne, Germany.
  • Kentenich H; Institute of Health Economics and Clinical Epidemiology, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Gleueler Str. 174-176, 50923 Cologne, Germany.
  • Stock S; Institute of Health Economics and Clinical Epidemiology, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Gleueler Str. 174-176, 50923 Cologne, Germany.
  • Müller D; Institute of Health Economics and Clinical Epidemiology, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Gleueler Str. 174-176, 50923 Cologne, Germany.
Cancers (Basel) ; 13(19)2021 Sep 29.
Article em En | MEDLINE | ID: mdl-34638366
ABSTRACT
Genetic screen-and-treat strategies for the risk-reduction of breast cancer (BC) and ovarian cancer (OC) are often evaluated by cost-utility analyses (CUAs). This analysis compares data on health preferences (i.e., utility values) in CUAs of targeted genetic testing for BC and OC. Based on utilities applied in fourteen CUAs, data on utility including related assumptions were extracted for the health states (i) genetic test, (ii) risk-reducing surgeries, (iii) BC/OC and (iv) post cancer. In addition, information about the sources of utility and the impact on the cost-effectiveness was extracted. Utility for CUAs relied on heterogeneous data and assumptions for all health states. The utility values ranged from 0.68 to 0.97 for risk-reducing surgeries, 0.6 to 0.85 for BC and 0.5 to 0.82 for OC. In two out of nine studies, considering the impact of the test result strongly affected the cost-effectiveness ratio. While in general utilities seem not to affect the cost-utility ratio, in future modeling studies the impact of a positive/negative test on utility should be considered mandatory. Women's health preferences, which may have changed as a result of improved oncologic care and genetic counselling, should be re-evaluated.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article