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A review and meta-analysis of health state utility values in breast cancer

  • Peasgood, T
  • Ward, S
  • Brazier, J
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    Background and purpose Health-related quality of life is an important issue in the treatment of breast cancer, and health-state utilities are essential for cost-utility analysis. This paper identifies and summarises published utilities for common health-related quality of life outcomes for breast cancer, considers the impact of variation in study designs used, and pools utilities for some breast cancer health states. Data sources and study selection Thirteen databases were searched using key words relating to breast cancer and utility measurement. Articles were included if specified empirical methods for deriving utility values were used and details of the method, including number of respondents, were given. Articles were excluded if values were based on expert opinion or were not unique. Data extraction and synthesis The authors identified 49 articles which met their inclusion criteria, providing 476 unique utilities for breast cancer health states. Where possible, mean utility estimates were pooled using ordinary least squares, with utilities clustered within study group and weighted by both number of respondents and inverse of the variance of each utility. Regressions included controls for disease state, utility assessment method and other features of study design. Results Utility values found in the review are summarised for six categories: 1) screening related states, 2) preventative states, 3) adverse events in breast cancer and its treatment, 4) non-specific breast cancer, 5) metastatic breast cancer states and 6) early breast cancer states. Pooled utility values for the latter two categories are estimated, showing base state utility values of between 0.668 and 0.782 for early breast cancer and 0.721 and 0.806 metastatic breast cancer depending upon which model is used. Utilities were found to vary significantly by valuation method, and who conducted the valuation. Conclusions A large number of utility values for breast cancer is available in the literature; the states which these refer to are often complex, making pooling of values problematic. The impacts upon quality of life and length of life are both important to the assessment of treatments for breast cancer. These outcomes can be combined using the health-related quality of life measure of a QALY (quality adjusted life year). QALYs may be thought of as a "utility" score, since they represent people’s preferences towards a particular health state, where 0 represents dead and 1 represents full health. Being able to locate any health state on a 0 to 1 scale allows an estimation of the number of QALYs a treatment brings, and, subsequently, a comparison of the cost per QALY benefit across different treatments. The cost per QALY of competing treatments can be a useful input into medical decision making and priority setting. Cost per QALY for breast cancer treatments may be derived from primary research, or from modelling interventions at different disease stages. Where modelling is conducted, modellers require a "utility" value for each possible health state: e.g. newly diagnosed breast cancer, currently undergoing chemotherapy, and experiencing some toxicity from treatment. This allows them to map the profile of hypothetical patients as they pass through different scenarios and understand the QALYs gained from alternative treatments. There are numerous studies which have investigated the utility values associated with breast cancer; unfortunately, they show considerable variation in results. For example, values for metastatic breast cancer (MBC) range from -0.52 to 0.882. What explains this variation? First, there are a number of different health states which an individual with MBC may experience relating to different treatment regimes, different responses to treatment and different possible side-effects of treatment. Secondly, there are different methods for generating utility scores, which can generate different values for the exact same health state. This study aims to systematically review health state utility values (HSUVs) for breast cancer (early and metastatic) in order to identify all breast cancer HSUVs in the current literature. It then seeks to provide a pooled estimate of HSUVs for each identifiable health state within breast cancer. It also seeks to understand the impact of different methodological techniques on the estimates of utility scores for breast cancer. This will generate a list of HSUVs that can be used in future economic evaluations, and offer greater understanding of how representative individual utility estimates are for breast cancer states.

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    Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 29950.

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    Date of creation: 2010
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    Handle: RePEc:pra:mprapa:29950
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    1. Brazier, John & Ratcliffe, Julie & Salomon, Joshua A. & Tsuchiya, Aki, 2007. "Measuring and Valuing Health Benefits for Economic Evaluation," OUP Catalogue, Oxford University Press, number 9780198569824, July.
    2. D. Stratmann-Schoene & T. Kuehn & R. Kreienberg & R. Leidl, 2006. "A preference-based index for the SF-12," Health Economics, John Wiley & Sons, Ltd., vol. 15(6), pages 553-564.
    3. Johnston, Katharine & Brown, Jackie & Gerard, Karen & O'Hanlon, Moira & Morton, Alison, 1998. "Valuing temporary and chronic health states associated with breast screening," Social Science & Medicine, Elsevier, vol. 47(2), pages 213-222, July.
    4. Karen Gerard & Katharine Johnston & Jackie Brown, 1999. "The role of a pre-scored multi-attribute health classification measure in validating condition-specific health state descriptions," Health Economics, John Wiley & Sons, Ltd., vol. 8(8), pages 685-699.
    5. Brazier, John & Roberts, Jennifer & Deverill, Mark, 2002. "The estimation of a preference-based measure of health from the SF-36," Journal of Health Economics, Elsevier, vol. 21(2), pages 271-292, March.
    6. Hall, Jane & Gerard, Karen & Salkeld, Glenn & Richardson, Jeff, 1992. "A cost utility analysis of mammography screening in Australia," Social Science & Medicine, Elsevier, vol. 34(9), pages 993-1004, May.
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