Patients’ Preferences for Genomic Diagnostic Testing in Chronic Lymphocytic Leukaemia: A Discrete Choice Experiment

Article English OPEN
Buchanan, James ; Wordsworth, Sarah ; Schuh, Anna (2016)

Background Genomic information could help to reduce the morbidity effects of inappropriate treatment decisions in many disease areas, in particular cancer. However, evidence of the benefits that patients derive from genomic testing is limited. This study evaluated patient preferences for genomic testing in the context of chronic lymphocytic leukaemia (CLL). Methods We used a discrete choice experiment (DCE) survey to assess the preferences of CLL patients in the UK for genomic testing. The survey presented patients with 16 questions in which they had to choose between two possible test scenarios. Tests in these scenarios were specified in terms of six attributes, including test effectiveness, test reliability and time to receive results. Results 219 patients completed the survey (response rate 20 %). Both clinical and process-related attributes were valued by respondents. Patients were willing to pay £24 for a 1 % increase in chemotherapy non-responders identified, and £27 to reduce time to receive test results by 1 day. Patients were also willing to wait an extra 29 days for test results if an additional one-third of chemotherapy non-responders could be identified, and would tolerate a genomic test being wrong 8 % of the time to receive this information. Conclusion CLL patients value the information that could be provided by genomic tests, and prefer combinations of test characteristics that more closely reflect future genomic testing practice than current genetic testing practice. Commissioners will need to carefully consider how genomic testing is operationalised in this context if the benefits of testing are to be realised. Electronic supplementary material The online version of this article (doi:10.1007/s40271-016-0172-1) contains supplementary material, which is available to authorized users.
  • References (51)
    51 references, page 1 of 6

    1. National Institute for Health and Care Excellence. Familial breast cancer: the classification and care of women at risk of familial breast cancer in primary, secondary and tertiary care 2006. https://www.nice.org.uk/guidance/cg164.

    2. Mardis ER. The impact of next-generation sequencing technology on genetics. Trends Genet. 2008;24(3):133-41. doi:10.1016/ j.tig.2007.12.007.

    3. Ioannidis JPA, Khoury MJ. Are randomized trials obsolete or more important than ever in the genomic era? Genome Medicine. 2013;5(4):32. doi:10.1186/Gm436.

    4. Buchanan J, Wordsworth S, Schuh A. Issues surrounding the health economic evaluation of genomic technologies. Pharmacogenomics. 2013;14(15):1833-47. doi:10.2217/pgs.13.183.

    5. Foster MW, Mulvihill JJ, Sharp RR. Evaluating the utility of personal genomic information. Genet Med. 2009;11(8):570-4. doi:10.1097/GIM.0b013e3181a2743e.

    6. Veenstra DL, Piper M, Haddow JE, Pauker SG, Klein R, Richards CS, et al. Improving the efficiency and relevance of evidencebased recommendations in the era of whole-genome sequencing: an EGAPP methods update. Genet Med. 2013;15(1):14-24. doi:10.1038/gim.2012.106.

    7. Giacomini M, Miller F, O'Brien BJ. Economic considerations for health insurance coverage of emerging genetic tests. Community Genet. 2003;6(2):61-73.

    8. Grosse SD, Wordsworth S, Payne K. Economic methods for valuing the outcomes of genetic testing: beyond cost-effectiveness analysis. Genet Med. 2008;10(9):648-54. doi:10.1097/GIM. 0b013e3181837217.

    9. Mushlin AI, Mooney C, Holloway RG, Detsky AS, Mattson DH, Phelps CE. The cost-effectiveness of magnetic resonance imaging for patients with equivocal neurological symptoms. Int J Technol Assess Health Care. 1997;13(01):21-34. doi:10.1017/ S0266462300010205.

    10. de Bekker-Grob EW, Ryan M, Gerard K. Discrete choice experiments in health economics: a review of the literature. Health Econ. 2012;21(2):145-72. doi:10.1002/hec.1697.

  • Metrics
    No metrics available