Quality of life drives patients' preferences for secondary findings from genomic sequencing
AuthorMighton, C; Carlsson, L; Clausen, M; Casalino, S; Shickh, S; McCuaig, L; Joshi, E; Panchal, S; Semotiuk, K; Ott, K; ...
Source TitleEuropean Journal of Human Genetics
PublisherNATURE PUBLISHING GROUP
University of Melbourne Author/sBaxter, Nancy
AffiliationMelbourne School of Population and Global Health
Document TypeJournal Article
CitationsMighton, C., Carlsson, L., Clausen, M., Casalino, S., Shickh, S., McCuaig, L., Joshi, E., Panchal, S., Semotiuk, K., Ott, K., Elser, C., Eisen, A., KiM, R. H., Lerner-Ellis, J., Carroll, J. C., Glogowski, E., Schrader, K. & Bombard, Y. (2020). Quality of life drives patients' preferences for secondary findings from genomic sequencing. EUROPEAN JOURNAL OF HUMAN GENETICS, 28 (9), pp.1178-1186. https://doi.org/10.1038/s41431-020-0640-x.
Access StatusAccess this item via the Open Access location
Open Access URLhttps://europepmc.org/articles/PMC7609335?pdf=render
There is growing impetus to include measures of personal utility, the nonmedical value of information, in addition to clinical utility in health technology assessment (HTA) of genomic tests such as genomic sequencing (GS). However, personal utility and clinical utility are challenging to define and measure. This study aimed to explore what drives patients' preferences for hypothetically learning medically actionable and non-medically actionable secondary findings (SF), capturing clinical and personal utility; this may inform development of measures to evaluate patient outcomes following return of SF. Semi-structured interviews were conducted with adults with a personal or family cancer history participating in a trial of a decision aid for selection of SF from genomic sequencing (GS) ( www.GenomicsADvISER.com ). Interviews were analyzed thematically using constant comparison. Preserving health-related and non-health-related quality of life was an overarching motivator for both learning and not learning SF. Some participants perceived that learning SF would help them "have a good quality of life" through informing actions to maintain physical health or leading to psychological benefits such as emotional preparation for disease. Other participants preferred not to learn SF because results "could ruin your quality of life," such as by causing negative psychological impacts. Measuring health-related and non-health-related quality of life may capture outcomes related to clinical and personal utility of GS and SF, which have previously been challenging to measure. Without appropriate measures, generating and synthesizing evidence to evaluate genomic technologies such as GS will continue to be a challenge, and will undervalue potential benefits of GS and SF.
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