Quality of life drives patients' preferences for secondary findings from genomic sequencing.
Journal
European journal of human genetics : EJHG
ISSN: 1476-5438
Titre abrégé: Eur J Hum Genet
Pays: England
ID NLM: 9302235
Informations de publication
Date de publication:
09 2020
09 2020
Historique:
received:
28
11
2019
accepted:
14
04
2020
revised:
31
03
2020
pubmed:
20
5
2020
medline:
3
6
2021
entrez:
20
5
2020
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 32424322
doi: 10.1038/s41431-020-0640-x
pii: 10.1038/s41431-020-0640-x
pmc: PMC7609335
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1178-1186Subventions
Organisme : NCI NIH HHS
ID : P30 CA008748
Pays : United States
Organisme : CIHR
ID : FRN #160968
Pays : Canada
Organisme : CIHR
ID : FRN GSD-164222
Pays : Canada
Investigateurs
Yvonne Bombard Pi
(Y)
Susan Randall Armel
(SR)
Melyssa Aronson
(M)
Nancy Baxter
(N)
Ken Bond
(K)
José-Mario Capo-Chichi
(JM)
June C Carroll
(JC)
Timothy Caulfield
(T)
Marc Clausen
(M)
Tammy J Clifford
(TJ)
Iris Cohn
(I)
Irfan Dhalla
(I)
Craig C Earle
(CC)
Andrea Eisen
(A)
Christine Elser
(C)
Mike Evans
(M)
Emily Glogowski
(E)
Tracy Graham
(T)
Jada G Hamilton
(JG)
Wanrudee Isaranuwatchai
(W)
Monika Kastner
(M)
Raymond H Kim
(RH)
Andreas Laupacis
(A)
Jordan Lerner-Ellis
(J)
Chantal F Morel
(CF)
Michelle Mujoomdar
(M)
Kenneth Offit
(K)
Seema Panchal
(S)
Mark Robson
(M)
Stephen W Scherer
(SW)
Adena Scheer
(A)
Kasmintan Schrader
(K)
Terrence Sullivan
(T)
Kevin E Thorpe
(KE)
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