Societal preferences for the return of incidental findings from clinical genomic sequencing: a discrete-choice experiment

Regier, Dean A.; Peacock, Stuart; Pataky, Reka; Hoek, Kimberly van der; Jarvik, Gail P.; Hoch, Jeffrey S.

doi:10.1503/cmaj.140697

Cited by 79 publications

(77 citation statements)

References 32 publications

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“…20 In a scenario that explores willingness-to-pay for information that may or may not be actionable, mean willingness-to-pay was $280. 20 These methods were different from our study, and willingness-to-pay was greater than our findings, but similar in magnitude.…”

Section: Discussionmentioning

confidence: 99%

“…17–20 However, there is limited evidence on willingness-to-pay for WGS information depending on whether or not that information is medically actionable, or who should decide what results are included and returned in a WGS report. In this study, we elicit preferences for who defines which WGS results are included in a WGS report to help inform health policy, and estimate the value of WGS information using contingent valuation methods to elicit willingness-to-pay in a nationally representative sample of adults from the United States general population.…”

Section: Introductionmentioning

confidence: 99%

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What are people willing to pay for whole-genome sequencing information, and who decides what they receive?

Marshall

Gonzalez

MacDonald

et al. 2016

Genetics in Medicine

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PURPOSE Whole genome sequencing (WGS) can be used as a powerful diagnostic tool which could also be used for screening but may generate anxiety, unnecessary testing and overtreatment. Current guidelines suggest reporting clinically actionable secondary findings when diagnostic testing is performed. We estimated preferences for receiving WGS results. METHODS A US nationally representative survey (n=410 adults) was used to rank preferences for who decides (expert panel, your doctor, you) which WGS results are reported. We estimated the value of information about variants with varying levels of clinical usefulness using willingness-to-pay contingent valuation questions. RESULTS 43% preferred to decide themselves what information is included in the WGS report. 38% (95% CI:33–43%) would not pay for actionable variants, and 3% (95% CI:1–5%) would pay more than $1000. 55% (95% CI:50–60%) would not pay for variants in which medical treatment is currently unclear, and 7% (95% CI:5–9%) would pay more than $400. CONCLUSION Most people prefer to decide what WGS results are reported. Despite valuing actionable information more, some respondents perceive that genetic information could negatively impact them. Preference heterogeneity for WGS information should be considered in the development of policies, particularly to integrate patient preferences with personalized medicine and shared decision making.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

What are people willing to pay for whole-genome sequencing information, and who decides what they receive?

Marshall

Gonzalez

MacDonald

et al. 2016

Genetics in Medicine

View full text Add to dashboard Cite

show abstract

“…[14] The study uses 5 attributes, Disease risk, Disease treatability, Disease severity, Carrier status, and Cost to you. The first 4 of these attributes are similar to our attributes of Risk, Possibility of treatment, Severity of disease, and Reproductive relevance.…”

Section: Discussionmentioning

confidence: 99%

Clinical genome sequencing and population preferences for information about ‘incidental’ findings—From medically actionable genes (MAGs) to patient actionable genes (PAGs)

Ploug

Holm

2017

PLoS ONE

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Whole genome or exome sequencing is increasingly used in the clinical contexts, and ‘incidental’ findings are generated. There is need for an adequate policy for the reporting of these findings to individuals. Such a policy has been suggested by the American College of Medical Genetics and Genomics (ACMG). We argue that ACMG’s policy is overly paternalistic, and that an adequate policy must take into account population preferences. We conducted a choice based conjoint survey of population preferences for reporting in a representative sample of the Danish population. In a 12 task survey respondents were asked about their preference for reporting in relation to three scenarios with seven different attributes. Of 1200 respondents 66.4% participated. We show that population preferences for reporting differs from ACMG’s recommendations, and suggest a new policy based on both medically and patient actionable genes.

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“…Reporting secondary findings that are currently determined to have unclear medical treatment could generate anxiety and unnecessary medical tests, but patients could miss valuable information if not reported. [22] Further, acting on findings prematurely could result in harm from potential overtreatment and unnecessary healthcare resource use. [26, 27] However, individuals may prefer to learn about these findings to reassess personal priorities and/or get affairs in order if their chance of death is increased (changes in bequest values), or they may hope information on long-term risk becomes actionable in the future (option values).…”

Section: Problem Complexity and Proposed Solutionsmentioning

confidence: 99%

“…[17, 18] Previous research suggests that individuals, regardless of health status, value having choices about the WGS information they receive. [19-22] The initial decision to acquire WGS information involves assessing whether a broad set of uncertain outcomes, including both the WGS findings and willingness to act on the information received, is likely to offer enough benefit to justify the cost of sequencing. We used contingent valuation (CV) questions to determine the value of WGS information at the initial decision to undergo WGS.…”

Section: Introductionmentioning

confidence: 99%

Estimating Preferences for Complex Health Technologies: Lessons Learned and Implications for Personalized Medicine

2017

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We examine key study design challenges of using stated-preference methods to estimate the value of whole genome sequencing (WGS) as a specific example of genomic testing. Assessing the value of WGS is complex because WGS provides multiple findings, some of which can be incidental in nature and unrelated to the specific health concerns that motivated the test. Additionally, WGS results can include actionable findings (variants considered to be clinically useful and can be acted on), findings for which evidence for best clinical action is not available (variants considered clinically valid but do not meet as high of a standard for clinical usefulness), and findings of unknown significance. We consider three key challenges encountered in designing our national study on the value of WGS – layers of uncertainty, potential downstream consequences with endogenous aspects, and both positive and negative utility associated with testing information – and potential solutions as strategies to address these challenges. We conceptualized the decision to acquire WGS information as a series of sequential choices that are resolved separately: a) To determine the value of WGS information at the initial decision to undergo WGS, we used a contingent valuation questions, and b) to elicit respondent preferences for reducing risks of health problems and the consequences of taking the steps to reduce these risks, we used a discrete choice experiment. We conclude by considering the implications for evaluating the value of other complex health technologies that involve multiple forms of uncertainty.

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Societal preferences for the return of incidental findings from clinical genomic sequencing: a discrete-choice experiment

Cited by 79 publications

References 32 publications

What are people willing to pay for whole-genome sequencing information, and who decides what they receive?

What are people willing to pay for whole-genome sequencing information, and who decides what they receive?

Clinical genome sequencing and population preferences for information about ‘incidental’ findings—From medically actionable genes (MAGs) to patient actionable genes (PAGs)

Estimating Preferences for Complex Health Technologies: Lessons Learned and Implications for Personalized Medicine

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