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      Should germline genome editing be allowed? The effect of treatment characteristics on public acceptability

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          Abstract

          STUDY QUESTION

          To what extent do characteristics of germline genome editing (GGE) determine whether the general public supports permitting the clinical use of GGE?

          SUMMARY ANSWER

          The risk that GGE would cause congenital abnormalities had the largest effect on support for allowing GGE, followed by effectiveness of GGE, while costs, the type of application (disease or enhancement) and the effect on child well-being had moderate effects.

          WHAT IS KNOWN ALREADY

          Scientific progress on GGE has increased the urgency of resolving whether and when clinical application of GGE may be ethically acceptable. Various expert bodies have suggested that the treatment characteristics will be key in determining whether GGE is acceptable. For example, GGE with substantial risks (e.g. 15% chance of a major congenital abnormality) may be acceptable to prevent a severe disease but not to enhance non-medical characteristics or traits of an otherwise healthy embryo (e.g. eye colour or perhaps in the future more complex traits, such as intelligence). While experts have called for public engagement, it is unclear whether and how much the public acceptability of GGE is affected by the treatment characteristics proposed by experts.

          STUDY DESIGN, SIZE, DURATION

          The vignette-based survey was disseminated in 2018 among 1857 members of the Dutch general public. An online research panel was used to recruit a sample representing the adult Dutch general public.

          PARTICIPANTS/MATERIALS, SETTING, METHODS

          A literature review identified the key treatment characteristics of GGE: the effect on the well-being of the future child, use for disease or enhancement, risks for the future child, effectiveness (here defined as the chance of a live birth, assuming that if the GGE was not successful, the embryo would not be transferred), cost and availability of alternative treatments/procedures to prevent the genetic disease or provide enhancement (i.e. preimplantation genetic testing (PGT)), respectively. For each treatment characteristic, 2–3 levels were defined to realistically represent GGE and its current alternatives, donor gametes and ICSI with PGT. Twelve vignettes were created by fractional factorial design. A multinominal logit model assessed how much each treatment characteristic affected participants’ choices.

          MAIN RESULTS AND THE ROLE OF CHANCE

          The 1136 respondents (response rate 61%) were representative of the Dutch adult population in several demographics. Respondents were between 18 and 89 years of age. When no alternative treatment/procedure is available, the risk that GGE would cause (other) congenital abnormalities had the largest effect on whether the Dutch public supported allowing GGE (coefficient = −3.07), followed by effectiveness (coefficient = 2.03). Costs (covered by national insurance, coefficient = −1.14), the type of application (disease or enhancement; coefficient = −1.07), and the effect on child well-being (coefficient = 0.97) had similar effects on whether GGE should be allowed. If an alternative treatment/procedure (e.g. PGT) was available, participants were not categorically opposed to GGE, however, they were strongly opposed to using GGE for enhancement (coefficient = −3.37). The general acceptability of GGE was higher than participants’ willingness to personally use it (P < 0.001). When participants considered whether they would personally use GGE, the type of application (disease or enhancement) was more important, whereas effectiveness and costs (covered by national insurance) were less important than when they considered whether GGE should be allowed. Participants who were male, younger and had lower incomes were more likely to allow GGE when no alternative treatment/procedure is available.

          LIMITATIONS, REASONS FOR CAUTION

          Some (e.g. ethnic, religious) minorities were not well represented. To limit complexity, not all characteristics of GGE could be included (e.g. out-of-pocket costs), therefore, the views gathered from the vignettes reflect only the choices presented to the respondents. The non-included characteristics could be connected to and alter the importance of the studied characteristics. This would affect how closely the reported coefficients reflect ‘real-life’ importance.

          WIDER IMPLICATIONS OF THE FINDINGS

          This study is the first to quantify the substantial impact of GGE’s effectiveness, costs (covered by national insurance), and effect on child well-being on whether the public considered GGE acceptable. In general, the participants were strikingly risk-averse, in that they weighed the risks of GGE more heavily than its benefits. Furthermore, although only a single study in one country, the results suggests that—if sufficiently safe and effective—the public may approve of using GGE (presumably combined with PGT) instead of solely PGT to prevent passing on a disease. The reported public views can serve as input for future consideration of the ethics and governance of GGE.

          STUDY FUNDING/COMPETING INTEREST(S)

          Young Academy of the Royal Dutch Academy of Sciences (UPS/RB/745), Alliance Grant of the Amsterdam Reproduction and Development Research Institute (2017–170116) and National Institutes of Health Intramural Research Programme. No competing interests.

          TRIAL REGISTRATION NUMBER

          N/A.

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          Most cited references61

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          The framing of decisions and the psychology of choice

          The psychological principles that govern the perception of decision problems and the evaluation of probabilities and outcomes produce predictable shifts of preference when the same problem is framed in different ways. Reversals of preference are demonstrated in choices regarding monetary outcomes, both hypothetical and real, and in questions pertaining to the loss of human lives. The effects of frames on preferences are compared to the effects of perspectives on perceptual appearance. The dependence of preferences on the formulation of decision problems is a significant concern for the theory of rational choice.
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            Conjoint analysis applications in health--a checklist: a report of the ISPOR Good Research Practices for Conjoint Analysis Task Force.

            The application of conjoint analysis (including discrete-choice experiments and other multiattribute stated-preference methods) in health has increased rapidly over the past decade. A wider acceptance of these methods is limited by an absence of consensus-based methodological standards. The International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Good Research Practices for Conjoint Analysis Task Force was established to identify good research practices for conjoint-analysis applications in health. The task force met regularly to identify the important steps in a conjoint analysis, to discuss good research practices for conjoint analysis, and to develop and refine the key criteria for identifying good research practices. ISPOR members contributed to this process through an extensive consultation process. A final consensus meeting was held to revise the article using these comments, and those of a number of international reviewers. Task force findings are presented as a 10-item checklist covering: 1) research question; 2) attributes and levels; 3) construction of tasks; 4) experimental design; 5) preference elicitation; 6) instrument design; 7) data-collection plan; 8) statistical analyses; 9) results and conclusions; and 10) study presentation. A primary question relating to each of the 10 items is posed, and three sub-questions examine finer issues within items. Although the checklist should not be interpreted as endorsing any specific methodological approach to conjoint analysis, it can facilitate future training activities and discussions of good research practices for the application of conjoint-analysis methods in health care studies. Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
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              Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force.

              Conjoint analysis is a stated-preference survey method that can be used to elicit responses that reveal preferences, priorities, and the relative importance of individual features associated with health care interventions or services. Conjoint analysis methods, particularly discrete choice experiments (DCEs), have been increasingly used to quantify preferences of patients, caregivers, physicians, and other stakeholders. Recent consensus-based guidance on good research practices, including two recent task force reports from the International Society for Pharmacoeconomics and Outcomes Research, has aided in improving the quality of conjoint analyses and DCEs in outcomes research. Nevertheless, uncertainty regarding good research practices for the statistical analysis of data from DCEs persists. There are multiple methods for analyzing DCE data. Understanding the characteristics and appropriate use of different analysis methods is critical to conducting a well-designed DCE study. This report will assist researchers in evaluating and selecting among alternative approaches to conducting statistical analysis of DCE data. We first present a simplistic DCE example and a simple method for using the resulting data. We then present a pedagogical example of a DCE and one of the most common approaches to analyzing data from such a question format-conditional logit. We then describe some common alternative methods for analyzing these data and the strengths and weaknesses of each alternative. We present the ESTIMATE checklist, which includes a list of questions to consider when justifying the choice of analysis method, describing the analysis, and interpreting the results.
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                Author and article information

                Journal
                Human Reproduction
                Oxford University Press (OUP)
                0268-1161
                1460-2350
                February 01 2021
                January 25 2021
                November 26 2020
                February 01 2021
                January 25 2021
                November 26 2020
                : 36
                : 2
                : 465-478
                Affiliations
                [1 ]Department of Obstetrics and Gynecology, Center for Reproductive Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam 1105 AZ, The Netherlands
                [2 ]Department of Clinical Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands
                [3 ]Department of Bioethics, Clinical Center, National Institutes of Health, Bethesda, MD 20814, USA
                [4 ]Department of Medical Humanities, Julius Center, University Medical Center Utrecht, Utrecht 3584 CG, The Netherlands
                [5 ]Amsterdam School of Communications Research, University of Amsterdam, Amsterdam 1018 WV, The Netherlands
                Article
                10.1093/humrep/deaa212
                aea3172a-7a70-48a4-b34a-1ac7d438f7cd
                © 2020

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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