Understanding decisions to participate in genomic medicine in children's cancer care: A comparison of what influences parents, health care providers, and the general community.

BACKGROUND: The emerging role of genomically guided precision medicine in pediatric cancer care presents significant clinical, practical, and ethical challenges. We investigated the factors that influence decision-making in genomic medicine from the perspective of different stakeholders in the context of difficult-to-treat childhood cancer. METHODS: Health care providers (HCPs), parents of childhood cancer survivors, and general community members completed an online discrete choice experiment survey. Respondents considered whether to recommend (HCPs) or choose (parents/community) a genomically guided approach to pediatric cancer treatment. Respondents completed eight choice questions varying by survival benefit, prognosis, likelihood of finding a target, quality of life (QoL), HCP/parent preference, need for biopsy, cost, and who pays. Data were analyzed using a probability regression model, with findings expressed as relative importance, stated importance, and marginal willingness to pay (mWTP). RESULTS: One hundred twenty-six HCPs, 130 parents, and 531 community members participated. The probability of recommending/choosing genomically guided treatment increased significantly with better prognosis, survival benefit, improvements in QoL, and decision-making partner support. It decreased with increasing costs and if parents paid for treatment. HCPs were more responsive to all factors but were most influenced by survival outcomes, and parents and community members by QoL. In contrast to these forced choice preference results, HCPs stated they were most influenced by QoL and community members by survival. CONCLUSION: Our findings support the primacy of QoL in genomic decision-making, with some differences across stakeholders in the other factors influencing decision-making. These findings emphasize the need for high-quality information giving and communication to support genomic medicine choices.

Finding Out What Matters in Decision-Making Related to Genomics and Personalized Medicine in Pediatric Oncology: Developing Attributes to Include in a Discrete Choice Experiment.

BACKGROUND: Treatment decision-making in pediatric oncology can be complex. Recent advances in genome sequencing and novel or 'personalized' therapies potentially increases the complexity of decision-making and treatment options. OBJECTIVES: This study explored the views and experiences of healthcare providers (HCPs) and parents with respect to decision-making in difficult-to-treat cancers, including genomic decision-making. METHODS: A two-phase qualitative study was undertaken in which oncologists and nurses and parents of children with relapsed and refractory cancers were interviewed using a semi-structured interview guide. Data were analyzed thematically, with a focus on measurable themes relevant to the development of candidate attributes for a discrete choice experiment (DCE). Secondly, a review of studies that utilized stated preference experiments in the fields of genomics, medical decision-making, and pediatrics was undertaken and compared with the candidate attributes identified from interviews. RESULTS: Six candidate attributes were developed from the interview themes: clinical benefit, quality of life (QoL) including both treatment effects and functionality, likelihood of a target, cost (who pays), recommendation of HCP or extent family supported the decision, and whether a biopsy was needed. Two further candidate attributes were identified from the literature review: severity of illness and cost (dollar amount). CONCLUSIONS: This study identified eight candidate attributes that will be further validated prior to developing a DCE aimed at better understanding factors influencing decision-making related to genomic sequencing and personalized medicine. This study and the proposed DCE will contribute to improving ethical and clinical practices in the application of novel genomic technology in pediatric oncology.