Access to Genetic Information Leveraging Innovative Technology (AGILITY) Study

项目概要/摘要 利用创新技术获取遗传信息（Access to Genetic Information Leveling Innovative Technology，AGESTIC） 实现精准医疗的挑战。这包括有限的遗传咨询工作人员， 测试决定，以及在获得基因检测方面存在的不公平现象。为了应对这些挑战，我们将 进行1型混合试验，包括三个具体目标。第一个目标是利用现有的临床 遗传学聊天机器人，并将其用于人群筛选可能导致遗传性疾病的基因变异 乳腺癌和卵巢癌综合征、林奇综合征和家族性高胆固醇血症。由于 变异的流行率和采取行动减少负面结果的选择，10个基因已经被 由美国国家医学院和美国医学院批准用于人群筛查 遗传学为了验证目标人群的聊天机器人，我们将使用来自初级保健访谈的数据。 患者和提供者了解信息需求，以实现知情的测试决策。一旦聊天机器人 第二个目标是进行一项虚拟实施的随机对照试验， 照顾不同背景的病人。我们将测试聊天机器人的非劣效性， 标准遗传咨询我们计划招募2,400名成年参与者，来自五个种族，民族和 社会经济多样化的初级保健诊所在佛罗里达大学卫生系统。患者将 如果筛选条件没有更高的风险，则有资格入组试验。[风险较高的人 将有机会接受有针对性的基因检测，这是护理标准，并作为一个 描述性研究组]参与者将被随机分配，通过临床聊天机器人或遗传学机器人了解测试。 律师我们的主要成果是关于接受基因检测的知情选择。因此，那些 拒绝测试和接受测试的人一样有用。次要结果包括测试相关的痛苦， 决策冲突和测试吸收。知情选择将在作出决定后立即进行评估， 接受检测者在收到结果后，所有参与者在3个月和6个月后。确保 为了成功进行AGRENT试验，RTI国际的研究人员将与高级副院长 佛罗里达大学的研究、初级保健提供者、患者和社区咨询委员会 卫生系统制定招聘、参与和保留战略。第三个目标是进行一项 临床聊天机器人的实施评估作为优化遗传咨询的干预措施， 影响知情决策，并促进人口筛查。为此，我们将分析 与参与者、遗传咨询师和参与试验的初级保健提供者进行访谈，使用 为执行工作提供信息的公认办法。该研究将提供证据，支持 可行的解决方案，以解决如何提供强大的和可扩展的遗传咨询的关键问题 在常规临床护理中的应用。

PROJECT SUMMARY/ABSTRACT The AGILITY (Access to Genetic Information Leveraging Innovative TechnologY) trial will assess layered challenges in realizing precision medicine. This includes a limited genetic counseling workforce to facilitate test decisions, and existing inequities in access to genetic testing. To address these challenges, we will conduct a Type1 Hybrid Trial that includes three specific aims. The first aim is to take an existing clinical genetics chatbot and tailor it for use in population screening of gene variants that can lead to Hereditary Breast and Ovarian Cancer syndromes, Lynch Syndrome, and Familial Hypercholesterolemia. Due to the prevalence of the variants and options for taking actions to reduce negative outcomes, 10 genes have been endorsed for population screening by the National Academy of Medicine and the American College of Medical Genetics. To validate the chatbot for the target population, we will use data from interviews with primary care patients and providers to learn the informational needs to achieve informed test decisions. Once the chatbot is validated, the second aim is to conduct a virtually-implemented randomized controlled trial with primary care patients from a variety of backgrounds. We will test non-inferiority of the chatbot in comparison to standard genetic counseling. We plan to enroll 2,400 adult participants from five racially, ethnically and socioeconomically diverse primary care clinics at the University of Florida Health System. Patients will be eligible to enroll in the trial if they have no higher risks for the screening conditions. [Those with higher risks will be offered the opportunity to undergo targeted genetic testing as is standard of care, and followed as a descriptive study arm.] Participants will be randomized to learn about testing via a clinical chatbot or a genetic counselor. Our primary outcome is informed choice about undergoing genetic testing. As such, those who decline testing are as informative as those who accept. Secondary outcomes include test-related distress, decisional conflict, and testing uptake. Informed choice will be assessed immediately following the decision, after receipt of results for those who accept testing, and 3 and 6 months later for all participants. To ensure success of the AGILITY Trial, investigators at RTI International will work with the Senior Associate Dean of Research, primary care providers, patients and the community advisory board at the University of Florida Health System to develop recruitment, engagement, and retention strategies. The third aim is to conduct an implementation assessment of the clinical chatbot as an intervention to optimize genetic counseling without compromising informed decision-making and to facilitate population screening. To do so, we will analyze interviews with participants, genetic counselors, and primary care providers participating in the trial, using recognized approaches to inform implementation. The AGILITY study will provide evidence in support of workable solutions to address the critical issue of how to provide robust and scalable genetic counseling around predictive genomics in routine clinical care.