PHG Foundation, University of Cambridge, Cambridge, United Kingdom.
PLoS One. 2023 Oct 30;18(10):e0293576. doi: 10.1371/journal.pone.0293576. eCollection 2023.
Oesophageal cancer has significant morbidity and mortality but late diagnosis is common since early signs of disease are frequently misinterpreted. Project DELTA aims to enable earlier detection and treatment through targeted screening using a novel risk prediction algorithm for oesophageal cancer (incorporating risk factors of Barrett's oesophagus including prescriptions for acid-reducing medications (CanPredict)), together with a non-invasive, low-cost sampling device (CytospongeTM). However, there are many barriers to implementation, and this paper identifies key ethical and legal challenges to implementing these personalised prevention strategies for Barrett's oesophagus/oesophageal cancer.
To identify ethical and legal issues relevant to the deployment of a risk prediction tool for oesophageal cancer into primary care, we adopted an interdisciplinary approach, incorporating targeted informal literature reviews, interviews with expert collaborators, a multidisciplinary workshop and ethical and legal analysis.
Successful implementation raises many issues including ensuring transparency and effective risk communication; addressing bias and inequity; managing resources appropriately and avoiding exceptionalism. Clinicians will need support and training to use cancer risk prediction algorithms, ensuring that they understand how risk algorithms supplement rather than replace medical decision-making. Workshop participants had concerns about liability for harms arising from risk algorithms, including from potential bias and inequitable implementation. Determining strategies for risk communication enabling transparency but avoiding exceptionalist approaches are a significant challenge. Future challenges include using artificial intelligence to bolster risk assessment, incorporating genomics into risk tools, and deployment by non-health professional users. However, these strategies could improve detection and outcomes.
Novel pathways incorporating risk prediction algorithms hold considerable promise, especially when combined with low-cost sampling. However immediate priorities should be to develop risk communication strategies that take account of using validated risk algorithms, and to ensure equitable implementation. Resolving questions about liability for harms arising should be a longer-term objective.
食管癌具有较高的发病率和死亡率，但由于疾病早期症状常被误诊，因此诊断往往较晚。DELTA 项目旨在通过使用一种新的食管癌风险预测算法（纳入 Barrett 食管的风险因素，包括开具抑酸药物的处方（CanPredict））进行有针对性的筛查，以及使用一种非侵入性、低成本的采样设备（CytospongeTM），实现早期发现和治疗。然而，在实施过程中存在许多障碍，本文确定了实施 Barrett 食管/食管癌个性化预防策略的关键伦理和法律挑战。
为了确定与将食管癌风险预测工具部署到初级保健相关的伦理和法律问题，我们采用了跨学科方法，包括有针对性的非正式文献综述、与专家合作者的访谈、多学科研讨会以及伦理和法律分析。
成功实施会引发诸多问题，包括确保透明度和有效的风险沟通；解决偏见和不平等问题；合理管理资源，避免特殊主义。临床医生将需要支持和培训才能使用癌症风险预测算法，确保他们了解风险算法如何补充而不是替代医学决策。研讨会参与者对风险算法引起的伤害的责任表示担忧，包括潜在的偏见和不平等实施。确定风险沟通策略以实现透明度但避免特殊主义方法是一个重大挑战。未来的挑战包括使用人工智能来增强风险评估、将基因组学纳入风险工具，以及由非医疗专业人员用户进行部署。然而，这些策略可以改善检测和结果。
新型风险预测算法途径具有很大的潜力，尤其是与低成本采样相结合时。然而，当前的优先事项应该是制定风险沟通策略，考虑使用经过验证的风险算法，并确保公平实施。解决因风险算法引起的伤害责任问题应该是一个长期目标。
