Dennison Rebecca, Morris Stephen, Clune Reanna J, Wright Stuart, Waller Jo, Usher-Smith Juliet
Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
BMJ Open. 2025 May 31;15(5):e093803. doi: 10.1136/bmjopen-2024-093803.
To understand the importance and potential impact on uptake of different attributes of risk-based innovations in the context of risk-stratified healthcare for cancer screening and symptomatic diagnosis.
The online survey comprised a discrete choice experiment (DCE) in which participants chose between two risk assessment options or to opt out of risk stratification. There were six attributes: test method, type (genetic or non-genetic), location, frequency, sensitivity and specificity. Participants were randomly allocated to consider the choice in an asymptomatic or symptomatic context.
Members of the public in the UK.
1202 participants completed the DCE.
Conditional logistic regression and latent class analysis informed modelling of predicted preferences for a range of innovations with different features.
Overall, participants preferred risk assessments over opting out and prioritised sensitivity, with test method and specificity also important. Genetic and non-invasive tests were favoured. With sensitivity and specificity of 80% or better, participants would be more likely to take up a risk assessment than not. Comparing the asymptomatic and symptomatic contexts, 65% and 73% of participants would be very likely to participate regardless of the innovation used, and 29% and 13% of participants might participate depending on the method, sensitivity and specificity. A minority showed strong dislike of risk-based innovations, particularly within screening.
There are high levels of public support for risk-based innovations within risk-stratified cancer healthcare, especially for referral decision-making and using genetic and non-invasive tests. Optimising risk-based innovations is needed to engage those whose participation is contingent on test methods and performance metrics.
了解在癌症筛查和症状诊断的风险分层医疗背景下，不同基于风险的创新属性对采用率的重要性和潜在影响。
在线调查包括一个离散选择实验（DCE），参与者在两种风险评估选项之间进行选择，或选择不进行风险分层。有六个属性：检测方法、类型（基因或非基因）、地点、频率、敏感性和特异性。参与者被随机分配在无症状或有症状的情况下考虑选择。
英国公众成员。
1202名参与者完成了DCE。
条件逻辑回归和潜在类别分析为一系列具有不同特征的创新的预测偏好建模提供了依据。
总体而言，参与者更喜欢风险评估而非选择退出，并将敏感性列为优先考虑因素，检测方法和特异性也很重要。基因检测和非侵入性检测更受青睐。当敏感性和特异性达到80%或更高时，参与者进行风险评估的可能性更大。比较无症状和有症状的情况，无论采用何种创新，65%和73%的参与者很可能会参与，29%和13%的参与者可能会根据方法、敏感性和特异性参与。少数人对基于风险的创新表现出强烈反感，尤其是在筛查方面。
在风险分层的癌症医疗中，公众对基于风险的创新有很高的支持度，特别是在转诊决策以及使用基因检测和非侵入性检测方面。需要优化基于风险的创新，以吸引那些参与取决于检测方法和性能指标的人群。
