What is the best way for healthcare professionals to communicate changes in estimated risk of breast cancer?

乳腺癌等常见多因素疾病的风险估计模型经常被用于家族史诊所，以告知有关预防选择的决定。它们的使用正在增加，例如，在PROCAS研究中为58，000名参加常规乳房筛查的妇女提供了风险估计（1）。在临床实践中使用这些风险估计模型的一个挑战是，由于几个原因，个体的风险估计可能会发生变化。首先，风险估计算法的新版本，例如，更新了Tyrer-Cuzick模型。第二，这些模型可以包括更多的信息来源：历史上，它们是基于自我报告的家族史和与生育相关的因素，例如奇偶性。它们现在可以包括有关乳腺密度和单核苷酸多态性（SNP）的信息（2）。第三，乳腺癌终生风险的估计值随着年龄的增长而下降，因为每个人在以后的时间点上都更老。变化的程度可能很大。在家族史风险（FH风险）研究中，914名曼彻斯特妇女在1993-2010年间接受了风险评估。他们被告知他们的风险是“高”，“中等”，“平均”或“低于平均水平”;高或中等风险的妇女被提供预防选择，即加强筛查或化学预防（3）。106名女性的子样本使用最新版本的Tyrer-Cuzick模型重新评估了他们的风险，包括乳房X线摄影密度和18个SNP。在这106名妇女中，53名妇女的终生风险降低了一个或多个风险类别（例如从高到中等）。40名妇女没有改变类别，而13名妇女的风险增加。缺乏研究探索接受修订的风险估计对任何疾病的影响：范围搜索未能识别任何此类研究。虽然接受乳腺癌风险估计似乎没有什么情绪影响（4），但许多人不相信他们收到的估计（5）。接受修订的风险估计可能会进一步破坏对医疗保健专业人员的信任或风险估计的可信度，因为变化可能会产生修订的管理计划。（B）开发材料以支持涉及修订风险估计的咨询，以及（C）评估情感影响、对风险信息的理解、对医疗保健专业人员的信任，和妇女在家族史风险研究中的预防选择的观点。这项研究将产生一个证据基础，以帮助医疗保健专业人员更好地与女性沟通估计乳腺癌风险的变化，更广泛地说，改变其他疾病的风险，例如心血管疾病。(1)Evans DG等人，NHS乳腺筛查计划和家族史诊所中乳腺癌风险预测、早期检测和预防的改善：一项双队列研究。NIHR应用研究赠款计划，2016：4（11）。(2)Evans DGR等人，乳腺癌病理学和分期通过包括乳房X线摄影密度和常见遗传变异的风险分层模型更好地预测。乳腺癌研究Tr 2019; 176（1）：141-148。(3)Evans DG等人，一组18个SNP对参加英国家族筛查诊所的女性乳腺癌风险的影响：一项病例对照研究。医学遗传学杂志2017; 54（2）：111-113。(4)French DP et al.为女性提供个性化的10年乳腺癌风险估计的心理影响。英国癌症杂志2018; 118（12）：1648-1657。(5)Bayne M等（在出版中）干预措施的影响，包括提供个性化的癌症风险信息对风险感知和心理反应的准确性：系统性综述和荟萃分析。帕特·艾德·康斯DOI：10.1016/j.pec.2019/08/010

Risk estimation models for common multifactorial diseases such as breast cancer are often used, e.g. in Family History Clinics to inform decisions about prevention options. Their use is increasing, e.g. 58,000 women who attended routine breast-screening were provided risk estimates in the PROCAS study (1). A challenge for the use of these risk estimation models in clinical practice is that an individual's risk estimate can change, for several reasons. First, new versions of risk estimation algorithms, e.g., Tyrer-Cuzick model are updated. Second, these models can include more information sources: historically, they were based on self-reported family history and hormone-related factors, e.g. parity. They can now include information about breast density and Single Nucleotide Polymorphisms (SNPs) (2). Thirdly, estimates of lifetime breast cancer risk decrease with age, as each individual is older at later timepoints. The extent of change can be large. In the Family History Risk (FH-Risk) study, 914 Manchester-based women received risk estimates between 1993-2010. They were told their risk was "high", "moderate", "average" or "below average"; women at high or moderate risk were offered prevention options, i.e. enhanced screening or chemoprevention (3). A sub-sample of 106 women had their risks re-evaluated using the latest version of the Tyrer-Cuzick model, including mammographic density and 18 SNPs. Of these 106 women, the lifetime risk of 53 women decreased by one or more risk categories (e.g. from high to moderate). Forty women did not change category whilst the risk of 13 women increased. There is a dearth of research exploring the impact of receiving revised risk estimates for any disease: a scoping search failed to identify any such studies. Whilst there appears to be little emotional impact of receiving breast cancer risk estimates (4), many people do not trust the estimates they received (5). Receiving revised risk estimates may further undermine trust in healthcare professionals or credibility of risk estimation, as changes may produce revised management plans.This PhD will: (a) identify the key issues for women who receive revised risk estimates; (b) develop materials to support consultations involving revised risk estimates, and (c) assess emotional impact, understanding of risk information, trust in healthcare professionals, and views of prevention options of women in the Family History Risk study. This research will produce an evidence base to help healthcare professionals communicate better with women about changes in estimated breast cancer risk, and more widely, changing risk of other diseases, e.g. Cardiovascular Disease.(1) Evans DG et al, Improvement in risk prediction, early detection and prevention of breast cancer in the NHS Breast Screening Programme and family history clinics: a dual cohort study. NIHR Programme Grants for Applied Research, 2016: 4(11).(2) Evans DGR et al, Breast cancer pathology and stage are better predicted by risk stratification models that include mammographic density and common genetic variants. Breast Cancer Res Tr 2019; 176(1): 141-148.(3) Evans DG et al, The impact of a panel of 18 SNPs on breast cancer risk in women attending a UK familial screening clinic: a case-control study. J Med Genet. 2017; 54(2):111-113.(4) French DP et al. Psychological impact of providing women with personalised 10-year breast cancer risk estimates. Br J Cancer 2018; 118(12): 1648-1657.(5) Bayne M et al. (in press) Effect of interventions including provision of personalised cancer risk information on accuracy of risk perception and psychological responses: a systematic review and meta-analysis. Pat Ed Couns. DOI: 10.1016/j.pec.2019/08/010