Celeste McCracken, Zahra Raisi-Estabragh, Liliana Szabo, Michele Veldsman, Betty Raman, Anya Topiwala, Adriana Roca-Fernández, Masud Husain, Steffen E Petersen, Stefan Neubauer, Thomas E Nichols
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Main outcome measures Myocardial infarction, atrial fibrillation, heart failure, stroke, all-cause dementia, chronic kidney disease, fatty liver disease, alcoholic liver disease, liver cirrhosis and liver failure. Results Using a set of predictors easily gathered at the standard primary care health check (such as the National Health Service Health Check), we demonstrate that it is feasible to simultaneously produce risk estimates for multiple disease outcomes with AUROC of 70% or greater. These predictors can be entered once into a single form and produce risk scores for stroke (AUROC 0.727, 95% CI 0.713 to 0.740), all-cause dementia (0.823, 95% CI 0.810 to 0.836), myocardial infarction (0.785, 95% CI 0.775 to 0.795), atrial fibrillation (0.777, 95% CI 0.768 to 0.785), heart failure (0.828, 95% CI 0.818 to 0.838), chronic kidney disease (0.774, 95% CI 0.765 to 0.783), fatty liver disease (0.766, 95% CI 0.753 to 0.779), alcoholic liver disease (0.864, 95% CI 0.835 to 0.894), liver cirrhosis (0.763, 95% CI 0.734 to 0.793) and liver failure (0.746, 95% CI 0.695 to 0.796). Conclusions Easily collected diagnostics can be used to assess 10-year risk across multiple disease outcomes, without the need for specialist computing or invasive biomarkers. Such an approach could increase the utility of existing data and place multiorgan risk information at the fingertips of primary care providers, thus creating opportunities for longer-term multimorbidity prevention. Additional work is needed to validate whether these findings would hold in a larger, more representative cohort outside the UK Biobank. Data may be obtained from a third party and are not publicly available. This analysis was produced under UK Biobank Access Application 59867. The data in this study are owned by the UK Biobank (www. ukbiobank.ac.uk) and legal constraints do not permit public sharing of the data. The UK Biobank, however, is open to all bona fide researchers anywhere in the world. Thus, the data used in this communication can be easily and directly accessed by applying through the UK Biobank Access Management System (www.ukbiobank.ac.uk/ register-apply). 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This study tests the feasibility of producing multiple disease risk estimates with at least 70% discrimination (area under the receiver operating curve, AUROC) within the time and information constraints of the existing primary care health check framework. Design Observational prospective cohort study Setting UK Biobank. Participants 228 240 adults from the UK population. Interventions None. Main outcome measures Myocardial infarction, atrial fibrillation, heart failure, stroke, all-cause dementia, chronic kidney disease, fatty liver disease, alcoholic liver disease, liver cirrhosis and liver failure. Results Using a set of predictors easily gathered at the standard primary care health check (such as the National Health Service Health Check), we demonstrate that it is feasible to simultaneously produce risk estimates for multiple disease outcomes with AUROC of 70% or greater. These predictors can be entered once into a single form and produce risk scores for stroke (AUROC 0.727, 95% CI 0.713 to 0.740), all-cause dementia (0.823, 95% CI 0.810 to 0.836), myocardial infarction (0.785, 95% CI 0.775 to 0.795), atrial fibrillation (0.777, 95% CI 0.768 to 0.785), heart failure (0.828, 95% CI 0.818 to 0.838), chronic kidney disease (0.774, 95% CI 0.765 to 0.783), fatty liver disease (0.766, 95% CI 0.753 to 0.779), alcoholic liver disease (0.864, 95% CI 0.835 to 0.894), liver cirrhosis (0.763, 95% CI 0.734 to 0.793) and liver failure (0.746, 95% CI 0.695 to 0.796). Conclusions Easily collected diagnostics can be used to assess 10-year risk across multiple disease outcomes, without the need for specialist computing or invasive biomarkers. Such an approach could increase the utility of existing data and place multiorgan risk information at the fingertips of primary care providers, thus creating opportunities for longer-term multimorbidity prevention. Additional work is needed to validate whether these findings would hold in a larger, more representative cohort outside the UK Biobank. Data may be obtained from a third party and are not publicly available. This analysis was produced under UK Biobank Access Application 59867. The data in this study are owned by the UK Biobank (www. ukbiobank.ac.uk) and legal constraints do not permit public sharing of the data. The UK Biobank, however, is open to all bona fide researchers anywhere in the world. Thus, the data used in this communication can be easily and directly accessed by applying through the UK Biobank Access Management System (www.ukbiobank.ac.uk/ register-apply). 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引用次数: 0
摘要
目标 尽管多病发病率不断上升,但现有的风险评估工具大多局限于单一的相关结果。本研究测试了在现有初级保健健康检查框架的时间和信息限制条件下,生成至少具有 70% 识别率(接收器工作曲线下面积,AUROC)的多种疾病风险估计值的可行性。设计 观察性前瞻性队列研究 设置英国生物数据库。参与者 228 240 名来自英国的成年人。干预措施 无。主要结果指标 心肌梗死、心房颤动、心力衰竭、中风、全因痴呆、慢性肾病、脂肪肝、酒精肝、肝硬化和肝功能衰竭。结果 我们利用在标准初级保健健康检查(如国民健康服务健康检查)中很容易收集到的一组预测因子,证明了同时生成 AUROC 为 70% 或更高的多种疾病结果的风险估计是可行的。这些预测因子只需输入一份表格,就能得出中风(AUROC 为 0.727,95% CI 为 0.713 至 0.740)、全因痴呆(0.823,95% CI 为 0.810 至 0.836)、心肌梗塞(0.785,95% CI 为 0.775 至 0.795)、心房颤动(0.777,95% CI 为 0.768 至 0.785)、心力衰竭(0.828,95% CI 0.818 至 0.838)、慢性肾病(0.774,95% CI 0.765 至 0.783)、脂肪肝(0.766,95% CI 0.753 至 0.779)、酒精性肝病(0.864,95% CI 0.835 至 0.894)、肝硬化(0.763,95% CI 0.734 至 0.793)和肝衰竭(0.746,95% CI 0.695 至 0.796)。结论 容易收集到的诊断结果可用于评估多种疾病的 10 年风险,而无需专业计算或侵入性生物标记物。这种方法可以提高现有数据的效用,让初级保健提供者触手可及多器官风险信息,从而为长期多病预防创造机会。我们还需要做更多的工作,以验证这些发现是否能在英国生物库以外的更大规模、更具代表性的人群中成立。数据可能来自第三方,不对外公开。本分析由英国生物库访问申请 59867 生成。本研究中的数据归英国生物库(www. ukbiobank.ac.uk)所有,法律限制不允许公开共享数据。不过,英国生物库向世界上任何地方的所有善意研究人员开放。因此,只要通过英国生物库访问管理系统(www.ukbiobank.ac.uk/ register-apply)提出申请,就可以方便、直接地访问本通讯中使用的数据。本研究的结果将根据英国生物库公布的退还政策退还给英国生物库。
Feasibility of multiorgan risk prediction with routinely collected diagnostics: a prospective cohort study in the UK Biobank
Objectives Despite rising rates of multimorbidity, existing risk assessment tools are mostly limited to a single outcome of interest. This study tests the feasibility of producing multiple disease risk estimates with at least 70% discrimination (area under the receiver operating curve, AUROC) within the time and information constraints of the existing primary care health check framework. Design Observational prospective cohort study Setting UK Biobank. Participants 228 240 adults from the UK population. Interventions None. Main outcome measures Myocardial infarction, atrial fibrillation, heart failure, stroke, all-cause dementia, chronic kidney disease, fatty liver disease, alcoholic liver disease, liver cirrhosis and liver failure. Results Using a set of predictors easily gathered at the standard primary care health check (such as the National Health Service Health Check), we demonstrate that it is feasible to simultaneously produce risk estimates for multiple disease outcomes with AUROC of 70% or greater. These predictors can be entered once into a single form and produce risk scores for stroke (AUROC 0.727, 95% CI 0.713 to 0.740), all-cause dementia (0.823, 95% CI 0.810 to 0.836), myocardial infarction (0.785, 95% CI 0.775 to 0.795), atrial fibrillation (0.777, 95% CI 0.768 to 0.785), heart failure (0.828, 95% CI 0.818 to 0.838), chronic kidney disease (0.774, 95% CI 0.765 to 0.783), fatty liver disease (0.766, 95% CI 0.753 to 0.779), alcoholic liver disease (0.864, 95% CI 0.835 to 0.894), liver cirrhosis (0.763, 95% CI 0.734 to 0.793) and liver failure (0.746, 95% CI 0.695 to 0.796). Conclusions Easily collected diagnostics can be used to assess 10-year risk across multiple disease outcomes, without the need for specialist computing or invasive biomarkers. Such an approach could increase the utility of existing data and place multiorgan risk information at the fingertips of primary care providers, thus creating opportunities for longer-term multimorbidity prevention. Additional work is needed to validate whether these findings would hold in a larger, more representative cohort outside the UK Biobank. Data may be obtained from a third party and are not publicly available. This analysis was produced under UK Biobank Access Application 59867. The data in this study are owned by the UK Biobank (www. ukbiobank.ac.uk) and legal constraints do not permit public sharing of the data. The UK Biobank, however, is open to all bona fide researchers anywhere in the world. Thus, the data used in this communication can be easily and directly accessed by applying through the UK Biobank Access Management System (www.ukbiobank.ac.uk/ register-apply). Results from this study will be returned to UK Biobank according to their published returns policy.
期刊介绍:
BMJ Evidence-Based Medicine (BMJ EBM) publishes original evidence-based research, insights and opinions on what matters for health care. We focus on the tools, methods, and concepts that are basic and central to practising evidence-based medicine and deliver relevant, trustworthy and impactful evidence.
BMJ EBM is a Plan S compliant Transformative Journal and adheres to the highest possible industry standards for editorial policies and publication ethics.