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
{"title":"Feasibility of multiorgan risk prediction with routinely collected diagnostics: a prospective cohort study in the UK Biobank","authors":"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","doi":"10.1136/bmjebm-2023-112518","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":9059,"journal":{"name":"BMJ Evidence-Based Medicine","volume":null,"pages":null},"PeriodicalIF":9.0000,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMJ Evidence-Based Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1136/bmjebm-2023-112518","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
Abstract
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.