Evidence map›Paper›PMID 38719437›Full record

Observational studyBMJ evidence-based medicine2024

Feasibility of multiorgan risk prediction with routinely collected diagnostics: a prospective cohort study in the UK Biobank.

Celeste McCracken, Zahra Raisi-Estabragh, Liliana Szabo, Michele Veldsman, Betty Raman, Anya Topiwala, Adriana Roca-Fernández, Masud Husain, Steffen E Petersen, Stefan Neubauer and 1 more

Abstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in BMJ evidence-based medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Celeste McCrackenDivision of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, and Oxford University Hospitals NHS Foundation Trust, Oxford, UK celeste.mccracken@cardiov.ox.ac.uk.ORCID 0000-0003-1285-2393
Zahra Raisi-EstabraghWilliam Harvey Research Institute, Queen Mary University of London, London, UK.
Liliana SzaboWilliam Harvey Research Institute, Queen Mary University of London, London, UK.
Michele VeldsmanDepartment of Experimental Psychology, University of Oxford, Oxford, UK.
Betty RamanDivision of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, and Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Anya TopiwalaBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Adriana Roca-FernándezPerspectum Ltd, Oxford, UK.
Masud HusainDepartment of Experimental Psychology, University of Oxford, Oxford, UK.
Steffen E PetersenWilliam Harvey Research Institute, Queen Mary University of London, London, UK.
Stefan NeubauerDivision of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, and Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Thomas E NicholsBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Funding

Spatial inference methods for image analysisR01EB026859 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SCHWARTZMAN, ARMIN · 2019 to 2022
$1.7M
Medical Research Council MC_PC_20058NIBIB NIH HHS R01 EB026859NIHR National Institues of Health Research & Oxford Biomedical Research Centre BRC-1215-20014Wellcome TrustWellcome Trust 100309/Z/12/ZWellcome Trust 206330/Z/17/ZWellcome Trust & NIHR National Institutes of Health & Oxford BRC 203141/Z/16/Z
6 · The paper itself

Abstract

objectivesDespite 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.

designObservational prospective cohort study

settingUK Biobank.

participants228 240 adults from the UK population.

interventionsNone.

main outcome measuresMyocardial infarction, atrial fibrillation, heart failure, stroke, all-cause dementia, chronic kidney disease, fatty liver disease, alcoholic liver disease, liver cirrhosis and liver failure.

resultsUsing 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).

conclusionsEasily 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.

Indexed as

Feasibility StudiesAdultAgedBiological Specimen BanksDementiaFemaleHumansMaleMiddle AgedProspective StudiesRisk AssessmentRisk FactorsROC CurveStrokeUK BiobankUnited KingdomGeneral PracticePRIMARY CAREPrimary Healthcare

Identifiers

PMID38719437
PMCPMC11503151

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.