Long-term cardiovascular risks and the impact of statin treatment on socioeconomic inequalities: a microsimulation model.

Markov microsimulation model cardiovascular disease individual patient characteristics inequality quality-adjusted life years socioeconomic status

Journal

The British journal of general practice : the journal of the Royal College of General Practitioners
ISSN: 1478-5242
Titre abrégé: Br J Gen Pract
Pays: England
ID NLM: 9005323

Informations de publication

Date de publication:
19 Feb 2024
Historique:
received: 22 04 2023
accepted: 19 09 2023
medline: 20 2 2024
pubmed: 20 2 2024
entrez: 19 2 2024
Statut: aheadofprint

Résumé

UK cardiovascular disease (CVD) incidence and mortality have declined in recent decades but socioeconomic inequalities persist. To present a new CVD model, and project health outcomes and the impact of guideline-recommended statin treatment across quintiles of socioeconomic deprivation in the UK. A lifetime microsimulation model was developed using 117 896 participants in 16 statin trials, 501 854 UK Biobank (UKB) participants, and quality-of-life data from national health surveys. A CVD microsimulation model was developed using risk equations for myocardial infarction, stroke, coronary revascularisation, cancer, and vascular and non-vascular death, estimated using trial data. The authors calibrated and further developed this model in the UKB cohort, including further characteristics and a diabetes risk equation, and validated the model in UKB and Whitehall II cohorts. The model was used to predict CVD incidence, life expectancy, quality-adjusted life years (QALYs), and the impact of UK guideline-recommended statin treatment across socioeconomic deprivation quintiles. Age, sex, socioeconomic deprivation, smoking, hypertension, diabetes, and cardiovascular events were key CVD risk determinants. Model-predicted event rates corresponded well to observed rates across participant categories. The model projected strong gradients in remaining life expectancy, with 4-5-year (5-8 QALYs) gaps between the least and most socioeconomically deprived quintiles. Guideline-recommended statin treatment was projected to increase QALYs, with larger gains in quintiles of higher deprivation. The study demonstrated the potential of guideline-recommended statin treatment to reduce socioeconomic inequalities. This CVD model is a novel resource for individualised long-term projections of health outcomes of CVD treatments.

Sections du résumé

BACKGROUND BACKGROUND
UK cardiovascular disease (CVD) incidence and mortality have declined in recent decades but socioeconomic inequalities persist.
AIM OBJECTIVE
To present a new CVD model, and project health outcomes and the impact of guideline-recommended statin treatment across quintiles of socioeconomic deprivation in the UK.
DESIGN AND SETTING METHODS
A lifetime microsimulation model was developed using 117 896 participants in 16 statin trials, 501 854 UK Biobank (UKB) participants, and quality-of-life data from national health surveys.
METHOD METHODS
A CVD microsimulation model was developed using risk equations for myocardial infarction, stroke, coronary revascularisation, cancer, and vascular and non-vascular death, estimated using trial data. The authors calibrated and further developed this model in the UKB cohort, including further characteristics and a diabetes risk equation, and validated the model in UKB and Whitehall II cohorts. The model was used to predict CVD incidence, life expectancy, quality-adjusted life years (QALYs), and the impact of UK guideline-recommended statin treatment across socioeconomic deprivation quintiles.
RESULTS RESULTS
Age, sex, socioeconomic deprivation, smoking, hypertension, diabetes, and cardiovascular events were key CVD risk determinants. Model-predicted event rates corresponded well to observed rates across participant categories. The model projected strong gradients in remaining life expectancy, with 4-5-year (5-8 QALYs) gaps between the least and most socioeconomically deprived quintiles. Guideline-recommended statin treatment was projected to increase QALYs, with larger gains in quintiles of higher deprivation.
CONCLUSION CONCLUSIONS
The study demonstrated the potential of guideline-recommended statin treatment to reduce socioeconomic inequalities. This CVD model is a novel resource for individualised long-term projections of health outcomes of CVD treatments.

Identifiants

pubmed: 38373851
pii: BJGP.2023.0198
doi: 10.3399/BJGP.2023.0198
pmc: PMC10904120
mid: EMS188946
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Department of Health
ID : 17/140/02
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/R024227/1
Pays : United Kingdom

Informations de copyright

© The Authors.

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Auteurs

Runguo Wu (R)

Health Economics and Policy Research Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK.

Claire Williams (C)

Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Junwen Zhou (J)

Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Iryna Schlackow (I)

Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Jonathan Emberson (J)

Nuffield Department of Population Health and Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK.

Christina Reith (C)

Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Anthony Keech (A)

National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Sydney, Australia.

John Robson (J)

Clinical Effectiveness Group, Wolfson Institute of Population Health, Queen Mary University of London, London, UK.

Jane Armitage (J)

Nuffield Department of Population Health and Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK.

Alastair Gray (A)

Nuffield Department of Population Health, University of Oxford, Oxford, UK.

John Simes (J)

National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Sydney, Australia.

Colin Baigent (C)

Nuffield Department of Population Health and Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK.

Borislava Mihaylova (B)

Health Economics and Policy Research Unit, Wolfson Institute of Population Health, Queen Mary University of London, London; associate professor and senior health economist, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Classifications MeSH