Evidence map›Paper›PMID 40661233›Full record

ArticleJournal of the Royal Statistical Society. Series A, (Statistics in Society)2025

Optimal risk-assessment scheduling for primary prevention of cardiovascular disease.

Francesca Gasperoni, Christopher H Jackson, Angela M Wood, Michael J Sweeting, Paul J Newcombe, David Stevens, Jessica K Barrett

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the Royal Statistical Society. Series A, (Statistics in Society), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Article
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

7 authors.

Francesca GasperoniMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0002-1713-9477
Christopher H JacksonMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
Angela M WoodCardiovascular Epidemiology Unit/Department of Public Health and Primary Care, Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0002-7937-304X
Michael J SweetingDepartment of Health Sciences, University of Leicester, Leicester, UK.ORCID https://orcid.org/0000-0003-0980-8965
Paul J NewcombeMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
David StevensLiverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool Heart & Chest Hospital, Liverpool, UK.
Jessica K BarrettMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0003-1889-9803

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this work, we introduce a personalized and age-specific net benefit function, composed of benefits and costs, to recommend optimal timing of risk assessments for cardiovascular disease (CVD) prevention. We extend the 2-stage landmarking model to estimate patient-specific CVD risk profiles, adjusting for time-varying covariates. We apply our model to data from the Clinical Practice Research Datalink, comprising primary care electronic health records from the UK. We find that people at lower risk could be recommended an optimal risk-assessment interval of 5 years or more. Time-varying risk factors are required to discriminate between more frequent schedules for high-risk people.

Indexed as

2-stage landmarking modelcardiovascular diseasenet benefitoptimal risk-assessmentstatins initiation

Identifiers

PMID40661233
PMCPMC12256122

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.