Evidence mapPaperPMID 42547763Full record

ArticlePharmacoEconomics2026

External Validation of SELECT Trial-Derived Cardiovascular Risk Equations in a UK Population with Overweight or Obesity and Established Cardiovascular Disease Without Diabetes.

Felice Gragnano, Martin Bøg, Anders Bo Bojesen, Milana Ivkovic, Christopher Lübker, Francesco Fusco, Resham Baruah, Joseph Whitaker, Nia C Jenkins, Iestyn Lloyd and 3 more

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Article in PharmacoEconomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

13 authors.

Felice GragnanoDepartment of Translational Medical Sciences, University of Campania "Luigi Vanvitelli", Caserta, Italy.
Martin BøgNovo Nordisk A/S, Søborg, Denmark. AXBQ@novonordisk.com.ORCID http://orcid.org/0000-0001-6431-8307
Anders Bo BojesenNovo Nordisk A/S, Søborg, Denmark.
Milana IvkovicNovo Nordisk A/S, Søborg, Denmark.
Christopher LübkerNovo Nordisk A/S, Søborg, Denmark.
Francesco FuscoNovo Nordisk A/S, Søborg, Denmark.
Resham BaruahNovo Nordisk, London, UK.
Joseph WhitakerNovo Nordisk, London, UK.
Nia C JenkinsHealth Economics and Outcomes Research Ltd., Cardiff, UK.
Iestyn LloydHealth Economics and Outcomes Research Ltd., Cardiff, UK.
Steffan HillHealth Economics and Outcomes Research Ltd., Cardiff, UK.
Peter E WeekeNovo Nordisk A/S, Søborg, Denmark.
A Michael LincoffDepartment of Cardiovascular Medicine, Cleveland Clinic, Cleveland, OH, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth economic models, many of which rely on risk equations, often play an important role in informing local healthcare decision making for the management of obesity. Risk equations for predicting cardiovascular outcomes have previously been derived from SELECT trial data. Validation of risk equations in real-world populations can provide confidence in the accuracy and reliability of health economic models.

objectiveThe aim of this study was to validate the predicted outcomes of the novel, SELECT trial-derived cardiovascular risk equations in a real-world UK population with overweight or obesity and established CVD without diabetes using the Clinical Practice Research Datalink (CPRD) database.

methodsThe SELECT risk equations for acute coronary syndrome (ACS) and stroke were externally validated in a CPRD cohort; records were assessed between 24 October 2008 and 29 March 2021 for patients aged ≥ 45 years with body mass index (BMI) ≥ 27 kg/m

resultsThe discrimination C-indices at 4 years were 0.65 (95% confidence interval [CI] 0.64-0.65) for ACS and 0.71 (95% CI 0.71-0.71) for stroke. After re-calibration, at 4 years calibration, observed/expected ratio was 1.02 (95% CI 1.00-1.03) for ACS and 0.98 (95% CI 0.96-1.00) for stroke. Prediction accuracy was lower for those with a higher baseline risk of stroke, with over-prediction observed in these patients. For both ACS and stroke, the SELECT risk equations showed better discrimination than Framingham (ACS) (C-index 0.68 vs 0.54) and SMART-REACH (stroke) (C-index 0.74 vs 0.50).

conclusionThe recalibrated SELECT risk equations showed acceptable discrimination and good calibration when applied to a real-world population of patients with overweight or obesity and established CVD without diabetes from the CPRD database. These risk equations with calibration also demonstrated better predictive performance compared with published risk equations, supporting their use in health economic evaluations in this patient population.

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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 Socratic graph.