Evidence map›Paper›PMID 39028718›Full record

ArticlePloS one2024

Cost-effectiveness of applying high-sensitivity troponin I to a score for cardiovascular risk prediction in asymptomatic population.

Paul Jülicher, Nataliya Makarova, Francisco Ojeda, Isabella Giusepi, Annette Peters, Barbara Thorand, Giancarlo Cesana, Torben Jørgensen, Allan Linneberg, Veikko Salomaa and 15 more

Abstract read
In one paragraph

Article in PloS one, 2024. 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

25 authors.

Paul JülicherMedical Affairs, Core Diagnostics, Abbott, Abbott Park, IL, United States of America.ORCID 0000-0002-6606-1020
Nataliya MakarovaMidwifery Science-Health Care Research and Prevention, Institute for Health Service Research in Dermatology and Nursing (IVDP), University Medical Center Hamburg-Eppendorf, Hamburg, Germany.ORCID 0000-0002-6850-7735
Francisco OjedaDepartment of General and Interventional Cardiology, University Heart and Vascular Center Hamburg, Hamburg, Germany.
Isabella GiusepiMedical Affairs, Core Diagnostics, Abbott, Abbott Park, IL, United States of America.
Annette PetersInstitute of Epidemiology, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany.
Barbara ThorandInstitute of Epidemiology, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany.
Giancarlo CesanaCentro Studi Sanità Pubblica, Università Milano Bicocca, Milan, Italy.
Torben JørgensenDepartment of Public Health, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0001-9453-2830
Allan LinnebergCenter for Clinical Research and Prevention, Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark.ORCID 0000-0002-0994-0184
Veikko SalomaaFinnish Institute for Health and Welfare, Helsinki, Finland.ORCID 0000-0001-7563-5324
Licia IacovielloDepartment of Epidemiology and Prevention, IRCCS Neuromed, Pozzilli, Italy.
Simona CostanzoDepartment of Epidemiology and Prevention, IRCCS Neuromed, Pozzilli, Italy.ORCID 0000-0003-4569-1186
Stefan SöderbergDepartment of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
Frank KeeCentre for Public Health, Queen's University of Belfast, Belfast, Northern Ireland.
Simona GiampaoliDepartment of Cardiovascular, Endocrine-metabolic Diseases and Aging, Istituto Superiore di Sanità, Rome, Italy.
Luigi PalmieriDepartment of Cardiovascular, Endocrine-metabolic Diseases and Aging, Istituto Superiore di Sanità, Rome, Italy.
Chiara DonfrancescoDepartment of Cardiovascular, Endocrine-metabolic Diseases and Aging, Istituto Superiore di Sanità, Rome, Italy.
Tanja ZellerGerman Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Kiel/Lübeck, Hamburg, Germany.
Kari KuulasmaaFinnish Institute for Health and Welfare, Helsinki, Finland.ORCID 0000-0003-2165-1411
Tarja TuovinenFinnish Institute for Health and Welfare, Helsinki, Finland.ORCID 0000-0002-9295-3516
Felicity LamrockMathematical Science Research Centre, Queen's University Belfast, Belfast, Northern Ireland, United Kingdom.
Annette Conrads-FrankDepartment of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT TIROL-University for Health Sciences and Technology, Hall in Tirol, Austria.
Paolo BrambillaDepartment of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy.
Stefan BlankenbergGerman Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Kiel/Lübeck, Hamburg, Germany.
Uwe SiebertDepartment of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT TIROL-University for Health Sciences and Technology, Hall in Tirol, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionRisk stratification scores such as the European Systematic COronary Risk Evaluation (SCORE) are used to guide individuals on cardiovascular disease (CVD) prevention. Adding high-sensitivity troponin I (hsTnI) to such risk scores has the potential to improve accuracy of CVD prediction. We investigated how applying hsTnI in addition to SCORE may impact management, outcome, and cost-effectiveness.

methodsCharacteristics of 72,190 apparently healthy individuals from the Biomarker for Cardiovascular Risk Assessment in Europe (BiomarCaRE) project were included into a discrete-event simulation comparing two strategies for assessing CVD risk. The standard strategy reflecting current practice employed SCORE (SCORE); the alternative strategy involved adding hsTnI information for further stratifying SCORE risk categories (S-SCORE). Individuals were followed over ten years from baseline examination to CVD event, death or end of follow-up. The model tracked the occurrence of events and calculated direct costs of screening, prevention, and treatment from a European health system perspective. Cost-effectiveness was expressed as incremental cost-effectiveness ratio (ICER) in € per quality-adjusted life year (QALYs) gained during 10 years of follow-up. Outputs were validated against observed rates, and results were tested in deterministic and probabilistic sensitivity analyses.

resultsS-SCORE yielded a change in management for 10.0% of individuals, and a reduction in CVD events (4.85% vs. 5.38%, p<0.001) and mortality (6.80% vs. 7.04%, p<0.001). S-SCORE led to 23 (95%CI: 20-26) additional event-free years and 7 (95%CI: 5-9) additional QALYs per 1,000 subjects screened, and resulted in a relative risk reduction for CVD of 9.9% (95%CI: 7.3-13.5%) with a number needed to screen to prevent one event of 183 (95%CI: 172 to 203). S-SCORE increased costs per subject by 187€ (95%CI: 177 € to 196 €), leading to an ICER of 27,440€/QALY gained. Sensitivity analysis was performed with eligibility for treatment being the most sensitive.

conclusionAdding a person's hsTnI value to SCORE can impact clinical decision making and eventually improves QALYs and is cost-effective compared to CVD prevention strategies using SCORE alone. Stratifying SCORE risk classes for hsTnI would likely offer cost-effective alternatives, particularly when targeting higher risk groups.

Indexed as

Cardiovascular DiseasesCost-Benefit AnalysisTroponin IAdultAgedBiomarkersEuropeFemaleHeart Disease Risk FactorsHumansMaleMiddle AgedQuality-Adjusted Life YearsRisk AssessmentBiomarkersTroponin I

Identifiers

PMID39028718
PMCPMC11259308

What Socratic 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 Socratic graph.