Evidence map›Paper›PMID 32912153›Full record

ArticleBMC medical genetics2020

Risk prediction for coronary heart disease by a genetic risk score - results from the Heinz Nixdorf Recall study.

Sonali Pechlivanis, Nils Lehmann, Per Hoffmann, Markus M Nöthen, Karl-Heinz Jöckel, Raimund Erbel, Susanne Moebus

Open access · goldAbstract read
In one paragraph

Article in BMC medical genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 14% of its field
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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

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  6. International journal of medical sciences · 2024
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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 at 3 institutions in 2 countries.

Sonali PechlivanisInstitute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany. sonali.pechlivanis@uk-essen.de.ORCID 0000-0002-6181-7044
Nils LehmannInstitute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany.
Per HoffmannDepartment of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany.
Markus M NöthenDepartment of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany.
Karl-Heinz JöckelInstitute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany.
Raimund ErbelInstitute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany.
Susanne MoebusInstitute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany.
University of Duisburg-Essen · DEUniversity of Bonn · DEEssen University Hospital · DE

Funding

Deutsche Forschungsgemeinschaft ER 155/6-1Deutsche Forschungsgemeinschaft ER 155/6-2Deutsche Forschungsgemeinschaft PE 2309/2-1
6 · The paper itself

Abstract

backgroundA Genetic risk score for coronary artery disease (CAD) improves the ability of predicting coronary heart disease (CHD). It is unclear whether i) the use of a CAD genetic risk score is superior to the measurement of coronary artery calcification (CAC) for CHD risk assessment and ii) the CHD risk assessment using a CAD genetic risk score differs between men and women.

methodsWe included 4041 participants (age-range: 45-76 years, 1919 men) of the Heinz Nixdorf Recall study without CHD or stroke at baseline. A standardized weighted CAD genetic risk score was constructed using 70 known genetic variants. The risk score was divided into quintiles (Q1-Q5). We specified low (Q1), intermediate (Q2-Q4) and high (Q5) genetic risk groups. Incident CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death. The association between the genetic risk score and genetic risk groups with incident CHD was assessed using Cox models to estimate hazard ratios (HR) and 95%-confidence intervals (CI). The models were adjusted by age and sex (Model1), as well as by established CHD risk factors (RF) and CAC (Model2). The analyses were further stratified by sex and controlled for multiple testing.

resultsDuring a median follow-up time of 11.6 ± 3.7 years, 343 participants experienced CHD events (219 men). Per-standard deviation (SD) increase in the genetic risk score was associated with 18% increased risk for incident CHD (Model1: p = 0.002) which did not change after full adjustment (Model2: HR = 1.18 per-SD (p = 0.003)). In Model2 we observed a 60% increased CHD risk in the high (p = 0.009) compared to the low genetic risk group. Stratifying by sex, only men showed statistically significantly higher risk for CHD (Model2: HR = 1.23 per-SD (p = 0.004); intermediate: HR = 1.52 (p = 0.04) and high: HR = 1.88 (p = 0.008)) with no statistically significant risk observed in women.

conclusionOur results suggest that the CAD genetic risk score could be useful for CHD risk prediction, at least in men belonging to the higher genetic risk group, but it does not outbalance the value of CT-based quantification of CAC which works independently on both men and women and allows better risk stratification in both the genders.

Indexed as

AgedCoronary Artery DiseaseFemaleHumansMaleMendelian Randomization AnalysisMiddle AgedMyocardial InfarctionPrognosisProportional Hazards ModelsRisk AssessmentRisk FactorsStrokeTomography, X-Ray ComputedCohort studyCoronary artery calcificationCoronary artery diseaseCoronary heart diseaseGenetic risk score

Identifiers

PMID32912153
PMCPMC7487988
OpenAlexW3084388260

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.