Evidence map›Paper›PMID 34608230›Full record

ArticleScientific reports2021

A newly developed and externally validated non-clinical score accurately predicts 10-year cardiovascular disease risk in the general adult population.

Catarina Schiborn, Tilman Kühn, Kristin Mühlenbruch, Olga Kuxhaus, Cornelia Weikert, Andreas Fritsche, Rudolf Kaaks, Matthias B Schulze

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 3 pooled it
–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

10 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  8. Review
  9. The clinical characterization of the adult patient with bipolar disorder aimed at personalization of management.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2022
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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

8 authors.

Catarina SchibornDepartment of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany. catarina.schiborn@dife.de.
Tilman KühnDivision of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Kristin MühlenbruchDepartment of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany.
Olga KuxhausDepartment of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany.
Cornelia WeikertDepartment of Food Safety, German Federal Institute for Risk Assessment, Berlin, Germany.
Andreas FritscheGerman Center for Diabetes Research (DZD), Munich Neuherberg, Germany.
Rudolf KaaksDivision of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Matthias B SchulzeDepartment of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inclusion of clinical parameters limits the application of most cardiovascular disease (CVD) prediction models to clinical settings. We developed and externally validated a non-clinical CVD risk score with a clinical extension and compared the performance to established CVD risk scores. We derived the scores predicting CVD (non-fatal and fatal myocardial infarction and stroke) in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (n = 25,992, cases = 683) using competing risk models and externally validated in EPIC-Heidelberg (n = 23,529, cases = 692). Performance was assessed by C-indices, calibration plots, and expected-to-observed ratios and compared to a non-clinical model, the Pooled Cohort Equation, Framingham CVD Risk Scores (FRS), PROCAM scores, and the Systematic Coronary Risk Evaluation (SCORE). Our non-clinical score included age, gender, waist circumference, smoking, hypertension, type 2 diabetes, CVD family history, and dietary parameters. C-indices consistently indicated good discrimination (EPIC-Potsdam 0.786, EPIC-Heidelberg 0.762) comparable to established clinical scores (thereof highest, FRS: EPIC-Potsdam 0.781, EPIC-Heidelberg 0.764). Additional clinical parameters slightly improved discrimination (EPIC-Potsdam 0.796, EPIC-Heidelberg 0.769). Calibration plots indicated very good calibration with minor overestimation in the highest decile of predicted risk. The developed non-clinical 10-year CVD risk score shows comparable discrimination to established clinical scores, allowing assessment of individual CVD risk in physician-independent settings.

Indexed as

Epidemiological ModelsAdultAgedCardiovascular DiseasesComorbidityDisease SusceptibilityFemaleHumansMaleMiddle AgedPopulation SurveillanceReproducibility of ResultsRisk AssessmentRisk FactorsTime Factors

Identifiers

PMID34608230
PMCPMC8490374

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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.