Evidence map›Paper›PMID 23740530›Full record

ArticleClinical cardiology2013

Development of a multi-institutional cohort to facilitate cardiovascular disease biomarker validation using existing biorepository samples linked to electronic health records.

Deanna S Cross, Catherine A McCarty, Steven R Steinhubl, David J Carey, Porat M Erlich

Open access · greenAbstract readMulticenter StudyValidation Study
In one paragraph

Article in Clinical cardiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.0field-weighted citation impact, top 12% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

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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

5 authors at 3 institutions in 1 country.

Deanna S CrossCenter for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin.
Catherine A McCarty
Steven R Steinhubl
David J Carey
Porat M Erlich
Geisinger Health System · USCenter for Human Genetics · USEssentia Health · US

Funding

Institutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2M
HMO Research Network Cardiovascular Research NetworkU19HL091179 · NHLBI · KAISER FOUNDATION RESEARCH INSTITUTE · PI GO, ALAN S · 2007 to 2011
$8.7M
NCATS NIH HHS UL1 TR000427NCATS NIH HHS UL1TR000427NHLBI NIH HHS U19 HL091179NHLBI NIH HHS U19 HL91179-01
6 · The paper itself

Abstract

backgroundEmerging biomarkers for acute myocardial infarction (AMI) may enhance conventional risk-prediction algorithms if they are informative and associated with risk independently of established predictors. In this study, we constructed a cohort for testing emerging biomarkers for AMI in managed-care populations using existing biospecimen repositories linked to electronic health records (EHR). HYPOTHESIS: Electronic health record-based biorepositories collected by healthcare systems can be federated to provide large, methodologically sound testing sets for biomarker validation.

methodsSubjects ages 40 to 80 years were selected from 2 existing population-based biospecimen repositories. Incident AMI status and covariates were ascertained from the EHR. An ad hoc model for AMI risk was parameterized and validated. Simulation was used to test incremental gains in performance due to the inclusion of biomarkers in this model. Gains in performance were assessed in terms of area under the receiver operating characteristic curve (ROC-AUC) and case reclassification.

resultsA total of 18 329 individuals (57% female) contributed 108 400 person-years of EHR follow-up. The crude AMI incidence was 10.8 and 5.0 per 1000 person-years among males and females, respectively. Compared with the model with risk factors alone, inclusion of a simulated biomarker yielded substantial gains in sensitivity without loss of specificity. Furthermore, a net ROC-AUC gain of 13.3% was observed, as well as correct reclassification of 9.8% of incident cases (79 of 806) that were otherwise not considered statin-indicated at baseline under the National Cholesterol Education Program Adult Treatment Panel III criteria.

conclusionsMore research is needed to assess incremental contribution of emerging biomarkers for AMI prediction in managed-care populations.

Indexed as

Biological Specimen BanksElectronic Health RecordsMedical Record LinkageArea Under CurveBiomarkersCardiovascular DiseasesComputer SimulationFemaleHumansIncidenceMaleMiddle AgedPredictive Value of TestsPrognosisReproducibility of ResultsRetrospective StudiesBiomarkers

Identifiers

PMID23740530
PMCPMC3970767
OpenAlexW1901045397

What OpenQuestion holds

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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 OpenQuestion graph.