Utility of a Genomic-based, Perso... [J Am Board Fam Med. 2014 Mar-Apr] - PubMed - NCBI

Utility of a Genomic-based, Perso... [J Am Board Fam Med. 2014 Mar-Apr] - PubMed - NCBI

J Am Board Fam Med. 2014 Mar-Apr;27(2):258-67. doi: 10.3122/jabfm.2014.02.130155.

Utility of a Genomic-based, Personalized Medicine Test in Patients Presenting With Symptoms Suggesting Coronary Artery Disease.

Herman L1, Froelich J, Kanelos D, St Amant R, Yau M, Rhees B, Monane M, McPherson J.

Author information

Abstract

Purpose: Better methods are needed to assess patients presenting with symptoms suggestive of obstructive coronary artery disease (CAD). We hypothesized that the use of a gene expression score (GES) would lead to a change in the diagnostic evaluation.

METHODS:

The Primary Care Providers Use of a Gene Expression Test in Coronary Artery Disease Diagnosis (IMPACT-PCP) trial (clinical trial identifier NCT01594411, clinicaltrials.gov) was a prospective study of stable, nonacute, nondiabetic patients presenting with chest pain and related symptoms at 4 primary care practices. All patients underwent GES testing, with clinicians documenting their planned diagnostic strategy both before and after GES. The GES was derived from a peripheral blood draw measuring expression of 23 genes and has been shown to have a 96% negative predictive value for excluding the diagnosis of obstructive CAD.

RESULTS:

Of the 251 study patients, 140 were women (56%); the participants had a mean age of 56 years (standard deviation, 13.0) and a mean body mass index of 30 mg/kg(2) (standard deviation, 6.7). The mean GES was 16 (range, 1-38), and 127 patients (51%) had a low GES ([ltqeu]15). A change in the diagnostic testing pattern before and after GES testing was noted in 145 of 251 patients (58% observed vs. 10% predefined expected change; P < .001).

CONCLUSIONS:

Incorporation of the GES into the diagnostic workup showed clinical utility above and beyond conventional clinical factors by optimizing the patient's diagnostic evaluation.

KEYWORDS:

Cardiovascular Abnormalities, Genetics, Medical Decision Making, Practice-based Research, Technology Assessment

PMID:

 

24610188

 

[PubMed - in process] 

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