Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Clinical Trial
. 2010 Oct 5;153(7):425-34.
doi: 10.7326/0003-4819-153-7-201010050-00005.

Multicenter validation of the diagnostic accuracy of a blood-based gene expression test for assessing obstructive coronary artery disease in nondiabetic patients

Steven Rosenberg  1 , Michael R Elashoff, Philip Beineke, Susan E Daniels, James A Wingrove, Whittemore G Tingley, Philip T Sager, Amy J Sehnert, May Yau, William E Kraus, L Kristin Newby, Robert S Schwartz, Szilard Voros, Stephen G Ellis, Naeem Tahirkheli, Ron Waksman, John McPherson, Alexandra Lansky, Mary E Winn, Nicholas J Schork, Eric J Topol; PREDICT (Personalized Risk Evaluation and Diagnosis in the Coronary Tree) Investigators
Collaborators, Affiliations
Clinical Trial

Multicenter validation of the diagnostic accuracy of a blood-based gene expression test for assessing obstructive coronary artery disease in nondiabetic patients

Steven Rosenberg et al. Ann Intern Med. .

Abstract

Background: Diagnosing obstructive coronary artery disease (CAD) in at-risk patients can be challenging and typically requires both noninvasive imaging methods and coronary angiography, the gold standard. Previous studies have suggested that peripheral blood gene expression can indicate the presence of CAD.

Objective: To validate a previously developed 23-gene, expression-based classification test for diagnosis of obstructive CAD in nondiabetic patients.

Design: Multicenter prospective trial with blood samples obtained before coronary angiography. (ClinicalTrials.gov registration number: NCT00500617) SETTING: 39 centers in the United States.

Patients: An independent validation cohort of 526 nondiabetic patients with a clinical indication for coronary angiography.

Measurements: Receiver-operating characteristic (ROC) analysis of classifier score measured by real-time polymerase chain reaction, additivity to clinical factors, and reclassification of patient disease likelihood versus disease status defined by quantitative coronary angiography. Obstructive CAD was defined as 50% or greater stenosis in 1 or more major coronary arteries by quantitative coronary angiography.

Results: The area under the ROC curve (AUC) was 0.70 ± 0.02 (P < 0.001); the test added to clinical variables (Diamond-Forrester method) (AUC, 0.72 with the test vs. 0.66 without; P = 0.003) and added somewhat to an expanded clinical model (AUC, 0.745 with the test vs. 0.732 without; P = 0.089). The test improved net reclassification over both the Diamond-Forrester method and the expanded clinical model (P < 0.001). At a score threshold that corresponded to a 20% likelihood of obstructive CAD (14.75), the sensitivity and specificity were 85% and 43% (yielding a negative predictive value of 83% and a positive predictive value of 46%), with 33% of patient scores below this threshold.

Limitation: Patients with chronic inflammatory disorders, elevated levels of leukocytes or cardiac protein markers, or diabetes were excluded.

Conclusion: A noninvasive whole-blood test based on gene expression and demographic characteristics may be useful for assessing obstructive CAD in nondiabetic patients without known CAD.

Primary funding source: CardioDx.

PubMed Disclaimer

Conflict of interest statement

RSS, SZ, RW, JM, and NT report no conflicts of interest with respect to the contents of this manuscript.

Figures

Figure 1
Figure 1
Allocation of Patients from the PREDICT trial for algorithm development and validation. From a total of 1569 subjects meeting the study inclusion/exclusion criteria 226 were used for gene discovery. The remaining 1343 were divided into independent cohorts for algorithm development (694) and validation (649) as shown; 94% of patients in these cohorts came from the same centers. For algorithm development a total of 640 patient samples were used; 54 were excluded due to incomplete data (13), inadequate blood volume (19), sex mismatch between experimental and clinical records (5), or statistical outlier assessment (17) (see Supplement for details). For the validation cohort a total of 123 samples were excluded based on: inadequate blood volume or RNA yield (43), significant contamination with genomic DNA (78), or prespecified statistical outlier assessment (2).
Figure 2
Figure 2
Schematic of the Algorithm Structure and Genes. The algorithm consists of overlapping gene expression functions for males and females with a sex-specific linear age function for the former and a non-linear age function for the latter. For the gene expression components shown 16/23 genes in 4 terms are gender independent: term 1 – neutrophil activation and apoptosis, term 3 – NK cell activation to T cell ratio, term 4, B to T cell ratio, and term 5 –expression of gene AF289562 normalized to the mean of TFCP2 and HNRPF. In addition, Term 2 consists of 3 sex-independent neutrophil/innate immunity genes normalized in a sex-specific way to neutrophil gene expression (AQP9,NCF4) for females and to RPL28 (lymphocytes) in males. The final male specific term is the normalized expression of TSPAN16. The raw algorithm score is calculated from RT-PCR data as described (Appendix 3); for clinical use, the raw score was converted to a 0–40 scale by linear transformation.
Figure 3
Figure 3
ROC analysis of Validation Cohort Performance For Algorithm and Clinical Variables. Algorithm performance adds to Clinical Factors by Diamond-Forrester. Comparison of the combination of D–F score and algorithm score (heavy solid line) to D–F score alone (---) in ROC analysis is shown. The AUC=0.50 line (light solid line) is shown for reference. A total of 525 of the 526 validation cohort patients had information available to calculate D–F scores. The AUCs for the two ROC curves are 0.721 ± 0.023 and 0.663 ±0.025, p = 0.003.
Figure 4
Figure 4
Dependence of Algorithm Score on % Maximum Stenosis in the Validation Cohort. The extent of disease for each patient was quantified by QCA maximum % stenosis and grouped into 5 categories: no measurable disease, 1–24%, 25–49% in ≥1 vessel, 1 vessel >50%, and >1 vessel >50%. The average algorithm score for each group is illustrated; error bars correspond to 95% confidence intervals. The complete relationship of algorithm score to obstructive CAD likelihood is depicted in Supplementary Figure 1; in Figure 4 scores of 10, 20, and 30 correspond to 15, 30, and 57% disease likelihood. A score of 15, corresponding to a 20% likelihood was used for dichotomous analyses as described in the text.
See this image and copyright information in PMC

Comment in

Summary for patients in

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Lloyd-Jones D, Adams R, Carnethon M, et al. Heart disease and stroke statistics--2009 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 2009;119(3):480–486. - PubMed
    1. Martina B, Bucheli B, Stotz M, Battegay E, Gyr N. First Clinical Judgment by Primary Care Physicians Distinguishes Well between Nonorganic and Organic Causes of Abdominal or Chest Pain. J Gen Intern Med. 1997;12:459–465. - PMC - PubMed
    1. Svavarsdottir AE, Jonasson MR, Gudmundsson GH, Fjeldsted K. Chest pain in family practice. Diagnosis and long-term outcome in a community setting. Can Fam Physician. 1996;42:1122–1128. - PMC - PubMed
    1. Klinkman MS, Stevens D, Gorenflo DW. Episodes of care for chest pain: a preliminary report from MIRNET. Michigan Research Network. J Fam Pract. 1994;38(4):345–352. - PubMed
    1. Gibbons RJ, Abrams J, Chatterjee K, et al. ACC/AHA 2002 guideline update for the management of patients with chronic stable angina--summary article: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines (Committee on the Management of Patients With Chronic Stable Angina) J Am Coll Cardiol. 2003;41(1):159–168. - PubMed

Publication types

MeSH terms

Associated data