Analytical performance validation of a coronary heart disease risk assessment multi-analyte proteomic test

Expert Opin Med Diagn. 2013 Mar;7(2):127-36. doi: 10.1517/17530059.2013.753055. Epub 2012 Dec 11.


Background: Coronary heart disease (CHD) remains prevalent despite efforts to improve CHD risk assessment. The authors developed a multi-analyte immunoassay-based CHD risk assessment (CHDRA) algorithm, clinically validated in a multicenter study, to improve CHDRA in intermediate risk individuals.

Objective: Clinical laboratory validation of the CHDRA biomarker assays' analytical performance.

Methods: Multiplexed immunoassay panels developed for the seven CHDRA assays were evaluated with donor sera in a clinical laboratory. Specificity, sensitivity, interfering substances and reproducibility of the CHDRA assays, along with the effects of pre-analytical specimen processing, were evaluated.

Results: Analytical measurements of the CHDRA panel proteins (CTACK, Eotaxin, Fas Ligand, HGF, IL-16, MCP-3 and sFas) exhibited acceptable accuracy (80 - 120%), cross-reactivity (< 1%), interference (< 30% at high concentrations of bilirubin, lipids, hemoglobin and HAMA), sensitivity and reproducibility (< 20% CV across multiple runs, operators and instruments). Recoveries from donor sera subjected to typical clinical laboratory pre-analytical conditions were within 80 - 120%. The pre-analytical variables did not substantively impact the CHDRA scores.

Conclusions: The CHDRA panel analytical validation in a clinical laboratory meets or exceeds the specifications established during the clinical utility studies. Risk score reproducibility across multiple test scenarios suggests the assays are not susceptible to clinical laboratory pre-analytical and analytical variation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers / blood
  • Blood Proteins / analysis*
  • Coronary Disease / blood*
  • Humans
  • Immunoassay
  • Proteomics / methods
  • Reproducibility of Results
  • Risk Assessment / methods
  • Sensitivity and Specificity
  • Specimen Handling


  • Biomarkers
  • Blood Proteins