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Updated: Mar 6, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
The AlloMap™ genomic biomarker story: 10 years after
1Advanced Heart Failure/Mechanical Support/Heart Transplant, David Geffen School of Medicine at UCLA, Ronald Reagan UCLA Medical Center, Los Angeles, CA, USA.
Abstract:
Over the last >20 years, we have co-developed the rationale for the first diagnostic and prognostic leukocyte gene expression profiling (GEP) biomarker test in transplantation medicine that gained US-FDA-regulatory clearance and international evidence-based medicine guideline acceptance to rule out moderate/severe acute cellular cardiac allograft rejection without invasive endomyocardial biopsies (EMB). Based on this test, a non-invasive clinical algorithm was implemented since 2005. After clinical implementation, this GEP-based monitoring in direct comparison with an EMB-based strategy was non-inferior with respect to detection of clinical rejection, defined as new onset allograft dysfunction with/without histology of ACR, re-transplantation or death, and at the same time improved patient satisfaction. Subsequently, we demonstrated the test's capacity when used as serial monitoring tool to predict these clinical rejection events. In this Personal Viewpoint article, I will discuss the various decision-making branching points that were made in the AlloMap biomarker test development to inform future genomic biomarker test development projects.
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