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Preoperative Molecular Markers in Thyroid Nodules.

Zeyad T Sahli1, Philip W Smith2, Christopher B Umbricht1

  • 1Department of Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.

Frontiers in Endocrinology
|May 4, 2018
PubMed
Summary

Distinguishing benign from malignant thyroid nodules is crucial. Molecular markers like Afirma® Gene Expression Classifier (GEC) and Thyroseq® V2 show variable diagnostic accuracy, with limitations impacting clinical utility.

Keywords:
AfirmaThyroseqmolecular testnon-invasive follicular thyroid neoplasm with papillary-like nuclear featuresthyroid cancer

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Area of Science:

  • Endocrinology
  • Oncology
  • Molecular Diagnostics

Background:

  • Accurate differentiation of benign versus malignant thyroid nodules is critical for patient management.
  • Molecular markers are increasingly used to improve diagnostic accuracy.
  • Existing molecular tests face challenges including new histopathological classifications and cost-effectiveness.

Purpose of the Study:

  • To review the diagnostic performance of Afirma® Gene Expression Classifier (GEC) and Thyroseq® V2.
  • To discuss current limitations and future directions for molecular markers in thyroid nodule diagnosis.

Main Methods:

  • Systematic literature review of studies evaluating Afirma® GEC and Thyroseq® V2.
  • Analysis of reported sensitivity, specificity, positive predictive value, and negative predictive value.

Main Results:

  • Afirma® GEC studies showed a wide range of performance: Se (75-100%), Sp (5-53%), PPV (13-100%), NPV (20-100%).
  • Thyroseq® V2 studies reported: Se (40-100%), Sp (56-93%), PPV (13-90%), NPV (48-97%).
  • Significant variability exists in the reported diagnostic metrics for both tests.

Conclusions:

  • Both Afirma® GEC and Thyroseq® V2 have demonstrated utility but exhibit considerable variability in diagnostic accuracy.
  • Challenges remain in their clinical application, including interpretation of results and cost-effectiveness.
  • Further research is needed to optimize molecular marker utility and address current limitations.