The Diagnostic Performance of Afirma Gene Expression Classifier for the Indeterminate Thyroid Nodules: A Meta-Analysis

Abstract

Background

Approximately 15 to 30% of thyroid nodules evaluated by fine-needle aspiration (FNA) were classified as indeterminate; the accurate diagnostic molecular tests of these nodules remain a challenge. We aimed to evaluate the diagnostic performance of Afirma gene expression classifier (GEC) for the indeterminate thyroid nodules (ITNs).

Methods

Studies published from January 2005 to December 2018 were systematically reviewed. The gold reference standard relied on the histopathologic results diagnosis from thyroidectomy surgical specimens. MetaDisc software was used to investigate the pooled sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), diagnostic odds ratio (DOR), and summary receiver operating characteristic (SROC) curves.

Results

A total of 18 studies involving 5290 patients with 3290 cases of ITNs were included. Collected data revealed that the pooled sensitivity of GEC was 95.5% (95% CI 93.3%–97.0%, p < 0.001), the specificity was 22.1% (95% CI 19.4%-24.9%, p < 0.001), the NPV was 88.2% (95% CI 0.833–0.921, p < 0.001), the PPV was 44.3% (95% CI 0.416–0.471, p < 0.001), and the DOR was 5.25 (95% CI 3.42–8.04, p= 0.855).

Conclusion

The GEC has quite high sensitivity of 95.5% but low specificity of 22.1%. The high sensitivity makes it probable to rule out malignant nodules. Thus, over half of nodules with GEC-suspicious results still require further validation like molecular markers, diagnostic surgery, or long follow-up, which limits its use in future clinical practice.