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Indeterminate thyroid nodules (ITN) represent 20–30% of biopsied nodules, with a 10–60% risk of malignancy. Molecular testing can stratify the risk of malignancy among ITNs, and subsequently reduce the need for unnecessary diagnostic surgery. We aimed to assess the performance of these molecular tests at a single institution. Patients with Bethesda III, IV, and V nodules with Afirma and Interpace Diagnostics genetic testing data from November 2013 to November 2021 were included. Three cohorts were formed, including GSC + XA, ThyGeNEXT + ThyraMIR, and GSC + GEC. Statistical analysis determined the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), diagnostic odds ratio (DOR), and accuracy of each type of testing. The PPV of nodules undergoing genetic testing by ThyGeNEXT + ThyraMIR (45.00%, 95%CI: 28.28–62.93%, p = 0.032) and GSC + XA (57.14%, 95%CI: 29.32–81.08%, p < 0.001) were superior to that of GEC + GSC (30.72%, 95%CI: 26.83–34.90%). The NPV was above 85% in all cohorts, suggesting overall suitable rule-out tests. The Afirma platform (GSC + XA) had the highest NPV at 96.97%. The overall accuracy for nodules undergoing ThyGeNEXT + ThyraMIR was 81.42% (95%CI: 73.01–88.11%, p < 0.001). A total of 230 patients underwent thyroidectomy, including less than 60% of each of the ThyGeNEXT + ThyraMIR and GSC + XA cohorts. Specifically, only 25% of patients in the GSC + XA cohort underwent surgery, considerably decreasing the rate of unnecessary surgical intervention. Sub-group analysis, including only patients with surgical pathology, found that PPV tended to be higher in the GSC + XA cohort, at 66.67% (95%CI: 37.28–87.06%), as compared to the ThyGeNEXT + ThyraMIR cohort, at 52.94% (95%CI: 35.25–69.92%). The Afirma genetic testing platform GSC + XA outperformed the other platforms with regards to both PPV and NPV and decreased the rate of surgery in patients with ITNs by 75%, significantly preventing unnecessary surgical intervention.

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Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.