Association of Malignancy Prevalence With Test Properties and Performance of the Gene Expression Classifier in Indeterminate Thyroid Nodules

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It is crucial for clinicians to know the malignancy prevalence within each indeterminate cytologic category to estimate the performance of the gene expression classifier (GEC).


To examine the variability in the performance of the GEC.

Design, Setting, and Participants

This retrospective cohort study of patients with Bethesda category III and IV thyroid nodules used single-institution data from January 1, 2013, through February 29, 2016. Expected negative predictive value (NPV) was calculated by adopting published sensitivity and specificity. Observed NPV was calculated based on the true-negative rate. Outcomes were compared with pooled data from 11 studies published January 1, 2010, to January 31, 2016.


A total of 145 patients with 154 thyroid nodules were included in the study (mean [SD] age, 56.0 [16.2] years; 106 females [73.1%]). Malignancy prevalence was 45%. On the basis of this prevalence, the expected NPV is 85% and the observed NPV is 69%. If the prevalence is assumed to be 25%, the expected NPV would be 94%, whereas the observed NPV would be 85%. Pooled data analysis of 11 studies comprising 1303 participants revealed a malignancy prevalence of 31% (95% CI, 29%-34%) and a pooled NPV of 92% (95% CI, 87%-96%).

Conclusions and Relevance

In this study, variability in the performance of the GEC was not solely a function of malignancy prevalence and may have been attributable to intrinsic variability of the test sensitivity and specificity. The utility of the GEC in practice is elusive because of this variability. A better definition of the GEC’s intrinsic properties is needed.

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