Diagnostic Uncertainty

In Indeterminate Thyroid Nodules

NEW Validation Study Demonstrates
Highest PPV and High NPV1*

Accurate risk stratification can help reduce unnecessary thyroid surgery and assist pre-operative patient counseling and surgical planning.2

Markers That MatterTM

Strategically designed rule-in / rule-out testing platform—maximizing your understanding of true negatives, true positives, and aggressive biological features of thyroid cancer

Performance Matters

Demonstrated High NPV and Highest PPV1*

50 %
50 %
50 %
40 %

*Study Design

Multicenter, retrospective, blinded validation study of 309 subjects with indeterminate thyroid nodules (Bethesda III, IV, or V) and corresponding surgical histology. Gold-standard unanimous consensus histopathology diagnosis (n=197) among three pathologists was used and all molecular testing was performed using archived cytology smears. Results were reported as negative, moderate, or positive based on the combined test results from both ThyGeNEXT® (mutation panel) and ThyraMIR® (microRNA risk classifier). Additional histopathologic subtype prevalence adjustments were used to determine the impact of Spectrum Effect biases on test performance. The analysis showed that test performance was optimal in a histopathologic subtype population encountered in clinical practice.

Compared to other marketed tests,3,4 results demonstrated that microRNA and mutation panel combination testing had the highest PPV (positive predictive value) at 75% and similar NPV (negative predictive value) at 97% (n=178, prevalence-adjusted). microRNA classification further risk-stratified patients with weak driver mutations, including RAS, resulting in four out of five nodules being accurately ruled-in or ruled-out for disease. Prevalence-unadjusted PPV and NPV were 74% and 95%, respectively.

Flexibility Matters

Interpace Diagnostics is the only company that offers:

Testing of fresh FNA samples or direct smears/ThinPrep® slides

No special shipping or refrigeration requirements

Mutation panel + miRNA expression classifier



1. Lupo MA, et al. Diagn Cytopathol. 2020;1–11. https://doi.org/10.1002/dc.24564. 2. Banizs AB, Silverman JF. Diagn Cytopathol. 2019;47(4):268-274. 3. Steward DL, et al. JAMA Oncol. 2019;5(2):204-212. 4. Patel KN, et al. JAMA Surg. 2018;153(9):817-824.

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