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Performance of a Multigene Genomic Classifier in Thyroid Nodules With Indeterminate Cytology: A Prospective Blinded Multicenter Study
Open accessAbstract
Importance: Approximately 20% of fine-needle aspirations (FNA) of thyroid nodules have indeterminate cytology, most frequently Bethesda category III or IV. Diagnostic surgeries can be avoided for these patients if the nodules are reliably diagnosed as benign without surgery. Objective: To determine the diagnostic accuracy of a multigene classifier (GC) test (ThyroSeq v3) for cytologically indeterminate thyroid nodules. Design, Setting, and Participants: Prospective, blinded cohort study conducted at 10 medical centers, with 782 patients with 1013 nodules enrolled. Eligibility criteria were met in 256 patients with 286 nodules; central pathology review was performed on 274 nodules. Interventions: A total of 286 FNA samples from thyroid nodules underwent molecular analysis using the multigene GC (ThyroSeq v3). Main Outcomes and Measures: The primary outcome was diagnostic accuracy of the test for thyroid nodules with Bethesda III and IV cytology. The secondary outcome was prediction of cancer by specific genetic alterations in Bethesda III to V nodules. Results: Of the 286 cytologically indeterminate nodules, 206 (72%) were benign, 69 (24%) malignant, and 11 (4%) noninvasive follicular thyroid neoplasms with papillary-like nuclei (NIFTP). A total of 257 (90%) nodules (154 Bethesda III, 93 Bethesda IV, and 10 Bethesda V) had informative GC analysis, with 61% classified as negative and 39% as positive. In Bethesda III and IV nodules combined, the test demonstrated a 94% (95% CI, 86%-98%) sensitivity and 82% (95% CI, 75%-87%) specificity. With a cancer/NIFTP prevalence of 28%, the negative predictive value (NPV) was 97% (95% CI, 93%-99%) and the positive predictive value (PPV) was 66% (95% CI, 56%-75%). The observed 3% false-negative rate was similar to that of benign cytology, and the missed cancers were all low-risk tumors. Among nodules testing positive, specific groups of genetic alterations had cancer probabilities varying from 59% to 100%. Conclusions and Relevance: In this prospective, blinded, multicenter study, the multigene GC test demonstrated a high sensitivity/NPV and reasonably high specificity/PPV, which may obviate diagnostic surgery in up to 61% of patients with Bethesda III to IV indeterminate nodules, and up to 82% of all benign nodules with indeterminate cytology. Information on specific genetic alterations obtained from FNA may help inform individualized treatment of patients with a positive test result.
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Self-citationApproximate is Better than “Exact” for Interval Estimation of Binomial Proportions
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Integrated Genomic Characterization of Papillary Thyroid Carcinoma
Agrawal, N., Akbani, R., Aksoy, B. A., Ally, A., Arachchi, H., Asa, S. L., Auman, J. T., Balasundaram, M., Balu, S., Baylin, S. B., et al. (2014) · Cell · doi:10.1016/j.cell.2014.09.050 · Cited by 3,062
Self-citationACR Thyroid Imaging, Reporting and Data System (TI-RADS): White Paper of the ACR TI-RADS Committee
Tessler, F. N., Middleton, W. D., Grant, E. G., Hoang, J. K., Berland, L. L., Teefey, S. A., Cronan, J. J., Beland, M. D., Desser, T. S., Frates, M. C., et al. (2017) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2017.01.046 · Cited by 2,530
The 2017 Bethesda System for Reporting Thyroid Cytopathology
Cibas, E. S., & Ali, S. Z. (2017) · Thyroid · doi:10.1089/thy.2017.0500 · Cited by 1,844
Management of a Solitary Thyroid Nodule
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Nikiforov, Y. E., Seethala, R. R., Tallini, G., Baloch, Z. W., Basolo, F., Thompson, L. D. R., Barletta, J. A., Wenig, B. M., Al Ghuzlan, A., Kakudo, K., et al. (2016) · JAMA Oncology · doi:10.1001/jamaoncol.2016.0386 · Cited by 1,404
Self-citationRuss, G., Bonnema, S. J., Erdogan, M. F., Durante, C., Ngu, R., & Leenhardt, L. (2017) · European Thyroid Journal · doi:10.1159/000478927 · Cited by 1,284
Preoperative Diagnosis of Benign Thyroid Nodules with Indeterminate Cytology
Alexander, E. K., Kennedy, G. C., Baloch, Z. W., Cibas, E. S., Chudova, D., Diggans, J., Friedman, L., Kloos, R. T., LiVolsi, V. A., Mandel, S. J., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1203208 · Cited by 1,163
Self-citationWorldwide Thyroid-Cancer Epidemic? The Increasing Impact of Overdiagnosis
Vaccarella, S., Franceschi, S., Bray, F., Wild, C. P., Plummer, M., & Dal Maso, L. (2016) · New England Journal of Medicine · doi:10.1056/nejmp1604412 · Cited by 1,145
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Nangalia, J., & Campbell, P. J. (2019) · New England Journal of Medicine · doi:10.1056/nejmra1910138 · Cited by 66
The somatic molecular evolution of cancer: Mutation, selection, and epistasis
Dasari, K., Somarelli, J. A., Kumar, S., & Townsend, J. P. (2021) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2021.08.003 · Cited by 22
Metadata
- Authors
- Steward, D. L., Carty, S. E., Sippel, R. S., Yang, S. P., Sosa, J. A., Sipos, J. A., Figge, J. J., Mandel, S., Haugen, B. R., Burman, K. D., Baloch, Z. W., Lloyd, R. V., Seethala, R. R., Gooding, W. E., Chiosea, S. I., Gomes-Lima, C., Ferris, R. L., Folek, J. M., Khawaja, R. A., Kundra, P., Loh, K. S., Marshall, C. B., Mayson, S., McCoy, K. L., Nga, M. E., Ngiam, K. Y., Nikiforova, M. N., Poehls, J. L., Ringel, M. D., Yang, H., Yip, L., & Nikiforov, Y. E.
- Venue
- JAMA Oncology
- Publisher
- American Medical Association (AMA)
- Published
- 2019-02-01
- Volume
- 5
- Issue
- 2
- Pages
- 204
- ISSN
- 2374-2437 (ISSN-L)
- OpenAlex
- W2900078105
- Cited by
- 486
- References
- 40
- FWCI
- 29.68
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Steward, D. L., Carty, S. E., Sippel, R. S., Yang, S. P., Sosa, J. A., Sipos, J. A., Figge, J. J., Mandel, S., Haugen, B. R., Burman, K. D., Baloch, Z. W., Lloyd, R. V., Seethala, R. R., Gooding, W. E., Chiosea, S. I., Gomes-Lima, C., Ferris, R. L., Folek, J. M., Khawaja, R. A., . . . Nikiforov, Y. E. (2019). Performance of a Multigene Genomic Classifier in Thyroid Nodules With Indeterminate Cytology: A Prospective Blinded Multicenter Study. JAMA Oncology. https://doi.org/10.1001/jamaoncol.2018.4616
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.