James J Figge1, William E Gooding2, David L Steward3, Linwah Yip4, Rebecca S Sippel5, Samantha Peiling Yang6,7, Randall P Scheri8, Jennifer A Sipos9, Susan J Mandel10, Sarah E Mayson11, Kenneth D Burman12, Jessica M Folek13, Bryan R Haugen11, Julie A Sosa14, Rajeev Parameswaran15,16, Wee Boon Tan15,16, Yuri E Nikiforov17, Sally E Carty4. 1. Diabetes & Endocrine Care, St. Peter's Health Partners/Trinity Health, Rensselaer, New York, USA. 2. Biostatistics Facility, UPMC Hillman Cancer Center, Pittsburgh, Pennsylvania, USA. 3. Department of Otolaryngology, Head and Neck Surgery, University of Cincinnati Medical Center, Cincinnati, Ohio, USA. 4. Division of Endocrine Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. 5. Division of Endocrine Surgery, University of Wisconsin, Madison, Wisconsin, USA. 6. Endocrinology Division, Department of Medicine, National University Hospital, Singapore, Singapore. 7. Endocrinology Division, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. 8. Section of Endocrine Surgery, Department of Surgery, Duke University, Durham, North Carolina, USA. 9. Division of Endocrinology, Diabetes, and Metabolism, Ohio State University School of Medicine, Columbus, Ohio, USA. 10. Division of Endocrinology, Diabetes and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA. 11. Division of Endocrinology, Metabolism and Diabetes, University of Colorado School of Medicine, Aurora, Colorado, USA. 12. Endocrinology Section, Department of Medicine, MedStar Washington Hospital Center, Washington, District of Columbia, USA. 13. PeaceHealth Medical Group, Springfield, Oregon, USA. 14. Department of Surgery, University of California San Francisco, San Francisco, California, USA. 15. Division of Endocrine Surgery, Department of Surgery, National University Hospital, Singapore, Singapore. 16. Division of Endocrine Surgery, Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. 17. Department of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Abstract
Background: Molecular testing (MT) is commonly used to refine cancer probability in thyroid nodules with indeterminate cytology. Whether or not ultrasound (US) patterns and clinical parameters can further inform the risk of thyroid cancer in nodules predicted to be positive or negative by MT remains unknown. The aim of this study was to test if clinical parameters, including patient age, sex, nodule size (by US), Bethesda category (III, IV, V), US pattern (American Thyroid Association [ATA] vs. American College of Radiology Thyroid Image Reporting and Data System [TI-RADS] systems), radiation exposure, or family history of thyroid cancer can modify the probability of thyroid cancer or noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) predicted by MT. Methods: We studied 257 thyroid nodules in 232 patients from 10 study centers with indeterminate fine needle aspiration cytology and informative MT results using the ThyroSeq v3 genomic classifier (TSv3). Univariate and multivariate logistic regression was used for data analysis. Results: The presence of cancer/NIFTP was associated with positive TSv3 results (odds ratio 61.39, p < 0.0001). On univariate regression, patient sex, age, and Bethesda category were associated with cancer/NIFTP probability (p < 0.05 for each). Although ATA (p = 0.1211) and TI-RADS (p = 0.1359) US categories demonstrated positive trends, neither was significantly associated with cancer/NIFTP probability. A multivariate regression model incorporating the four most informative non-MT covariates (sex, age, Bethesda category, and ATA US pattern; Model No. 1) yielded a C index of 0.653; R2 = 0.108. When TSv3 was added to Model number 1, the C index increased to 0.888; R2 = 0.572. However, age (p = 0.341), Bethesda category (p = 0.272), and ATA US pattern (p = 0.264) were nonsignificant, and other than TSv3 (p < 0.0001), male sex was the only non-MT parameter that potentially contributed to cancer/NIFTP risk (p = 0.095). The simplest and most efficient clinical model (No. 3) incorporated TSv3 and sex (C index = 0.889; R2 = 0.588). Conclusions: In this multicenter study of thyroid nodules with indeterminate cytology and MT, neither the ATA nor TI-RADS US scoring systems further informed the risk of cancer/NIFTP beyond that predicted by TSv3. Although age and Bethesda category were associated with cancer/NIFTP probability on univariate analysis, in sequential nomograms they provided limited incremental value above the high predictive ability of TSv3. Patient sex may contribute to cancer/NIFTP risk in thyroid nodules with indeterminate cytology.
Background: Molecular testing (MT) is commonly used to refine cancer probability in thyroid nodules with indeterminate cytology. Whether or not ultrasound (US) patterns and clinical parameters can further inform the risk of thyroid cancer in nodules predicted to be positive or negative by MT remains unknown. The aim of this study was to test if clinical parameters, including patient age, sex, nodule size (by US), Bethesda category (III, IV, V), US pattern (American Thyroid Association [ATA] vs. American College of Radiology Thyroid Image Reporting and Data System [TI-RADS] systems), radiation exposure, or family history of thyroid cancer can modify the probability of thyroid cancer or noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) predicted by MT. Methods: We studied 257 thyroid nodules in 232 patients from 10 study centers with indeterminate fine needle aspiration cytology and informative MT results using the ThyroSeq v3 genomic classifier (TSv3). Univariate and multivariate logistic regression was used for data analysis. Results: The presence of cancer/NIFTP was associated with positive TSv3 results (odds ratio 61.39, p < 0.0001). On univariate regression, patient sex, age, and Bethesda category were associated with cancer/NIFTP probability (p < 0.05 for each). Although ATA (p = 0.1211) and TI-RADS (p = 0.1359) US categories demonstrated positive trends, neither was significantly associated with cancer/NIFTP probability. A multivariate regression model incorporating the four most informative non-MT covariates (sex, age, Bethesda category, and ATA US pattern; Model No. 1) yielded a C index of 0.653; R2 = 0.108. When TSv3 was added to Model number 1, the C index increased to 0.888; R2 = 0.572. However, age (p = 0.341), Bethesda category (p = 0.272), and ATA US pattern (p = 0.264) were nonsignificant, and other than TSv3 (p < 0.0001), male sex was the only non-MT parameter that potentially contributed to cancer/NIFTP risk (p = 0.095). The simplest and most efficient clinical model (No. 3) incorporated TSv3 and sex (C index = 0.889; R2 = 0.588). Conclusions: In this multicenter study of thyroid nodules with indeterminate cytology and MT, neither the ATA nor TI-RADS US scoring systems further informed the risk of cancer/NIFTP beyond that predicted by TSv3. Although age and Bethesda category were associated with cancer/NIFTP probability on univariate analysis, in sequential nomograms they provided limited incremental value above the high predictive ability of TSv3. Patient sex may contribute to cancer/NIFTP risk in thyroid nodules with indeterminate cytology.
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Authors: David L Steward; Sally E Carty; Rebecca S Sippel; Samantha Peiling Yang; Julie A Sosa; Jennifer A Sipos; James J Figge; Susan Mandel; Bryan R Haugen; Kenneth D Burman; Zubair W Baloch; Ricardo V Lloyd; Raja R Seethala; William E Gooding; Simion I Chiosea; Cristiane Gomes-Lima; Robert L Ferris; Jessica M Folek; Raheela A Khawaja; Priya Kundra; Kwok Seng Loh; Carrie B Marshall; Sarah Mayson; Kelly L McCoy; Min En Nga; Kee Yuan Ngiam; Marina N Nikiforova; Jennifer L Poehls; Matthew D Ringel; Huaitao Yang; Linwah Yip; Yuri E Nikiforov Journal: JAMA Oncol Date: 2019-02-01 Impact factor: 31.777