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Comparison of different systems of ultrasound (US) risk stratification for malignancy in elderly patients with thyroid nodules. Real world experience

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Abstract

Purpose

To comparatively assess the performance of three sonographic classification systems, American Thyroid Association (ATA), the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS), and American Association of Clinical Endocrinologists (AACE)/American College of Endocrinology (ACE)/Associazione Medici Endocrinologi (AME) in identifying malignant nodules in an elderly population.

Methods

Cross-sectional study of patients referred for fine needle aspiration biopsy in an academic center for the elderly. One nodule/patient was considered. Nodules classified Bethesda V/VI were considered malignant. Receiver operating characteristics (ROC) curves were established and compared to evaluate diagnostic performance. Malignancy among biopsies below the size cutoff for each ultrasound classification was also compared.

Results

One thousand, eight hundred sixty-seven patients (92% females); median (Q1–Q3), age 71 (67–76) years, were studied showing 82.8% benign (Bethesda II) and 2.6% malignant cytology. The three classifications correctly identified malignancy (P < 0.01). Nonetheless, in the ATA and AACE/ACE/AME 16 and 2 malignant nodules, respectively, were unclassifiable. Including unclassified malignant nodules (n = 1234, malignant = 50), comparison of the ROC curves showed lower performance of ATA [area under the curve (AUC) = ATA (0.49) vs. ACR TI-RADS (0.62), p = 0.008 and ATA vs. AACE/ACE/AME (0.59), p = 0.022]. Proportion of below size cutoff biopsies for ATA, ACR TI-RADS, and AACE/ACE/AME was different [16, 42, and 29% (all p < 0.001)], but no differences in malignancy rate were observed in these nodules.

Conclusion

The present study is the first to validate in elderly patients these classifications showing that AACE/ACE/AME and ACR TI-RADS can predict thyroid malignancy more accurately than the ATA when unclassifiable malignant nodules are considered. Moreover, in this aged segment of the population, the use of ACR TI-RADS avoided more invasive procedures.

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References

  1. C. Durante, G. Grani, L. Lamartina, S. Filetti, S.J. Mandel, D.S. Cooper, The diagnosis and management of thyroid nodules: a review. JAMA 319(9), 914–924 (2018). https://doi.org/10.1001/jama.2018.0898

    Article  PubMed  Google Scholar 

  2. C. Reiners, K. Wegscheider, H. Schicha, P. Theissen, R. Vaupel, R. Wrbitzky, P.M. Schumm-Draeger, Prevalence of thyroid disorders in the working population of Germany: ultrasonography screening in 96,278 unselected employees. Thyroid 14(11), 926–932 (2004). https://doi.org/10.1089/thy.2004.14.926

    Article  PubMed  Google Scholar 

  3. N. Kwong, M. Medici, T.E. Angell, X. Liu, E. Marqusee, E.S. Cibas, J.F. Krane, J.A. Barletta, M.I. Kim, P.R. Larsen, E.K. Alexander, The influence of patient age on thyroid nodule formation, multinodularity, and thyroid cancer risk. J. Clin. Endocrinol. Metab. 100(12), 4434–4440 (2015). https://doi.org/10.1210/jc.2015-3100

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. J.J. Diez,, Goiter in adult patients aged 55 years and older: etiology and clinical features in 634 patients. J. Gerontol. A Biol. Sci. Med. Sci. 60(7), 920–923 (2005). https://doi.org/10.1093/gerona/60.7.920

    Article  PubMed  Google Scholar 

  5. S. Sorrenti, E. Baldini, F. Tartaglia, A. Catania, S. Arcieri, D. Pironi, P.G. Calo, A. Filippini, S. Ulisse, Nodular thyroid disease in the elderly: novel molecular approaches for the diagnosis of malignancy. Aging Clin. Exp. Res. 29(Suppl 1), 7–13 (2017). https://doi.org/10.1007/s40520-016-0654-y

    Article  PubMed  Google Scholar 

  6. B.R. Haugen, E.K. Alexander, K.C. Bible, G.M. Doherty, S.J. Mandel, Y.E. Nikiforov, F. Pacini, G.W. Randolph, A.M. Sawka, M. Schlumberger, K.G. Schuff, S.I. Sherman, J.A. Sosa, D.L. Steward, R.M. Tuttle, L. Wartofsky, 2015 American Thyroid Association Management Guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: the American Thyroid Association Guidelines Task Force on thyroid nodules and differentiated thyroid cancer. Thyroid 26(1), 1–133 (2016). https://doi.org/10.1089/thy.2015.0020

    Article  PubMed  PubMed Central  Google Scholar 

  7. H. Gharib, E. Papini, J.R. Garber, D.S. Duick, R.M. Harrell, L. Hegedus, R. Paschke, R. Valcavi, P. Vitti, American Association of Clinical Endocrinologists, American College of Endocrinology, and Associazione Medici Endocrinologi Medical Guidelines for clinical practice for the diagnosis and management of thyroid nodules–2016 update. Endocr. Pract. 22(5), 622–639 (2016). https://doi.org/10.4158/EP161208.GL

    Article  PubMed  Google Scholar 

  8. F.N. Tessler, W.D. Middleton, E.G. Grant, J.K. Hoang, L.L. Berland, S.A. Teefey, J.J. Cronan, M.D. Beland, T.S. Desser, M.C. Frates, L.W. Hammers, U.M. Hamper, J.E. Langer, C.C. Reading, L.M. Scoutt, A.T. Stavros, ACR thyroid imaging, reporting and data system (TI-RADS): white paper of the ACR TI-RADS committee. J. Am. Coll. Radiol. 14(5), 587–595 (2017).https://doi.org/10.1016/j.jacr.2017.01.046

    Article  PubMed  Google Scholar 

  9. G. Grani, L. Lamartina, V. Cantisani, M. Maranghi, P. Lucia, C. Durante, Interobserver agreement of various thyroid imaging reporting and data systems. Endocr. Connect. 7(1), 1–7 (2018). https://doi.org/10.1530/EC-17-0336

    Article  PubMed  Google Scholar 

  10. E.S. Cibas, S.Z. Ali, The bethesda system for reporting thyroid cytopathology. Thyroid 19(11), 1159–1165 (2009). https://doi.org/10.1089/thy.2009.0274

    Article  PubMed  Google Scholar 

  11. G. Brenta, M. Schnitman, L. Bonnahon, S. Besuschio, C. Zuk, G. De Barrio, C. Peruzzotti, G. Saubidet, Evaluation of innovative skin-marking technique performed before thyroid ultrasound-guided fine-needle aspiration biopsies. Endocr. Pract. 8(1), 5–9 (2002). https://doi.org/10.4158/EP.8.1.5

    Article  PubMed  Google Scholar 

  12. E.R. DeLong, D.M. DeLong, D.L. Clarke-Pearson, Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44(3), 837–845 (1988)

    Article  CAS  Google Scholar 

  13. X. Robin, N. Turck, A. Hainard, N. Tiberti, F. Lisacek, J.C. Sanchez, M. Muller, pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinform. 12, 77 (2011). https://doi.org/10.1186/1471-2105-12-77

    Article  Google Scholar 

  14. Z. Wang, C.M. Vyas, O. Van Benschoten, M.A. Nehs, F.D. Moore Jr., E. Marqusee, J.F. Krane, M.I. Kim, H.T. Heller, A.A. Gawande, M.C. Frates, P.M. Doubilet, G.M. Doherty, N.L. Cho, E.S. Cibas, C.B. Benson, J.A. Barletta, A.M. Zavacki, P.R. Larsen, E.K. Alexander, T.E. Angell, Quantitative analysis of the benefits and risk of thyroid nodule evaluation in patients ≥70 years old. Thyroid 28(4), 465–471 (2018). https://doi.org/10.1089/thy.2017.0655

    Article  PubMed  Google Scholar 

  15. J.H. Yoon, H.S. Lee, E.K. Kim, H.J. Moon, J.Y. Kwak, Malignancy risk stratification of thyroid nodules: comparison between the thyroid imaging reporting and data system and the 2014 American Thyroid Association Management Guidelines. Radiology 278(3), 917–924 (2016). https://doi.org/10.1148/radiol.2015150056

    Article  PubMed  Google Scholar 

  16. A. Persichetti, E. Di Stasio, R. Guglielmi, G. Bizzarri, S. Taccogna, I. Misischi, F. Graziano, L. Petrucci, A. Bianchini, E. Papini, Predictive value of malignancy of thyroid nodule ultrasound classification systems: a prospective study. J. Clin. Endocrinol. Metab. 103(4), 1359–1368 (2018). https://doi.org/10.1210/jc.2017-01708

    Article  PubMed  Google Scholar 

  17. A. Lauria Pantano, E. Maddaloni, S.I. Briganti, G. Beretta Anguissola, E. Perrella, C. Taffon, A. Palermo, P. Pozzilli, S. Manfrini, A. Crescenzi, Differences between ATA, AACE/ACE/AME and ACR TI-RADS ultrasound classifications performance in identifying cytological high-risk thyroid nodules. Eur. J. Endocrinol. 178(6), 595–603 (2018). https://doi.org/10.1530/EJE-18-0083

    Article  CAS  PubMed  Google Scholar 

  18. M.I. Vera, T. Merono, M.A. Urrutia, C. Parisi, Y. Morosan, M. Rosmarin, M. Schnitman, F. Brites, S. Grisendi, M.S. Serrano, W. Luciani, L. Serrano, C. Zuk, G. De Barrio, C. Cejas, M.C. Faingold, G. Brenta, Differential profile of ultrasound findings associated with malignancy in mixed and solid thyroid nodules in an elderly female population. J. Thyroid Res. 2014, 761653 (2014). https://doi.org/10.1155/2014/761653

    Article  PubMed  PubMed Central  Google Scholar 

  19. C. Shi, S. Li, T. Shi, B. Liu, C. Ding, H. Qin, Correlation between thyroid nodule calcification morphology on ultrasound and thyroid carcinoma. J. Int. Med. Res. 40(1), 350–357 (2012). https://doi.org/10.1177/147323001204000136

    Article  CAS  PubMed  Google Scholar 

  20. Z. Wang, H. Zhang, P. Zhang, L. He, W. Dong, Diagnostic value of ultrasound-detected calcification in thyroid nodules. Ann. Acad. Med. Singap. 43(2), 102–106 (2014)

    PubMed  Google Scholar 

  21. G. Grani, L. Lamartina, V. Ascoli, D. Bosco, M. Biffoni, L. Giacomelli, M. Maranghi, R. Falcone, V. Ramundo, V. Cantisani, S. Filetti, C. Durante, Reducing the number of unnecessary thyroid biopsies while improving diagnostic accuracy: toward the “Right” TIRADS. J. Clin. Endocrinol. Metab. 104(1), 95–102 (2019). https://doi.org/10.1210/jc.2018-01674

    Article  PubMed  Google Scholar 

  22. T. Xu, Y. Wu, R.X. Wu, Y.Z. Zhang, J.Y. Gu, X.H. Ye, W. Tang, S.H. Xu, C. Liu, X.H. Wu, Validation and comparison of three newly-released thyroid imaging reporting and data systems for cancer risk determination. Endocrine 64(2), 299–307 (2019). https://doi.org/10.1007/s12020-018-1817-8

    Article  CAS  PubMed  Google Scholar 

  23. R.R. Tappouni, J.N. Itri, T.S. McQueen, N. Lalwani, J.J. Ou, ACR TI-RADS: pitfalls, solutions, and future directions. Radiographics 39(7), 2040–2052 (2019). https://doi.org/10.1148/rg.2019190026

    Article  PubMed  Google Scholar 

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Acknowledgements

To the technicians and fellows of the Radiology Department who assisted in filling out the US characteristics forms. We thank Dr. Pol Castellano Escuder for his support on ROC curve comparison and other statistical analyses.

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Authors and Affiliations

  1. Endocrinology Department, Cesar Milstein Hospital, CABA, Buenos Aires, Argentina

    Fernando Di Fermo, Noelia Sforza, Melanie Rosmarin, Yanina Morosan Allo, Carina Parisi, Jimena Santamaria, Nestor Pacenza, Cristina Faingold & Gabriela Brenta

  2. Radiology Department, Cesar Milstein Hospital, CABA, Buenos Aires, Argentina

    Carlos Zuk

  3. Clinical Biochemistry, School of Pharmacy and Biochemistry, University of Buenos Aires, CABA, Buenos Aires, Argentina

    Florencia Ferraro & Tomas Meroño

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  1. Fernando Di Fermo
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Correspondence to Gabriela Brenta.

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Di Fermo, F., Sforza, N., Rosmarin, M. et al. Comparison of different systems of ultrasound (US) risk stratification for malignancy in elderly patients with thyroid nodules. Real world experience. Endocrine 69, 331–338 (2020). https://doi.org/10.1007/s12020-020-02295-4

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