World Journal of Surgery

, Volume 39, Issue 12, pp 2928–2934 | Cite as

A Bedside Risk Calculator to Preoperatively Distinguish Follicular Thyroid Carcinoma from Follicular Variant of Papillary Thyroid Carcinoma

  • Brian R. Englum
  • John Pura
  • Shelby D. Reed
  • Sanziana A. Roman
  • Julie A. Sosa
  • Randall P. Scheri
Original Scientific Report

Abstract

Background

Follicular thyroid carcinoma (FTC) and follicular variant of papillary thyroid carcinoma (FV-PTC) are difficult entities to distinguish based on cytology prior to pathologic evaluation of surgical specimens but may have different treatment algorithms. The current study describes trends in rates of FTC versus FV-PTC in the U.S. and develops a risk assessment tool to aid clinicians in predicting final diagnosis and shaping treatment plans.

Methods

Relative rates of FTC and FV-PTC in the surveillance, epidemiology, and end results (SEER) database were evaluated for temporal trends from 1988 to 2011. Using multivariable logistic regression, a simplified scoring system was developed to estimate the risk of FTC versus FV-PTC using patient and tumor characteristics. The National Cancer Data Base was used for model validation.

Results and Discussion

Of 115,091 thyroid cancer cases in the SEER database from 1988 to 2011, 23,980 involved FTC (n = 5056; 21 %) or FV-PTC (n = 18,924; 79 %). In 1988, half of follicular cases were FV-PTC; however, FV-PTC accounted for over 85 % of these lesions by 2010. Increasing age >45 years, male gender, black race, increasing tumor size, and distant metastases were strongly associated with increased risk of FTC, while lymph node disease and extrathyroidal extension were associated with FV-PTC. A bedside risk assessment nomogram using these preoperative variables classified patient risk of FTC from 2 to 70 %. FV-PTC has become the dominant malignancy with follicular cytology, accounting for >85 % of these cases. A simple bedside risk assessment tool can risk stratify patients with follicular lesions and inform patient and clinician discussions and decision making.

Supplementary material

268_2015_3192_MOESM1_ESM.docx (115 kb)
Supplementary material 1 (DOCX 115 kb)

References

  1. 1.
    Siegel R, Ma J, Zou Z et al (2014) Cancer statistics, 2014. CA Cancer J Clin 64:9–29CrossRefPubMedGoogle Scholar
  2. 2.
    Pellegriti G, Frasca F, Regalbuto C et al (2013) Worldwide increasing incidence of thyroid cancer: update on epidemiology and risk factors. J Cancer Epidemiol 2013:965212PubMedCentralCrossRefPubMedGoogle Scholar
  3. 3.
    DeSantis CE, Lin CC, Mariotto AB et al (2014) Cancer treatment and survivorship statistics, 2014. CA Cancer J Clin 64:252–271CrossRefPubMedGoogle Scholar
  4. 4.
    Davies L, Welch HG (2006) Increasing incidence of thyroid cancer in the United States, 1973-2002. JAMA 295:2164–2167CrossRefPubMedGoogle Scholar
  5. 5.
    Aschebrook-Kilfoy B, Grogan RH, Ward MH et al (2013) Follicular thyroid cancer incidence patterns in the United States, 1980-2009. Thyroid 23:1015–1021PubMedCentralCrossRefPubMedGoogle Scholar
  6. 6.
    Yu XM, Schneider DF, Leverson G et al (2013) Follicular variant of papillary thyroid carcinoma is a unique clinical entity: a population-based study of 10,740 cases. Thyroid 23:1263–1268PubMedCentralCrossRefPubMedGoogle Scholar
  7. 7.
    Lin HW, Bhattacharyya N (2010) Clinical behavior of follicular variant of papillary thyroid carcinoma: presentation and survival. Laryngoscope 120:712–716CrossRefPubMedGoogle Scholar
  8. 8.
    Lin HS, Komisar A, Opher E et al (2000) Follicular variant of papillary carcinoma: the diagnostic limitations of preoperative fine-needle aspiration and intraoperative frozen section evaluation. Laryngoscope 110:1431–1436CrossRefPubMedGoogle Scholar
  9. 9.
    Kesmodel SB, Terhune KP, Canter RJ et al (2003) The diagnostic dilemma of follicular variant of papillary thyroid carcinoma. Surgery 134:1005–1012CrossRefPubMedGoogle Scholar
  10. 10.
    Cibas ES, Ali SZ (2009) The bethesda system for reporting thyroid cytopathology. Am J Clin Pathol 132:658–665CrossRefPubMedGoogle Scholar
  11. 11.
    Bongiovanni M, Spitale A, Faquin WC et al (2012) The bethesda system for reporting thyroid cytopathology: a meta-analysis. Acta Cytol 56:333–339CrossRefPubMedGoogle Scholar
  12. 12.
    Howlader N, Noone AM, Krapcho M et al (2014) SEER cancer statistics review, 1975-2011. National Cancer Institute, BethesdaGoogle Scholar
  13. 13.
    American College of Surgeons. National Cancer Data Base 2013 [3/10/2014]. http://www.facs.org/cancer/ncdb/
  14. 14.
    Committee on Cancer. FORDS: Facility Oncology Registry Data Standards, Revised for 2013: Commission on Cancer; 2013 [6/29/2014]. http://www.facs.org/cancer/coc/fords/fords-manual-2013.pdf
  15. 15.
    Adamo MB, Johnson CH, Ruhl JL et al (2013) 2013 SEER program coding and staging manual. National Cancer Institute, BethesdaGoogle Scholar
  16. 16.
    Iasonos A, Schrag D, Raj GV et al (2008) How to build and interpret a nomogram for cancer prognosis. J Clin Oncol 26:1364–1370CrossRefPubMedGoogle Scholar
  17. 17.
    Albores-Saavedra J, Henson DE, Glazer E et al (2007) Changing patterns in the incidence and survival of thyroid cancer with follicular phenotype–papillary, follicular, and anaplastic: a morphological and epidemiological study. Endocr Pathol 18:1–7CrossRefPubMedGoogle Scholar
  18. 18.
    Baloch ZW, Livolsi VA (2002) Follicular-patterned lesions of the thyroid: the bane of the pathologist. Am J Clin Pathol 117:143–150CrossRefPubMedGoogle Scholar
  19. 19.
    LiVolsi VA, Baloch ZW (2005) Use and abuse of frozen section in the diagnosis of follicular thyroid lesions. Endocr Pathol 16:285–293CrossRefPubMedGoogle Scholar
  20. 20.
    Shen PU, Kuhel WI, Yang GC et al (1997) Intraoperative touch-imprint cytological diagnosis of follicular variant of papillary thyroid carcinoma. Diagn Cytopathol 17:80–83CrossRefPubMedGoogle Scholar
  21. 21.
    Cooper DS, Doherty GM, Haugen BR et al (2009) Revised American Thyroid Association management guidelines for patients with thyroid nodules and differentiated thyroid cancer. Thyroid 19:1167–1214CrossRefPubMedGoogle Scholar
  22. 22.
    Alexander EK, Kennedy GC, Baloch ZW et al (2012) Preoperative diagnosis of benign thyroid nodules with indeterminate cytology. N Engl J Med 367:705–715CrossRefPubMedGoogle Scholar
  23. 23.
    Chudova D, Wilde JI, Wang ET et al (2010) Molecular classification of thyroid nodules using high-dimensionality genomic data. J Clin Endocrinol Metab 95:5296–5304CrossRefPubMedGoogle Scholar
  24. 24.
    McFadden DG, Dias-Santagata D, Sadow PM et al (2014) Identification of oncogenic mutations and gene fusions in the follicular variant of papillary thyroid carcinoma. J Clin Endocrinol Metab 99:E2457–E2462PubMedCentralCrossRefPubMedGoogle Scholar
  25. 25.
    Nikiforov YE, Carty SE, Chiosea SI et al (2014) Highly accurate diagnosis of cancer in thyroid nodules with follicular neoplasm/suspicious for a follicular neoplasm cytology by ThyroSeq v2 next-generation sequencing assay. Cancer 120:3627–3634CrossRefPubMedGoogle Scholar
  26. 26.
    Nikiforov YE, Ohori NP, Hodak SP et al (2011) Impact of mutational testing on the diagnosis and management of patients with cytologically indeterminate thyroid nodules: a prospective analysis of 1056 FNA samples. J Clin Endocrinol Metab 96:3390–3397PubMedCentralCrossRefPubMedGoogle Scholar
  27. 27.
    Armstrong MJ, Yang H, Yip L et al (2014) PAX8/PPARgamma rearrangement in thyroid nodules predicts follicular-pattern carcinomas, in particular the encapsulated follicular variant of papillary carcinoma. Thyroid 24:1369–1374PubMedCentralCrossRefPubMedGoogle Scholar
  28. 28.
    Cancer Genome Atlas Research N (2014) Integrated genomic characterization of papillary thyroid carcinoma. Cell 159:676–690CrossRefGoogle Scholar
  29. 29.
    Lee L, How J, Tabah RJ et al (2014) Cost-effectiveness of molecular testing for thyroid nodules with atypia of undetermined significance cytology. J Clin Endocrinol Metab 99:2674–2682CrossRefPubMedGoogle Scholar

Copyright information

© Société Internationale de Chirurgie 2015

Authors and Affiliations

  1. 1.Department of Surgery, Duke University Medical CenterDuke University School of MedicineDurhamUSA
  2. 2.Duke Clinical Research InstituteDurhamUSA

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