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Establishment and validation of a nomogram model for predicting the survival probability of differentiated thyroid carcinoma patients: a comparison with the eighth edition AJCC cancer staging system

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Abstract

Purpose

This study aimed to develop a clinically predictive nomogram model to predict the survival probability of differentiated thyroid carcinoma patients and compare the value of this model with that of the eighth edition AJCC cancer staging system.

Methods

We selected 59,876 differentiated thyroid carcinoma patients diagnosed between 2004 and 2015 from the SEER database and separated those patients into a training set (70%) and a validation set (30%) randomly. We used Cox regression analysis to build the nomogram model (model 1) and the eighth edition AJCC cancer staging model (model 2). Then we compared the predictive accuracy, discrimination, and clinical usage of both models by calculating AUC (Area under the curve), C-index, as well as analyzing DCA (Decision Curve Analysis) performance respectively.

Results

AUCs of all predicted time points (12-month, 36-month, 60-month, and 120-month) of model 1 were 0.933, 0.913, 0.879, and 0.868 for the training set; 0.933, 0.926, 0.916, and 0.894 for the validation set. As for model 2, data were 0.938, 0.906, 0.866, and 0.847 for the training set; 0.924, 0.925, 0.912, and 0.867 for the validation set. C-indices of model 1 were higher than those of model 2 (0.923 vs. 0.918 for the training set, 0.938 vs. 0.930 for the validation set). DCA comparison showed that the net benefit of model 1 was bigger when comparing with that of model 2.

Conclusions

Model 1 provided with both better predictive accuracy and clinical usage compared with those of model 2 and might be able to predict the survival probability of differentiated thyroid carcinoma patients visually and accurately with a higher net benefit.

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Data availability

The datasets [GENERATED/ANALYZED] for this study can be found in the [Surveillance, Epidemiology, and End Results (SEER) Program] [https://seer.cancer.gov/]. Also, The datasets are available from the corresponding author on reasonable request.

Abbreviations

AJCC:

American Joint Committee on Cancer

SEER:

surveillance, epidemiology, and end results program

AUC:

area under the curve of ROC

DCA:

decision curve analysis

PTC:

papillary thyroid carcinoma

FTC:

follicular thyroid carcinoma

MTC:

medullary thyroid carcinoma

ATC:

anaplastic thyroid carcinoma

DTC:

differentiated thyroid carcinoma

TT:

total thyroidectomy

LO:

thyroid lobectomy

S/N T:

subtotal or near total thyroidectomy

HR:

Hazard ratio

TSHR:

thyroid-stimulating hormone receptor

ATA:

The American Thyroid Association

References

  1. H. Lim, S.S. Devesa, J.A. Sosa, D. Check, C.M. Kitahara, Trends in thyroid cancer incidence and Mortality in the United States, 1974–2013. JAMA. 317(13), 1338–1348 (2017). https://doi.org/10.1001/jama.2017.2719

    Article  PubMed  PubMed Central  Google Scholar 

  2. Shin HJ, Hwang KA, Choi KC. Antitumor effect of various phytochemicals on diverse types of thyroid cancers. Nutrients. 2019;11(1). https://doi.org/10.3390/nu11010125.

  3. V.A. LiVolsi, Papillary thyroid carcinoma: an update. Mod. Pathol. 24(Suppl 2), S1–S9 (2011). https://doi.org/10.1038/modpathol.2010.129

    Article  CAS  PubMed  Google Scholar 

  4. N.A. Cipriani, S. Nagar, S.P. Kaplan, M.G. White, T. Antic, P.M. Sadow et al. Follicular thyroid carcinoma: how have histologic diagnoses changed in the last half-century and what are the prognostic implications? Thyroid. 25(11), 1209–1216 (2015). https://doi.org/10.1089/thy.2015.0297

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. C.J. O’Neill, L. Vaughan, D.L. Learoyd, S.B. Sidhu, L.W. Delbridge, M.S. Sywak, Management of follicular thyroid carcinoma should be individualised based on degree of capsular and vascular invasion. Eur. J. Surg. Oncol. 37(2), 181–185 (2011). https://doi.org/10.1016/j.ejso.2010.11.005

    Article  PubMed  Google Scholar 

  6. E. Molinaro, C. Romei, A. Biagini, E. Sabini, L. Agate, S. Mazzeo et al. Anaplastic thyroid carcinoma: from clinicopathology to genetics and advanced therapies. Nat. Rev. Endocrinol. 13(11), 644–660 (2017). https://doi.org/10.1038/nrendo.2017.76

    Article  CAS  PubMed  Google Scholar 

  7. X.S. Sun, S.R. Sun, N. Guevara, N. Fakhry, P.Y. Marcy, S. Lassalle et al. Chemoradiation in anaplastic thyroid carcinomas. Crit. Rev. Oncol./Hematol. 86(3), 290–301 (2013). https://doi.org/10.1016/j.critrevonc.2012.10.006

    Article  CAS  Google Scholar 

  8. M.P. Pusztaszeri, M. Bongiovanni, W.C. Faquin, Update on the cytologic and molecular features of medullary thyroid carcinoma. Adv. Anat. Pathol. 21(1), 26–35 (2014). https://doi.org/10.1097/PAP.0000000000000004

    Article  PubMed  Google Scholar 

  9. J. Ding, W. Wu, J. Fang, J. Zhao, L. Jiang, Male sex is associated with aggressive behaviour and poor prognosis in Chinese papillary thyroid carcinoma. Sci. Rep. 10(1), 4141 (2020). https://doi.org/10.1038/s41598-020-60199-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. B.A. Kilfoy, S.S. Devesa, M.H. Ward, Y. Zhang, P.S. Rosenberg, T.R. Holford et al. Gender is an age-specific effect modifier for papillary cancers of the thyroid gland. Cancer Epidemiol. 18(4), 1092–1100 (2009). https://doi.org/10.1158/1055-9965.epi-08-0976

    Article  Google Scholar 

  11. Y.H. Lee, Y.M. Lee, T.Y. Sung, J.H. Yoon, D.E. Song, T.Y. Kim et al. Is male gender a prognostic factor for papillary thyroid microcarcinoma? Ann. Surg. Oncol. 24(7), 1958–1964 (2017). https://doi.org/10.1245/s10434-017-5788-4

    Article  PubMed  Google Scholar 

  12. J. Jonklaas, G. Nogueras-Gonzalez, M. Munsell, D. Litofsky, K.B. Ain, S.T. Bigos et al. The impact of age and gender on papillary thyroid cancer survival. J. Clin. Endocrinol. Metab. 97(6), E878–E887 (2012). https://doi.org/10.1210/jc.2011-2864

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. E. Yorke, A. Melck, S.M. Wiseman, Impact of sex on the clinicopathological characteristics and prognosis of papillary thyroid cancer. Can. J. Surg. 59(4), 287–288 (2016). https://doi.org/10.1503/cjs.003816

    Article  PubMed  PubMed Central  Google Scholar 

  14. S.L. Oyer, V.A. Smith, E.J. Lentsch, Sex is not an independent risk factor for survival in differentiated thyroid cancer. Laryngoscope. 123(11), 2913–2919 (2013). https://doi.org/10.1002/lary.24018

    Article  PubMed  Google Scholar 

  15. N.D. Perrier, J.D. Brierley, R.M. Tuttle, Differentiated and anaplastic thyroid carcinoma: major changes in the American Joint Committee on Cancer eighth edition cancer staging manual. CA Cancer J. Clin. 68(1), 55–63 (2018). https://doi.org/10.3322/caac.21439

    Article  PubMed  Google Scholar 

  16. M. Kim, Y.N. Kim, W.G. Kim, S. Park, H. Kwon, M.J. Jeon et al. Optimal cut-off age in the TNM Staging system of differentiated thyroid cancer: is 55 years better than 45 years? Clin. Endocrinol. 86(3), 438–443 (2017). https://doi.org/10.1111/cen.13254

    Article  Google Scholar 

  17. P. Trimboli, A. Piccardo, A. Signore, S. Valabrega, A. Barnabei, G. Santolamazza et al. Patient age is an independent risk factor of relapse of differentiated thyroid carcinoma and improves the performance of the American Thyroid Association Stratification System. Thyroid. 30(5), 713–719 (2020). https://doi.org/10.1089/thy.2019.0688

    Article  CAS  PubMed  Google Scholar 

  18. A. Metere, V. Aceti, L. Giacomelli, The surgical management of locally advanced well-differentiated thyroid carcinoma: changes over the years according to the AJCC 8th edition Cancer Staging Manual. Thyroid Res. 12, 10 (2019). https://doi.org/10.1186/s13044-019-0071-3

    Article  PubMed  PubMed Central  Google Scholar 

  19. I.J. Nixon, I. Ganly, S.G. Patel, F.L. Palmer, M.M. Whitcher, R.M. Tuttle et al. Thyroid lobectomy for treatment of well differentiated intrathyroid malignancy. Surgery. 151(4), 571–579 (2012). https://doi.org/10.1016/j.surg.2011.08.016

    Article  PubMed  Google Scholar 

  20. E.L. Mazzaferri, R.L. Young, J.E. Oertel, W.T. Kemmerer, C.P. Page, Papillary thyroid carcinoma: the impact of therapy in 576 patients. Medicine. 56(3), 171–196 (1977)

    Article  CAS  Google Scholar 

  21. K.Y. Bilimoria, D.J. Bentrem, C.Y. Ko, A.K. Stewart, D.P. Winchester, M.S. Talamonti et al. Extent of surgery affects survival for papillary thyroid cancer. Ann. Surg. 246(3), 375–381 (2007). https://doi.org/10.1097/SLA.0b013e31814697d9. discussion 81-4

    Article  PubMed  PubMed Central  Google Scholar 

  22. A. Iasonos, D. Schrag, G.V. Raj, K.S. Panageas, How to build and interpret a nomogram for cancer prognosis. J. Clin. Oncol. 26(8), 1364–1370 (2008). https://doi.org/10.1200/JCO.2007.12.9791

    Article  PubMed  Google Scholar 

  23. V.P. Balachandran, M. Gonen, J.J. Smith, R.P. DeMatteo, Nomograms in oncology: more than meets the eye. Lancet Oncol. 16(4), e173–e180. (2015). https://doi.org/10.1016/S1470-2045(14)71116-7

    Article  PubMed  PubMed Central  Google Scholar 

  24. X. He, C. Liu, Y. Chen, J. He, Y. Dong, Overweight without central obesity, cardiovascular risk, and all-cause mortality. Mayo Clin. Proc. 93(6), 709–720 (2018). https://doi.org/10.1016/j.mayocp.2018.01.027

    Article  PubMed  Google Scholar 

  25. Z. Zhang, J. Reinikainen, K.A. Adeleke, M.E. Pieterse, C.G.M. Groothuis-Oudshoorn, Time-varying covariates and coefficients in Cox regression models. Ann. Transl. Med. 6(7), 121 (2018). https://doi.org/10.21037/atm.2018.02.12

    Article  PubMed  PubMed Central  Google Scholar 

  26. Z. Zhang, Survival analysis in the presence of competing risks. Ann. Transl. Med. 5(3), 47 (2017). https://doi.org/10.21037/atm.2016.08.62

    Article  PubMed  PubMed Central  Google Scholar 

  27. Z. Lei, J. Li, D. Wu, Y. Xia, Q. Wang, A. Si et al. Nomogram for preoperative estimation of microvascular invasion risk in hepatitis B virus-related hepatocellular carcinoma within the Milan Criteria. JAMA Surg. 151(4), 356–363 (2016). https://doi.org/10.1001/jamasurg.2015.4257

    Article  PubMed  Google Scholar 

  28. Y. Wu, H. Hu, J. Cai, R. Chen, X. Zuo, H. Cheng et al. A prediction nomogram for the 3-year risk of incident diabetes among Chinese adults. Sci. Rep. 10(1), 21716 (2020). https://doi.org/10.1038/s41598-020-78716-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. X. Wang, M. Mao, Z. He, L. Zhang, H. Li, J. Lin et al. Development and validation of a prognostic nomogram in AFP-negative hepatocellular carcinoma. Int. J. Biol. Sci. 15(1), 221–228 (2019). https://doi.org/10.7150/ijbs.28720

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. J. Stanhiser, K. Chagin, J.E. Jelovsek, A model to predict risk of blood transfusion after gynecologic surgery. Am. J. Obstet. Gynecol. 216(5), 506.e1–.e14 (2017). https://doi.org/10.1016/j.ajog.2017.01.004

    Article  Google Scholar 

  31. A.J. Vickers, E.B. Elkin, Decision curve analysis: a novel method for evaluating prediction models. Med. Decis. Mak. 26(6), 565–574 (2006). https://doi.org/10.1177/0272989X06295361

    Article  Google Scholar 

  32. B. Van Calster, L. Wynants, J.F.M. Verbeek, J.Y. Verbakel, E. Christodoulou, A.J. Vickers et al. Reporting and interpreting decision curve analysis: a guide for investigators. Eur. Urol. 74(6), 796–804 (2018). https://doi.org/10.1016/j.eururo.2018.08.038

    Article  PubMed  PubMed Central  Google Scholar 

  33. Y. Deng, H. Li, M. Wang, N. Li, T. Tian, Y. Wu et al. Global burden of thyroid cancer from 1990 to 2017. JAMA Netw. Open. 3(6), e208759 (2020). https://doi.org/10.1001/jamanetworkopen.2020.8759

    Article  PubMed  PubMed Central  Google Scholar 

  34. N. Nilubol, L. Zhang, E. Kebebew, Multivariate analysis of the relationship between male sex, disease-specific survival, and features of tumor aggressiveness in thyroid cancer of follicular cell origin. Thyroid. 23(6), 695–702 (2013). https://doi.org/10.1089/thy.2012.0269

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. N. Lapteva, X.F. Huang, CCL5 as an adjuvant for cancer immunotherapy. Expert Opin. Biol. Ther. 10(5), 725–733 (2010). https://doi.org/10.1517/14712591003657128

    Article  CAS  PubMed  Google Scholar 

  36. L.J. Zhang, Y. Xiong, N. Nilubol, M. He, S. Bommareddi, X. Zhu et al. Testosterone regulates thyroid cancer progression by modifying tumor suppressor genes and tumor immunity. Carcinogenesis. 36(4), 420–428 (2015). https://doi.org/10.1093/carcin/bgv001

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. M. Banerjee, D.G. Muenz, J.T. Chang, M. Papaleontiou, M.R. Haymart, Tree-based model for thyroid cancer prognostication. J. Clin. Endocrinol. Metab. 99(10), 3737–3745 (2014). https://doi.org/10.1210/jc.2014-2197

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. J.G. Hollowell, N.W. Staehling, W.D. Flanders, W.H. Hannon, E.W. Gunter, C.A. Spencer et al. Serum TSH, T(4), and thyroid antibodies in the United States population (1988 to 1994): National Health and Nutrition Examination Survey (NHANES III). J. Clin. Endocrinol. Metab. 87(2), 489–499 (2002). https://doi.org/10.1210/jcem.87.2.8182

    Article  CAS  PubMed  Google Scholar 

  39. M.R. Haymart, D.J. Repplinger, G.E. Leverson, D.F. Elson, R.S. Sippel, J.C. Jaume et al. Higher serum thyroid stimulating hormone level in thyroid nodule patients is associated with greater risks of differentiated thyroid cancer and advanced tumor stage. J. Clin. Endocrinol. Metab. 93(3), 809–814 (2008). https://doi.org/10.1210/jc.2007-2215

    Article  CAS  PubMed  Google Scholar 

  40. J.A. Du Villard, R. Wicker, P. Crespo, D. Russo, S. Filetti, J.S. Gutkind et al. Role of the cAMP and MAPK pathways in the transformation of mouse 3T3 fibroblasts by a TSHR gene constitutively activated by point mutation. Oncogene. 19(42), 4896–4905 (2000). https://doi.org/10.1038/sj.onc.1203852

    Article  PubMed  Google Scholar 

  41. M.R. Haymart, Understanding the relationship between age and thyroid cancer. Oncologist. 14(3), 216–221 (2009). https://doi.org/10.1634/theoncologist.2008-0194

    Article  PubMed  Google Scholar 

  42. B.R. Haugen, E.K. Alexander, K.C. Bible, G.M. Doherty, S.J. Mandel, Y.E. Nikiforov et al. 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 

  43. D.S. Cooper, G.M. Doherty, B.R. Haugen, R.T. Kloos, S.L. Lee, S.J. Mandel et al. Revised American Thyroid Association management guidelines for patients with thyroid nodules and differentiated thyroid cancer. Thyroid. 19(11), 1167–1214 (2009). https://doi.org/10.1089/thy.2009.0110

    Article  PubMed  Google Scholar 

  44. R.W. Randle, N.M. Bushman, J. Orne, C.J. Balentine, E. Wendt, M. Saucke et al. Papillary thyroid cancer: the good and bad of the “good cancer. Thyroid. 27(7), 902–907 (2017). https://doi.org/10.1089/thy.2016.0632

    Article  PubMed  PubMed Central  Google Scholar 

  45. X. Liu, Y. Fan, Y. Liu, X. He, X. Zheng, J. Tan et al. The impact of radioactive iodine treatment on survival among papillary thyroid cancer patients according to the 7th and 8th editions of the AJCC/TNM staging system: a SEER-based study. Updates Surg. 72(3), 871–884 (2020). https://doi.org/10.1007/s13304-020-00773-y

    Article  PubMed  Google Scholar 

  46. K.A. Pathak, A. Mazurat, P. Lambert, T. Klonisch, R.W. Nason, Prognostic nomograms to predict oncological outcome of thyroid cancers. J. Clin. Endocrinol. Metab. 98(12), 4768–4775 (2013). https://doi.org/10.1210/jc.2013-2318

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

The authors thank Dr. Qiang Jia, who has always been a source of encouragement and inspiration.

Funding

Data collection of this research was funded by the National Natural Science Foundation of China grants (#81571709 and #81971650 to Zhaowei Meng, #81872169 to Xiangqian Zheng) and the design of this research was funded by the Key Project of Tianjin Science and Technology Committee Foundation grant (#16JCZDJC34300 to Zhaowei Meng), Tianjin Science and Technology Committee Foundation grants (#17JCYBJC25400 to Yaguang Fan, #19JCYBJC27400 to Xiangqian Zheng), Tianjin Medical University General Hospital New Century Excellent Talent Program (to Zhaowei Meng), Young and Middle-aged Innovative Talent Training Program from Tianjin Education Committee (to Zhaowei Meng) and Talent Fostering Program (the 131 Project) from Tianjin Education Committee and Tianjin Human Resources and Social Security Bureau (to Zhaowei Meng).

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Author notes

  1. These authors contributed equally: Ruyi Zhang, Mei Xu.

Authors and Affiliations

  1. Department of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, China

    Ruyi Zhang, Xiangxiang Liu, Miao Wang, Qiang Jia, Shen Wang & Zhaowei Meng

  2. Department of Pediatric, Tianjin Medical University General Hospital, Tianjin, China

    Mei Xu

  3. Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin City, Tianjin, China

    Xiangqian Zheng

  4. Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, China

    Xianghui He

  5. Hull York Medical School, University of Hull, Hull, UK

    Chao Huang

  6. Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, China

    Yaguang Fan, Heng Wu & Ke Xu

  7. Tianjin Key Laboratory of Acute Abdomen Disease Associated Organ Injury and ITCWM Repair, Institute of Acute Abdominal Diseases, Tianjin Nankai Hospital, Tianjin, China

    Dihua Li

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Contributions

R.Z. wrote the manuscript. Co-first authors R.Z. and M.X. contributed equally to the study. M.X., X.L., M.W., Q.J., S.W., X.Z., X.H., C.H., Y.F., and H.W. revised the manuscript. All authors contributed to manuscript revision, read, approved the submitted version, and agreed to be accountable for all aspects of the research in ensuring the accuracy of this study. All authors have given consent to the publication of this manuscript.

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Correspondence to Ke Xu, Dihua Li or Zhaowei Meng.

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Zhang, R., Xu, M., Liu, X. et al. Establishment and validation of a nomogram model for predicting the survival probability of differentiated thyroid carcinoma patients: a comparison with the eighth edition AJCC cancer staging system. Endocrine 74, 108–119 (2021). https://doi.org/10.1007/s12020-021-02717-x

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