PDF herunterladen
CC BY-NC-ND 4.0 · World J Nucl Med 2021; 20(03): 253-259
DOI: 10.4103/wjnm.WJNM_104_20
Original Article

Clinical predictors of I-131 therapy failure in differentiated thyroid cancer by machine learning: A single-center experience

David J. Lubin
1   Departments of Radiology and Nuclear Medicine, University Hospital, SUNY Upstate, Syracuse, NY, USA
2   Department of Nuclear Medicine, University Hospital, SUNY Upstate, Syracuse, NY, USA
,
Caleb Tsetse
1   Departments of Radiology and Nuclear Medicine, University Hospital, SUNY Upstate, Syracuse, NY, USA
,
Mohammad S. Khorasani
3   Department of Surgery, University Hospital, College of Medicine, Upstate Medical University, SUNY Upstate, Syracuse, NY, USA
,
Massoud Allahyari
1   Departments of Radiology and Nuclear Medicine, University Hospital, SUNY Upstate, Syracuse, NY, USA
,
Mary McGrath
1   Departments of Radiology and Nuclear Medicine, University Hospital, SUNY Upstate, Syracuse, NY, USA
2   Department of Nuclear Medicine, University Hospital, SUNY Upstate, Syracuse, NY, USA
› Institutsangaben
› Weitere Informationen
Auch verfügbar auf
   Lizenzen und Reprints

Abstract

Well-differentiated thyroid carcinoma is predominantly a slow-growing malignancy, amendable to treatment, and has an excellent prognosis following thyroidectomy and radioiodine (RAI) therapy. However, patients who fail the initial RAI treatment attempt may require repeated RAI or other treatments and with this, comes an associated impact on patient quality of life. Therefore, the anticipation of patients in whom there is a higher risk of RAI failure may help in patient risk stratification and subsequent management. We conducted a retrospective review to determine the factors associated with initial RAI therapy failure in well-differentiated thyroid cancer patients. Using scikit-learn from Python, we implemented a machine-learning algorithm to determine the clinical patient factors associated with a higher likelihood of treatment resistance. We found that clinical factors such as tumor focality (P = 0.026) and lymph node invasion at surgical resection (P = 0.0135) were significantly associated with initial treatment failure following RAI. Elevated serum thyroglobulin (Tg) and Tg antibody levels following surgery but before RAI were also associated with treatment resistance (P < 0.0001 and P = 0.011 respectively). Less expected factors such as decreased time from surgery to RAI were also associated with treatment failure, however not to a statistically significant degree (P > 0.064). Clinical outcomes following RAI can be stratified by identifying factors that are associated with initial treatment failure. These findings can help restratify patients for RAI treatment and change patient management in certain cases. Such stratification will ultimately help to optimize successful treatment outcomes and improve patient quality of life.

Keywords

Machine learning - radioiodine ablation - restratification - thyroglobulin - thyroid cancer

Financial support and sponsorship

Nil.




Publikationsverlauf

Eingereicht: 28. Juli 2020

Angenommen: 18. Oktober 2020

Artikel online veröffentlicht:
24. März 2022

© 2021. Sociedade Brasileira de Neurocirurgia. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commecial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Thieme Medical and Scientific Publishers Pvt. Ltd.
A-12, 2nd Floor, Sector 2, Noida-201301 UP, India

 

  • References

  • 1 American Thyroid Association (ATA) Guidelines Taskforce on Thyroid Nodules and Differentiated Thyroid Cancer, Cooper DS, Doherty GM, Haugen BR, Kloos RT, Lee SL, et al. Revised American Thyroid Association management guidelines for patients with thyroid nodules and differentiated thyroid cancer. Thyroid 2009;19:1167-214.
  • 2 Tuttle RM, Ahuja S, Avram AM, Bernet VJ, Bourguet P, Daniels GH, et al. Controversies, consensus, and collaboration in the use of (131)I therapy in differentiated thyroid cancer: A joint statement from the American Thyroid Association, the European Association of Nuclear Medicine, the Society of Nuclear Medicine and Molecular Imaging, and the European Thyroid Association. Thyroid 2019;29:461-70.
  • 3 Mendoza ES, Lopez AA, Valdez VA, Cunanan EC, Matawaran BJ, Kho SA, et al. Predictors of incomplete response to therapy among Filipino patients with papillary thyroid cancer in a tertiary hospital. J Endocrinol Invest 2016;39:55-62.
  • 4 Sciuto R, Romano L, Rea S, Marandino F, Sperduti I, Maini CL. Natural history and clinical outcome of differentiated thyroid carcinoma: A retrospective analysis of 1503 patients treated at a single institution. Ann Oncol 2009;20:1728-35.
  • 5 Aschebrook-Kilfoy B, Schechter RB, Shih YC, Kaplan EL, Chiu BC, Angelos P, et al. The clinical and economic burden of a sustained increase in thyroid cancer incidence. Cancer Epidemiol Biomarkers Prev 2013;22:1252-9.
  • 6 Pedregosa, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, et al. Scikit-learn: Machine learning in python. JMLR 2011;12:2825-30.
  • 7 Klain M, Zampella E, Manganelli M, Gaudieri V, Nappi C, D'Antonio A, et al. Risk of structural persistent disease in pediatric patients with low or intermediate risk differentiated thyroid cancer. Endocrine 10 Jun 2020, DOI:10.1007/s12020-020-02379-1, PMID: 32529282.
  • 8 Buitinck L, Louppe G, Blondel M, Pedregosa F, Mueller A, Grisel O, et al. API design for machine learning software: Experiences from the scikit-learn project, European Conference on Machine Learning and Principles and Practices of Knowledge Discovery in Databases. arXiv 2013; arXiv:1309.0238v1.
  • 9 Available from: https://towardsdatascience.com.[Last Accessed on 2020 Dec 24].
  • 10 Cao CJ, Dou CY, Lian J, Luan ZS, Zhou W, Xie W, et al. Clinical outcomes and associated factors of radioiodine-131 treatment in differentiated thyroid cancer with cervical lymph node metastasis. Oncol Lett 2018;15:8141-8.
  • 11 Ciarallo A, Rivera J. Radioactive iodine therapy in differentiated thyroid cancer: 2020 update. AJR Am J Roentgenol 2020;215:285-91.
  • 12 Klain M, Zampella E, Manganelli M, Gaudieri V, Nappi C, D'Antonio A, et al. Risk of structural persistent disease in pediatric patients with low or intermediate risk differentiated thyroid cancer. Endocrine 10 Jun 2020, DOI:10.1007/s12020-020-02379-1, PMID: 32529282.
  • 13 Lo TE, Uy AT, Maningat PD. Well-differentiated thyroid cancer: The Philippine general hospital experience. Endocrinol Metab (Seoul) 2016;31:72-9.
  • 14 Ross DS, Litofsky D, Ain KB, Bigos T, Brierley JD, Cooper DS, et al. Recurrence after treatment of micropapillary thyroid cancer. Thyroid 2009;19:1043-8.