Research Papers:

Prediction of thyroidal 131I effective half-life in patients with Graves’ disease

Ruiguo Zhang, Guizhi Zhang, Renfei Wang, Jian Tan _, Yajing He and Zhaowei Meng

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Oncotarget. 2017; 8:80934-80940. https://doi.org/10.18632/oncotarget.20849

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Ruiguo Zhang1, Guizhi Zhang1, Renfei Wang1, Jian Tan1, Yajing He1 and Zhaowei Meng1

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

Correspondence to:

Jian Tan, email: [email protected]

Keywords: Graves’ disease, effective half-life, radioiodine therapy, iodine uptake, predictive model

Received: June 27, 2017    Accepted: August 07, 2017    Published: September 12, 2017


Purpose: Calculation of effective thyroidal half-life (Teff) of iodine-131(131I) is cumbersome and tedious. The aim of this study was to investigate factors that could be used to predict Teff and to develop a Teff prediction model in Graves’ disease patients.

Methods: A total of 256 patients with GD were involved in this study. We investigated the influences of age, gender, disease duration, thyroid weight, antithyroid drugs, antithyroid drugs discontinuation period (ADP), thyroid function indexes, thyroid autoantibodies, thyroid-stimulating hormone receptor antibody (TRAb) level and radioactive iodine uptake (RAIU) values before 131I therapy on Teff, applying univariate and multivariate analyses.

Results: Teff correlated negatively with thyroid peroxidase antibody, TRAb and thyroid weight, as well as positively with 24-hour, 48-hour, and 72-hour RAIU. Additionally, a longer ADP (especially≥ 14d) or without antithyroid drugs before 131I therapy led to a longer Teff. Stepwise multiple linear regression analysis showed that 24-hour and 72-hour RAIU were statistically significant predictors of Teff (P<0.001). The relationship was: predictive Teff=5.277+0.295×72-hour RAIU-0.217×24-hour RAIU (r =0.865, P < 0.001).

Conclusion: The present results indicate that prediction of Teff from 24-hour and 72-hour RAIU is feasible in patients with Graves’ disease, with high prediction accuracy.

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