Objective: If excellent response (ER) occurs after radioactive iodine (RAI) treatment in patients with differentiated thyroid carcinoma (DTC), the recurrence rate is low. Our study aims to predict ER at 6-24 months after RAI by using machine learning (ML) methods in which clinicopathological parameters are included in patients with DTC without distant metastasis.
Methods: Treatment response of 151 patients with DTC without distant metastasis and who received RAI treatment was determined (ER/nonER). Thyroidectomy ± neck dissection pathology data, laboratory, and imaging findings before and after RAI treatment were introduced to ML models.
Results: After RAI treatment, 118 patients had ER and 33 had nonER. Before RAI treatment, TgAb was positive in 29% of patients with ER and 55% of patients with nonER (p = 0.007). Eight of the ML models predicted ER with high area under the ROC curve (AUC) values (> 0.700). The model with the highest AUC value was extreme gradient boosting (AUC = 0.871), the highest accuracy shown by gradient boosting (81%).
Conclusions: ML models may be used to predict ER in patients with DTC without distant metastasis.
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| http://dx.doi.org/10.14639/0392-100X-N3029 | DOI Listing |
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