Clinicopathological features of radioactive iodine-refractory differentiated thyroid cancer / 重庆医学

ABSTRACT

Objective To investigate the clinicopathological characteristics of radioactive Iodine-refrac-tory differentiated thyroid cancer(RAIR-DTC)to provide a clinical evidence for early prediction of the thyroid cancer patients with radioactive Iodine-refractory(RAIR).Methods The data of 84 patients with undergoing thyroidectomy and 131I therapy in PLA 960 hospital from January 2010 to December 2019 were retrospectively analyzed.Thirty-nine patients with diagnosed RAIR-DTC served as the study group and 45 cases of radioactive iodine-avid differentiated thyroid cancer(RAIA-DTC)served as the control group.The clinicopathological characteristics were compared between the two groups.The logistic regression was used to analyze the inde-pendent risk factors of RAIR-DTC,and the RAIR-DTC prediction model was established.Results Compared with the RAIA-DTC group,the RAIR-DTC group had more iodine treatment times,the proportions of the pa-tients with age ≥55 years old,total iodine therapeutic dose,distant metastasis,TNM stage Ⅳ,high-risk sub-types and focal calcification were higher,the tumor maximum diameter was greater,the number of lymph node metastases was more and the probability of Ⅱ,Ⅰ+Ⅱ and non-central lymph node metastases was higher(P＞0.05).The progression-free survival rate had statistical difference between the two groups(P＜0.05).The total survival rate had no statistical difference between the two groups(P＞0.05).The binary logistic re-gression analysis results showed that the distant metastasis,high-risk histological subtype and maximum tumor diameter ≥10.5 mm were the independent risk factors for RAIR-DTC.The obtained fitting equation logit(P)=-2.259+3.330X1+2.287X2+1.606X3,the ROC curve was used to calculate the truncation val-ue of the fitted equation as-0.312 5,when logit(P)＞-0.312 5,it might develop into RAIR-DTC.Conclusion The clinicopathological characteristics of the patients with differentiated thyroid cancer could ef-fectively predict RAIR.