Clinico-pathological factors associated with radioiodine refractory differentiated thyroid carcinoma status

Author:

Schubert L.,Mbekwe-Yepnang A. M.,Wassermann J.,Braik-Djellas Y.,Jaffrelot L.,Pani F.,Deniziaut G.,Lussey-Lepoutre C.,Chereau N.,Leenhardt L.,Bernier M- O.,Buffet C.ORCID

Abstract

Abstract Purpose Risk factors for developing radioiodine refractory thyroid cancer (RAIR-TC) have rarely been analyzed. The purpose of the present study was to find clinical and pathological features associated with the occurrence of RAIR-disease in differentiated thyroid cancers (DTC) and to establish an effective predictive risk score. Methods All cases of RAIR-DTC treated in our center from 1990 to 2020 were retrospectively reviewed. Each case was matched randomly with at least four RAI-avid DTC control patients based on histological and clinical criteria. Conditional logistic regression was used to examine the association between RAIR-disease and variables with univariate and multivariate analyses. A risk score was then developed from the multivariate conditional logistic regression model to predict the risk of refractory disease occurrence. The optimal cut-off value for predicting the occurrence of RAIR-TC was assessed by receiver operating characteristic (ROC) curves and Youden’s statistic. Results We analyzed 159 RAIR-TC cases for a total of 759 controls and found 7 independent risk factors for predicting RAIR-TC occurrence: age at diagnosis ≥ 55, vascular invasion, synchronous cervical, pulmonary and bone metastases at initial work-up, cervical and pulmonary recurrence during follow-up. The predictive score of RAIR-disease showed a high discrimination power with a cut-off value of 8.9 out of 10 providing 86% sensitivity and 92% specificity with an area under the curve (AUC) of 0.95. Conclusion Predicting the occurrence of RAIR-disease in DTC patients may allow clinicians to focus on systemic redifferentiating strategies and/or local treatments for metastatic lesions rather than pursuing with ineffective RAI-therapies.

Publisher

Springer Science and Business Media LLC

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