The prognosis of poorly differentiated thyroid carcinomas (PDTC) defined by the Turin criteria is variable. The aim of this study on 51 PDTC patients was to determine clinical, histological and molecular prognostic factors associated with recurrence in patients with localized disease at initial treatment and with overall survival in patients with distant metastases. Of 40 patients for whom next-generation sequencing (NGS) by ThyroSeq v3 was able to be performed on historical samples, we identified high-risk molecular signature (TERT, TP53 mutations) in 24 (60%) cases, intermediate risk signature in 9 (22.5%) cases and low-risk signature in 7 (17.5%) cases. Potentially actionable mutations were identified in 10% of cases. After a median follow-up of 57.5 months, recurrence occurred in 11 (39%) of the 28 patients with localized disease. The American Thyroid Association (ATA) high risk of relapse, high mitotic count, high molecular risk signature and CD163 expression were associated with recurrence (P = 0.009, 0.01, 0.049, 0.03 respectively). After a median follow-up of 49.5 months, thyroid cancer-related death occurred in 53% of the patients with distant metastases. There was no significant prognostic factor associated with death in univariate analysis. However, none of the patients with intermediate ATA risk of recurrence and none of the patients with low-risk molecular signature died from the disease. In addition, high molecular-risk signature was associated with the presence of synchronous or metachronous distant metastasis (P = 0.007) and with poor overall survival (P = 0.01). In conclusion, ATA risk of relapse and high mitotic count was associated with higher rate of recurrence in localized PDTC. High molecular-risk signature was associated with the presence of distant metastasis and poor overall survival. Further studies are needed to determine if molecular testing adds to ATA risk stratification or response to therapy in predicting outcomes.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1530/ERC-22-0151 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!