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Assessment of Treatment Response to Lenvatinib in Thyroid Cancer Monitored by F-18 FDG PET/CT Using PERCIST 1.0, Modified PERCIST and EORTC Criteria-Which One Is Most Suitable?
Background: We aimed to compare the established metabolic response criteria PERCIST and EORTC for their applicability and predictive value in terms of clinical response assessment early after the initiation of lenvatinib therapy in patients with metastatic radioiodine-refractory (RAI) thyroid cancer...
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Published in: | Cancers 2022-04, Vol.14 (8), p.1868 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Background: We aimed to compare the established metabolic response criteria PERCIST and EORTC for their applicability and predictive value in terms of clinical response assessment early after the initiation of lenvatinib therapy in patients with metastatic radioiodine-refractory (RAI) thyroid cancer (TC). Methods: In 25 patients treated with lenvatinib, baseline and 4-month follow-up F-18 FDG PET/CT images were analyzed using PERCIST 1.0, modified PERCIST (using SUVpeak or SUVmax) and EORTC criteria. Two groups were defined: disease control (DC) and progressive disease (PD), which were correlated with PFS and OS. Results: PERCIST, mPERCIST, PERCISTmax and EORTC could be applied in 80%, 80%, 88% and 100% of the patients based on the requirements of lesion assessment criteria, respectively. With PERCIST, mPERCIST, PERCISTmax and EORTC, the patients classified as DC and PD ranged from 65 to 68% and from 32 to 35%, respectively. Patients with DC exhibited a longer median PFS than patients with PD for EORTC (p < 0.014) and for PERCIST and mPERCIST (p = 0.037), respectively. Conclusion: EORTC and the different PERCIST criteria performed equally regarding the identification of patients with PD requiring treatment changes. However, the applicability of PERCIST 1.0 using SULpeak seems restricted due to the significant proportion of small tumor lesions. |
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ISSN: | 2072-6694 2072-6694 |
DOI: | 10.3390/cancers14081868 |