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Updated: May 3, 2026

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer
Published on: June 9, 2023
Efficacy of Lenvatinib Therapy for Thyroid Cancer by Pathological Type: A Retrospective Real-world Study
Mioko Matsuo1, Mamoru Ito2, Kenji Tsuchihashi2
1Department of Otorhinolaryngology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan; matsuo.mioko.202@m.kyushu-u.ac.jp.
Background/Aim:
Refractory differentiated thyroid carcinoma (DTC) and anaplastic thyroid carcinoma (ATC) are associated with poor prognoses. Molecularly targeted agents such as lenvatinib are expected to significantly improve outcomes. However, data from real-world settings remain limited.
Patients And Methods:
A retrospective analysis was conducted in 48 patients with thyroid carcinoma treated with lenvatinib at Kyushu University Hospital between April 2015 and October 2024. We compared overall survival (from time of treatment initiation to death, censoring, or data cutoff) and progression-free survival (from time of treatment initiation to tumor progression as confirmed by image examination) using Kaplan-Meier analysis. A subgroup analysis was also conducted for patients who had and had not received prior radioactive iodine (RAI) therapy.
Results:
The analysis included 29 female and 19 male cases. The histologic types were papillary thyroid carcinoma in 26 patients, follicular thyroid carcinoma in seven patients, and ATC in 15 patients. Of 33 DTC cases, RAI was not administered in nine cases. The median progression-free survival was 30 months for papillary thyroid carcinoma, 18 months for follicular thyroid carcinoma, and four months for ATC. The median progression-free survival for patients with DTC who received RAI therapy was 19 months, whereas that for patients with DTC without RAI therapy was 46 months. No significant difference was found between the two groups (p=0.243).
Conclusion:
Lenvatinib may be effective in patients with DTC in whom RAI treatment is not feasible in real-world settings.
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