Anatomical-biochemical discordance and prognostic role of bone metastases in advanced MTC treated with [¹⁷⁷Lu]Lu-DOTA-TATE.

Medullary thyroid carcinoma (MTC) is a rare malignancy with limited treatment options in the metastatic setting. While peptide receptor radionuclide therapy (PRRT) with [¹⁷⁷Lu]Lu-DOTA-TATE has been well established in gastroenteropancreatic neuroendocrine tumors, its clinical utility in MTC remains under investigation.

We retrospectively analyzed 18 patients with advanced, somatostatin receptor-positive MTC treated with [¹⁷⁷Lu]Lu-DOTA-TATE. Treatment decisions-including in patients with low somatostatin receptor (SSTR) expression or first-line PRRT indication-were made by a multidisciplinary tumor board. Anatomical response was assessed using RECIST 1.1 on [⁶⁸Ga]Ga-DOTA-TATE PET/CT after two cycles. Biochemical and clinical outcomes were also recorded. Progression-free survival (PFS) was evaluated using Kaplan-Meier and Cox regression.

Median PFS was 37.0 months. Radiologic disease control -defined as partial response (PR) or stable disease (SD) -was achieved in 78%, and biochemical response (≥ 50% decrease in calcitonin) in 44% of patients. Patients with bone metastases had significantly shorter PFS (24.6 vs. 47.0 months, p = 0.027). Longer PFS was also observed in those receiving higher cumulative dose, those with larger solitary tumors, and those treated in the first-line setting, although these trends did not reach statistical significance. Discordance between anatomical and biochemical response was observed in 50% of cases, highlighting limitations of calcitonin-based monitoring.

PRRT with [¹⁷⁷Lu]Lu-DOTA-TATE is a well-tolerated treatment option for selected patients with advanced MTC, including those receiving first-line therapy and those with low SSTR expression. In our limited cohort, bone metastases were associated with shorter PFS, and discordant imaging/biochemical responses are common. Functional imaging-guided selection and individualized response assessment are essential for optimal management.
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Bilgic Bilgic, Nazari Nazari, Sağer Sağer, Sonmezoglu Sonmezoglu
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