Radiomic markers associated with clinical benefit in patients with radiographic progression of advanced uveal melanoma on tebentafusp.

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Tác giả: Shaad E Abedin, Volkan Beylergil, Richard Carvajal, Stephane Champiat, Laura Collins, Laurent Dercle, Thomas Eche, Lawrence H Schwartz, Binsheng Zhao

Ngôn ngữ: eng

Ký hiệu phân loại: 150.194 Reductionism

Thông tin xuất bản: England : European journal of cancer (Oxford, England : 1990) , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 742961

STUDY AIM: Tebentafusp, a bispecific fusion protein consisting of affinity-enhanced T cell receptor fused to anti-CD3 effector, has shown overall survival (OS) benefits across all RECIST response categories, including progressive disease (PD). In a phase 2 trial (NCT02570308) for advanced uveal melanoma (mUM), 35 % of PD patients experienced ≥ 0.5 log ctDNA reduction, resulting in a median overall survival (OS) of ∼17 months, compared to ∼8 months in the non-ctDNA reduction group. METHODS: A total of 34 of 127 2L+ mUM patients with PD were split into two groups based on absence or presence of ctDNA reduction (≥0.5 log reduction). Lesions from CT and MRI scans were analyzed using radiomics features at baseline and week eight, yielding two machine-learning-derived patient signatures (16 features). Performance of per-patient analysis (n = 32) and per-lesion analysis (n = 148) was assessed using ROC AUC (95 % confidence interval [CI]). RESULTS: In the per-patient analysis, a volumetric signature classified patients into groups with ROC AUC of 0.71 [0.53-0.90] with 63 % specificity and 81 % sensitivity at the optimal threshold (0.57). In the per-lesion analysis, a radiomic signature reached an ROC AUC of 0.70 [0.58-0.81] with 66 % specificity and 74 % sensitivity at the optimal threshold (0.53). Group B had lower baseline tumor lesion volume (ROC AUC=0.65), distinct baseline (ROC AUC=0.66), and change by week eight (ROC AUC=0.66/0.69 on CT/MRI) in tumor heterogeneity. CONCLUSION: Radiomic analysis accurately predicted ctDNA reduction in PD patients at both the patient and lesion level. The most influential predictor was decreased tumor heterogeneity observed on CT/MRI.
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