ArticleBJC reports2023
Radiomics and outcome prediction to antiangiogenic treatment in advanced gastroenteropancreatic neuroendocrine tumours: findings from the phase II TALENT trial.
Article in BJC reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02678780 (Trial to Assess the Efficacy of Lenvatinib in Metastatic Neuroendocrine Tumors.), which is not on this map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Trial to Assess the Efficacy of Lenvatinib in Metastatic Neuroendocrine Tumors. (TALENT STUDY)
Who cites it
1 citing paper in PubMed.
- Radiomic analysis of patient and interorgan heterogeneity in response to immunotherapies and BRAF-targeted therapy in metastatic melanoma.Journal for immunotherapy of cancer · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
22 authors.
Funding
Abstract
backgroundMore accurate predictive biomarkers in patients with gastroenteropancreatic neuroendocrine tumours (GEP-NETs) are needed. This study aims to investigate radiomics-based tumour phenotypes as a surrogate biomarker of the tumour vasculature and response prediction to antiangiogenic targeted agents in patients with GEP-NETs.
methodsIn this retrospective study, a radiomics signature was developed in patients with GEP-NETs and liver metastases receiving lenvatinib. Patients were selected from the multicentre phase II TALENT trial (NCT02678780) (development cohort). Radiomics variables were extracted from liver metastases in the pre-treatment CT-scans and selected using LASSO regression and minimum redundancy maximum relevance (mRMR). Logistic regression and Cox proportional-hazards models for radiomics and combined radiomics with clinical data were explored. The performance of the models was tested in an external cohort of patients treated with sunitinib (test cohort). Associations between the radiomics score and vascularisation factors in plasma were studied using hierarchical clustering and Mann-Whitney U test.
resultsA total of 89 patients were included in the study, 408 liver metastases were analysed. The CT-based radiomics signature was associated with clinical benefit in the development (training and validation sets) and test cohorts (AUC 0.75 [0.66-0.90], 0.67 [0.49-0.92] and 0.67 [0.43-0.91], respectively). The combined radiomics-clinical signature (including the radiomics score, Ki-67 index and primary tumour site) improved on radiomics-only signature performance (AUC 0.79 [95% CI 0.64-0.93]; p < 0.001). A higher radiomics score indicated longer progression-free survival (hazard ration of 0.11 [0.03-0.45]; p = 0.002) and was associated with vascularisation factors (p = 0.01).
conclusionsRadiomics-based phenotypes can provide valuable information about tumour characteristics, including the vasculature, that are associated with response to antiangiogenics. CLINICAL
trial registrationThis is a study of the Lenvatinib Efficacy in Metastatic Neuroendocrine Tumours (TALENT) phase II clinical trial (NCT02678780).
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