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Introduction: Tumor growth rate (TGR), percentage of change in tumor volume/month, has been previously identified as an early radiological biomarker for treatment monitoring in neuroendocrine tumor (NET) patients. We assessed the performance and reproducibility of TGR at 3 months (TGR3m) as a predictor factor of progression-free survival (PFS), including the impact of imaging method and reader variability.
Methods: Baseline and 3-month (±1 month) CT/MRI images from patients with advanced, grade 1-2 NETs were retrospectively reviewed by 2 readers. Influence of number of targets, tumor burden, and location of lesion on the performance of TGR3m to predict PFS was assessed by uni/multivariable Cox regression analysis. Agreement between readers was assessed by Lin's concordance coefficient (LCC) and kappa coefficient (KC).
Results: A total of 790 lesions were measured in 222 patients. Median PFS was 22.9 months. On univariable analysis, number of lesions (≥4), tumor burden, and presence of liver metastases were significantly correlated with PFS. On multivariate analysis, ≥4 lesions (HR: 1.89 [95% CI: 1.01-3.57]), TGR3m ≥0.8%/month (HR: 4.01 [95% CI: 2.31-6.97]), and watch and wait correlated with shorter PFS. No correlation was found between TGR3m and number of lesions (rho: -0.2; p value: 0.1930). No difference in mean TGR3m across organs was shown (p value: 0.6). Concordance between readers was acceptable (LCC: 0.52 [95% CI: 0.38-0.65]; KC: 0.57, agreement: 81.55%). TGR3m remained a significant prognostic factor when data from the second reader were employed (HR: 4.35 [95% CI: 2.44-7.79]; p value <0.001) regardless his expertise (HR: 1.21 [95% CI: 0.70-2.09]; p value: 0.493).
Discussion/conclusion: TGR3m is a robust and early radiological biomarker able to predict PFS. It may be used to identify patients with advanced NETs who require closer radiological follow-up.
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http://dx.doi.org/10.1159/000510445 | DOI Listing |
JMIR Res Protoc
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Department of Medical Oncology, Early Phase Unit, Georges-François Leclerc Centre, Dijon, France.
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Biobank of Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, Jiangsu, PR China.
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Department of Chemical and Biological Engineering, Department of Chemistry, Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction, State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science & Technology, Hong Kong, 999077,
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State Key Laboratory of Molecular Oncology, National Cancer Center/National, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
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