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      Radiomics predicts survival of patients with advanced non‑small cell lung cancer undergoing PD‑1 blockade using Nivolumab

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          Abstract

          Immune checkpoint blockade is an emerging anticancer strategy, and Nivolumab is a human mAb to PD-1 that is used in the treatment of a number of different malignancies, including non-small cell lung cancer (NSCLC), kidney cancer, urothelial carcinoma and melanoma. Although the use of Nivolumab prolongs survival in a number of patients, this treatment is hampered by high cost. Therefore, the identification of predictive markers of response to treatment in patients is required. In this context, PD-1/PDL1 blockade antitumor effects occur through the reactivation of a pre-existing immune response, and the efficacy of these effects is strictly associated with the presence of necrosis, hypoxia and inflammation at the tumour sites. It has been indicated that these events can be evaluated by specific assessments using a computed tomography (CT) texture analysis (TA) or radiomics. Therefore, a retrospective study was performed, which aimed to evaluate the potential use of this analysis in the identification of patients with NSCLC who may benefit from Nivolumab treatment. A retrospective analysis was performed of 59 patients with metastatic NSCLC who received Nivolumab treatment between January 2015 and July 2017 at Siena University Hospital (35 patients, training dataset), Catanzaro University Hospital and Reggio Calabria Grand Metropolitan Hospital, Italy (24 patients, validation dataset). Pre- and post-contrast CT sequences were used to contour the gross tumour volume (GTV) of the target lesions prior to Nivolumab treatment. The impact of variations on contouring was analysed using two delineations, which were performed on each patient, and the TA parameters were tested for reliability using the Intraclass Coefficient Correlation method (ICC). All analyses for the current study were performed using LifeX Software©. Imaging, clinical and pathological parameters were correlated with progression free survival and overall survival (OS) using Kaplan Meier analysis. An external validation testing was performed for the TA Score using the validation dataset. A total of 59 patients were included in the analysis of the present study. The reliability ICC analysis of 14 TA parameters indicated a highly reproducibility (ICC >0.70, single measure) in 12 (85%) pre- contrast and 13 (93%) post-contrast exams. A specific cut-off was detected for each of the following parameters: volume (score 1 >36 ml), histogram entropy (score 1 > 1.30), compacity (score 1 <3), gray level co-occurrence matrix (GLCM)-entropy (score 1 >1.80), GLCM-Dissimilarity (score 1 >5) and GLCM-Correlation (score 1<0.54). The global texture score allowed the classification of two subgroups of Low (Score 0-1; 36 patients; 61%) and High Risk patients (Score >1; 23 patients; 39%) that respectively, showed a median OS of 26 (mean +/- SD: 18 +/- 1.98 months; 95% CI 14-21 months) and 5 months (mean +/- SD: 6 +/- 0.99 months; 95% CI: 4-8 months; P=0.002). The current study indicated that TA parameters can identify patients that will benefit from PD-1 blockage by defining the radiological settings that are potentially suggestive of an active immune response. These results require further confirmation in prospective trials.

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          Author and article information

          Journal
          Oncology Letters
          Oncol Lett
          Spandidos Publications
          1792-1074
          1792-1082
          December 16 2019
          December 16 2019
          Affiliations
          [1 ]Unit of Radiation Oncology, Integrated Department of Diagnostic Radiology and Radiotherapy, Ospedale del Mare, I‑80147 Naples, Italy
          [2 ]Unit of Radiation Oncology, Oncology Department, University Hospital of Siena, I‑53100 Siena, Italy
          [3 ]Integrated Area of Medical Oncology, AOU Mater Domini and Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, I‑88100 Catanzaro, Italy
          [4 ]Department of Precision Medicine, University of Campania ‘L. Vanvitelli’, I‑80138 Naples, Italy
          [5 ]Unit of Medical Imaging, Emergency Department and Diagnostic Services, University Hospital of Siena, I‑53100 Siena, Italy
          [6 ]Unit of Medical Oncology, Oncology Department, Grand Metropolitan Hospital ‘Bianchi Melacrino Morelli’ Reggio Calabria I‑89124, Italy
          [7 ]Unit of Radiology, Department of Diagnostic Services, Grand Metropolitan Hospital ‘Bianchi Melacrino Morelli’ Reggio Calabria I‑89124, Italy
          [8 ]Epidemiology Unit, IRCCS Istituto Nazionale Tumori ‘Fondazione G. Pascale’, I‑80131 Naples, Italy
          Article
          10.3892/ol.2019.11220
          6956423
          31966081
          3677b979-2040-49c2-aee4-6c875be2c404
          © 2019
          History

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