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Radiomics predicts risk of cachexia in advanced NSCLC patients treated with immune checkpoint inhibitors.

Authors :
Mu, Wei
Katsoulakis, Evangelia
Whelan, Christopher J.
Gage, Kenneth L.
Schabath, Matthew B.
Gillies, Robert J.
Source :
British Journal of Cancer. Jul2021, Vol. 125 Issue 2, p229-239. 11p.
Publication Year :
2021

Abstract

<bold>Background: </bold>Approximately 50% of cancer patients eventually develop a syndrome of prolonged weight loss (cachexia), which may contribute to primary resistance to immune checkpoint inhibitors (ICI). This study utilised radiomics analysis of 18F-FDG-PET/CT images to predict risk of cachexia that can be subsequently associated with clinical outcomes among advanced non-small cell lung cancer (NSCLC) patients treated with ICI.<bold>Methods: </bold>Baseline (pre-therapy) PET/CT images and clinical data were retrospectively curated from 210 ICI-treated NSCLC patients from two institutions. A radiomics signature was developed to predict the cachexia with PET/CT images, which was further used to predict durable clinical benefit (DCB), progression-free survival (PFS) and overall survival (OS) following ICI.<bold>Results: </bold>The radiomics signature predicted risk of cachexia with areas under receiver operating characteristics curves (AUCs) ≥ 0.74 in the training, test, and external test cohorts. Further, the radiomics signature could identify patients with DCB from ICI with AUCs≥0.66 in these three cohorts. PFS and OS were significantly shorter among patients with higher radiomics-based cachexia probability in all three cohorts, especially among those potentially immunotherapy sensitive patients with PD-L1-positive status (p < 0.05).<bold>Conclusions: </bold>PET/CT radiomics analysis has the potential to predict the probability of developing cachexia before the start of ICI, triggering aggressive monitoring to improve potential to achieve more clinical benefit. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00070920
Volume :
125
Issue :
2
Database :
Academic Search Index
Journal :
British Journal of Cancer
Publication Type :
Academic Journal
Accession number :
151489960
Full Text :
https://doi.org/10.1038/s41416-021-01375-0