期刊
BRITISH JOURNAL OF CANCER
卷 125, 期 2, 页码 229-239出版社
SPRINGERNATURE
DOI: 10.1038/s41416-021-01375-0
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资金
- U.S. Public Health Service research grant [U01 CA143062, R01 CA190105]
The study used radiomics analysis of PET/CT images to predict cachexia risk in NSCLC patients treated with ICI, and found that the radiomics signature could also help predict durable clinical benefit, progression-free survival, and overall survival following ICI treatment.
Background 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 F-18-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. Methods 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. Results 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). Conclusions 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.
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