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放射组学预测免疫检查点抑制剂治疗晚期 NSCLC 患者恶病质风险。

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

机构信息

Department of Cancer Physiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.

James A. Haley Veterans' Hospital, Tampa, FL, USA.

出版信息

Br J Cancer. 2021 Jul;125(2):229-239. doi: 10.1038/s41416-021-01375-0. Epub 2021 Apr 7.

Abstract

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-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.

摘要

背景

约 50%的癌症患者最终会出现持续性体重减轻(恶病质)综合征,这可能导致对免疫检查点抑制剂(ICI)的原发性耐药。本研究利用 F-FDG-PET/CT 图像的放射组学分析来预测恶病质风险,随后可将其与接受 ICI 治疗的晚期非小细胞肺癌(NSCLC)患者的临床结局相关联。

方法

从两个机构的 210 名接受 ICI 治疗的 NSCLC 患者中回顾性收集基线(治疗前)PET/CT 图像和临床数据。开发了一种放射组学特征来预测 PET/CT 图像中的恶病质风险,该特征进一步用于预测 ICI 后持久临床获益(DCB)、无进展生存期(PFS)和总生存期(OS)。

结果

放射组学特征在训练、测试和外部测试队列中预测恶病质风险的受试者工作特征曲线下面积(AUCs)≥0.74。此外,该放射组学特征可在这三个队列中识别出具有 ICI 持久临床获益的患者,AUCs≥0.66。在所有三个队列中,恶病质风险较高的患者的 PFS 和 OS 明显更短,尤其是 PD-L1 阳性状态的潜在免疫治疗敏感患者(p<0.05)。

结论

PET/CT 放射组学分析有可能在开始 ICI 之前预测恶病质的发生概率,从而引发积极监测,以提高获得更多临床获益的潜力。

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