Novel, non-invasive imaging approach to identify patients with advanced non-small cell lung cancer at risk of hyperprogressive disease with immune checkpoint blockade

封锁 免疫检查点 医学 接收机工作特性 肺癌 疾病 免疫疗法 结核(地质) 肿瘤科 进行性疾病 癌症 放射科 内科学 受体 生物 古生物学
作者
Pranjal Vaidya,Kaustav Bera,Pradnya D. Patil,Amit Gupta,Prantesh Jain,Mehdi Alilou,Mohammadhadi Khorrami,Vamsidhar Velcheti,Anant Madabhushi
出处
期刊:Journal for ImmunoTherapy of Cancer [BMJ]
卷期号:8 (2): e001343-e001343 被引量:87
标识
DOI:10.1136/jitc-2020-001343
摘要

Hyperprogression is an atypical response pattern to immune checkpoint inhibition that has been described within non-small cell lung cancer (NSCLC). The paradoxical acceleration of tumor growth after immunotherapy has been associated with significantly shortened survival, and currently, there are no clinically validated biomarkers to identify patients at risk of hyperprogression.A total of 109 patients with advanced NSCLC who underwent monotherapy with Programmed cell death protein-1 (PD1)/Programmed death-ligand-1 (PD-L1) inhibitors were included in the study. Using RECIST measurements, we divided the patients into responders (n=50) (complete/partial response or stable disease) and non-responders (n=59) (progressive disease). Tumor growth kinetics were used to further identify hyperprogressors (HPs, n=19) among non-responders. Patients were randomized into a training set (D1=30) and a test set (D2=79) with the essential caveat that HPs were evenly distributed among the two sets. A total of 198 radiomic textural patterns from within and around the target nodules and features relating to tortuosity of the nodule associated vasculature were extracted from the pretreatment CT scans.The random forest classifier using the top features associated with hyperprogression was able to distinguish between HP and other radiographical response patterns with an area under receiver operating curve of 0.85±0.06 in the training set (D1=30) and 0.96 in the validation set (D2=79). These features included one peritumoral texture feature from 5 to 10 mm outside the tumor and two nodule vessel-related tortuosity features. Kaplan-Meier survival curves showed a clear stratification between classifier predicted HPs versus non-HPs for overall survival (D2: HR=2.66, 95% CI 1.27 to 5.55; p=0.009).Our study suggests that image-based radiomics markers extracted from baseline CTs of advanced NSCLC treated with PD-1/PD-L1 inhibitors may help identify patients at risk of hyperprogressions.
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