AUTHOR=Li Yanlin , Jia Xiaohui , Du Yonghao , Mao Ziyang , Zhang Yajuan , Shen Yuan , Sun Hong , Liu Mengjie , Niu Gang , Wang Jun , Hu Jie , Jiao Min , Guo Hui 

TITLE=Eosinophil as a biomarker for diagnosis, prediction, and prognosis evaluation of severe checkpoint inhibitor pneumonitis

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.827199

DOI=10.3389/fonc.2022.827199

ISSN=2234-943X

ABSTRACT=Introduction: Checkpoint inhibitor pneumonitis (CIP) is a common serious adverse event caused by immune checkpoint inhibitors (ICIs) and severe CIP can be life-threatening. We aimed to investigate the role of peripheral blood cells in diagnosis, prediction and prognosis evaluation for all and severe CIP. 
Materials and Methods: Patients with lung cancer receiving ICIs were enrolled in this retrospective study. Baseline was defined as the time of ICIs initiation, endpoint was defined as the time of clinical diagnosis of CIP or the last ICIs treatment and follow-up point was defined as 1 week after CIP. Eosinophil percentages at baseline, endpoint and follow-up point were shortened to “Ebas”, “Eend and “Efol” respectively.
Results: Among 430 patients included, incidence of CIP was 15.6% and severe CIP was 3.7%. Eend/Ebas value was lower in patients with CIP (p = 0.001), especially severe CIP (p = 0.036). Receiver operating characteristics curves revealed that Eend/Ebas could serve as a biomarker to diagnose CIP (p = 0.004) and severe CIP (p < 0.001). For severe CIP, eosinophil percentage declined before symptoms appeared and CT diagnosed. Eosinophil percentage significantly elevated at the follow-up point in recovery group but not in non-recovery group. CIP patients with Efol/Ebas ≥ 1.0 had significant prolonged overall survival (OS) (p = 0.024) and after-CIP survival (AS) (p = 0.043). The same results were found in severe CIP but without statistical difference. 
Conclusions: Eosinophil percentage could be an effective biomarker in diagnosis, prediction and prognosis evaluation for CIP and severe CIP.