Open AccessA model‐based meta‐analysis of immune‐related adverse events during immune checkpoint inhibitors treatment for NSCLC
Author(s) -
Zhang Renwei,
Kong Daming,
Chen Rong,
Guo Yuchen,
Jian Weizhe,
Han Mengyi,
Zhou Tianyan
Publication year - 2022
Publication title -
cpt: pharmacometrics and systems pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.53
H-Index - 37
ISSN - 2163-8306
DOI - 10.1002/psp4.12834
Subject(s) - adverse effect , medicine , oncology , lung cancer , immune system , meta analysis , logistic regression , immunotherapy , cancer , immunology
Immune checkpoint inhibitors (ICIs) have become a vital part of the therapeutic landscape for non‐small cell lung cancer (NSCLC) in recent years benefiting from their remarkable efficacy. However, ICIs are associated with potentially life‐threatening immune‐related adverse events (irAEs). This study aims to quantify dose dependence and additional influencing factors of both any grade and grade greater than or equal to 3 irAEs in patients with NSCLC treated by ICIs. The trial‐level irAE data was collected and pooled from 129 cohorts in 81 clinical studies. A logit‐transformed meta‐regression model was applied to derive the quantitative relationship of irAE rate and ICI exposure. Programmed cell death‐1 (PD‐1) or programmed cell death ligand‐1 (PD‐L1) inhibitors showed no dose dependence in patients with NSCLC, whereas cytotoxic T lymphocyte–associated antigen 4 (CTLA‐4) inhibitors exhibited a statistically significant dose dependence when used alone or combined with PD‐1 or PD‐L1 inhibitors. Besides, therapy line and combination of ICIs with chemotherapy or target therapy were significant covariates. Hopefully, the results of this study can improve clinicians’ awareness of irAEs and be helpful for clinical decisions during ICI treatment for NSCLC.