Cargando…
Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis
BACKGROUND: Immune checkpoint inhibitors (ICIs) have emerged as a promising treatment option for advanced non-small-cell lung cancer (NSCLC) patients, highlighting the need for biomarkers to identify responders and predict the outcome of ICIs. The purpose of this study was to evaluate the predictive...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9487526/ https://www.ncbi.nlm.nih.gov/pubmed/36147904 http://dx.doi.org/10.3389/fonc.2022.951557 |
_version_ | 1784792476953870336 |
---|---|
author | Zhu, Ke Su, Danqian Wang, Jianing Cheng, Zhouen Chin, Yiqiao Chen, Luyin Chan, Chingtin Zhang, Rongcai Gao, Tianyu Ben, Xiaosong Jing, Chunxia |
author_facet | Zhu, Ke Su, Danqian Wang, Jianing Cheng, Zhouen Chin, Yiqiao Chen, Luyin Chan, Chingtin Zhang, Rongcai Gao, Tianyu Ben, Xiaosong Jing, Chunxia |
author_sort | Zhu, Ke |
collection | PubMed |
description | BACKGROUND: Immune checkpoint inhibitors (ICIs) have emerged as a promising treatment option for advanced non-small-cell lung cancer (NSCLC) patients, highlighting the need for biomarkers to identify responders and predict the outcome of ICIs. The purpose of this study was to evaluate the predictive value of baseline standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) derived from 18F-FDG-PET/CT in advanced NSCLC patients receiving ICIs. METHODS: PubMed and Web of Science databases were searched from January 1st, 2011 to July 18th, 2022, utilizing the search terms “non-small-cell lung cancer”, “PET/CT”, “standardized uptake value”, “metabolic tumor volume”, “ total lesion glycolysis”, and “immune checkpoint inhibitors”. Studies that analyzed the association between PET/CT parameters and objective response, immune-related adverse events (irAEs) and prognosis of NSCLC patients treated with ICIs were included. We extracted the hazard ratio (HR) with a 95% confidence interval (CI) for progression-free survival (PFS) and overall survival (OS). We performed a meta-analysis of HR using Review Manager v.5.4.1. RESULTS: Sixteen studies were included for review and thirteen for meta-analysis covering 770 patients. As for objective response and irAEs after ICIs, more studies with consistent assessment methods are needed to determine their relationship with MTV. In the meta-analysis, low SUVmax corresponded to poor PFS with a pooled HR of 0.74 (95% CI, 0.57-0.96, P=0.02). And a high level of baseline MTV level was related to shorter PFS (HR=1.45, 95% CI, 1.11-1.89, P<0.01) and OS (HR, 2.72; 95% CI, 1.97-3.73, P<0.01) especially when the cut-off value was set between 50-100 cm(3). SUVmean and TLG were not associated with the prognosis of NSCLC patients receiving ICIs. CONCLUSIONS: High level of baseline MTV corresponded to shorter PFS and OS, especially when the cut-off value was set between 50-100 cm(3). MTV is a potential predictive value for the outcome of ICIs in NSCLC patients. |
format | Online Article Text |
id | pubmed-9487526 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94875262022-09-21 Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis Zhu, Ke Su, Danqian Wang, Jianing Cheng, Zhouen Chin, Yiqiao Chen, Luyin Chan, Chingtin Zhang, Rongcai Gao, Tianyu Ben, Xiaosong Jing, Chunxia Front Oncol Oncology BACKGROUND: Immune checkpoint inhibitors (ICIs) have emerged as a promising treatment option for advanced non-small-cell lung cancer (NSCLC) patients, highlighting the need for biomarkers to identify responders and predict the outcome of ICIs. The purpose of this study was to evaluate the predictive value of baseline standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) derived from 18F-FDG-PET/CT in advanced NSCLC patients receiving ICIs. METHODS: PubMed and Web of Science databases were searched from January 1st, 2011 to July 18th, 2022, utilizing the search terms “non-small-cell lung cancer”, “PET/CT”, “standardized uptake value”, “metabolic tumor volume”, “ total lesion glycolysis”, and “immune checkpoint inhibitors”. Studies that analyzed the association between PET/CT parameters and objective response, immune-related adverse events (irAEs) and prognosis of NSCLC patients treated with ICIs were included. We extracted the hazard ratio (HR) with a 95% confidence interval (CI) for progression-free survival (PFS) and overall survival (OS). We performed a meta-analysis of HR using Review Manager v.5.4.1. RESULTS: Sixteen studies were included for review and thirteen for meta-analysis covering 770 patients. As for objective response and irAEs after ICIs, more studies with consistent assessment methods are needed to determine their relationship with MTV. In the meta-analysis, low SUVmax corresponded to poor PFS with a pooled HR of 0.74 (95% CI, 0.57-0.96, P=0.02). And a high level of baseline MTV level was related to shorter PFS (HR=1.45, 95% CI, 1.11-1.89, P<0.01) and OS (HR, 2.72; 95% CI, 1.97-3.73, P<0.01) especially when the cut-off value was set between 50-100 cm(3). SUVmean and TLG were not associated with the prognosis of NSCLC patients receiving ICIs. CONCLUSIONS: High level of baseline MTV corresponded to shorter PFS and OS, especially when the cut-off value was set between 50-100 cm(3). MTV is a potential predictive value for the outcome of ICIs in NSCLC patients. Frontiers Media S.A. 2022-09-06 /pmc/articles/PMC9487526/ /pubmed/36147904 http://dx.doi.org/10.3389/fonc.2022.951557 Text en Copyright © 2022 Zhu, Su, Wang, Cheng, Chin, Chen, Chan, Zhang, Gao, Ben and Jing https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Zhu, Ke Su, Danqian Wang, Jianing Cheng, Zhouen Chin, Yiqiao Chen, Luyin Chan, Chingtin Zhang, Rongcai Gao, Tianyu Ben, Xiaosong Jing, Chunxia Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis |
title | Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis |
title_full | Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis |
title_fullStr | Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis |
title_full_unstemmed | Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis |
title_short | Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis |
title_sort | predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: a meta-analysis |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9487526/ https://www.ncbi.nlm.nih.gov/pubmed/36147904 http://dx.doi.org/10.3389/fonc.2022.951557 |
work_keys_str_mv | AT zhuke predictivevalueofbaselinemetabolictumorvolumefornonsmallcelllungcancerpatientstreatedwithimmunecheckpointinhibitorsametaanalysis AT sudanqian predictivevalueofbaselinemetabolictumorvolumefornonsmallcelllungcancerpatientstreatedwithimmunecheckpointinhibitorsametaanalysis AT wangjianing predictivevalueofbaselinemetabolictumorvolumefornonsmallcelllungcancerpatientstreatedwithimmunecheckpointinhibitorsametaanalysis AT chengzhouen predictivevalueofbaselinemetabolictumorvolumefornonsmallcelllungcancerpatientstreatedwithimmunecheckpointinhibitorsametaanalysis AT chinyiqiao predictivevalueofbaselinemetabolictumorvolumefornonsmallcelllungcancerpatientstreatedwithimmunecheckpointinhibitorsametaanalysis AT chenluyin predictivevalueofbaselinemetabolictumorvolumefornonsmallcelllungcancerpatientstreatedwithimmunecheckpointinhibitorsametaanalysis AT chanchingtin predictivevalueofbaselinemetabolictumorvolumefornonsmallcelllungcancerpatientstreatedwithimmunecheckpointinhibitorsametaanalysis AT zhangrongcai predictivevalueofbaselinemetabolictumorvolumefornonsmallcelllungcancerpatientstreatedwithimmunecheckpointinhibitorsametaanalysis AT gaotianyu predictivevalueofbaselinemetabolictumorvolumefornonsmallcelllungcancerpatientstreatedwithimmunecheckpointinhibitorsametaanalysis AT benxiaosong predictivevalueofbaselinemetabolictumorvolumefornonsmallcelllungcancerpatientstreatedwithimmunecheckpointinhibitorsametaanalysis AT jingchunxia predictivevalueofbaselinemetabolictumorvolumefornonsmallcelllungcancerpatientstreatedwithimmunecheckpointinhibitorsametaanalysis |