Simple parameters to solve a complex issue: Predicting response to checkpoint inhibitor therapy in lung cancer Journal Article


Authors: Newman, J.; Preeshagul, I.; Kohn, N.; Devoe, C.; Seetharamu, N.
Article Title: Simple parameters to solve a complex issue: Predicting response to checkpoint inhibitor therapy in lung cancer
Abstract: Background: Noninvasive biomarkers predicting immune checkpoint inhibitor (ICI) response are urgently needed. We evaluated the predictive value of pretreatment neutrophil-to-lymphocyte ratio (NLR), smoking history, smoking intensity, BMI and programmed death ligand 1 (PD-L1) expression in non-small-cell lung cancer (NSCLC) patients treated with ICIs. Materials and methods: Single-center retrospective study included 137 patients from July 2015 to February 2018. Outcomes included 3-month disease control rate, progression-free survival, and overall survival. Predictive value of biomarkers was assessed independently and in a multivariable model. Results: NLR was associated with all outcomes. Smoking history was predictive of progression-free survival and smoking intensity was predictive of disease control rate. BMI and PD-L1 were not associated with any outcome. High BMI was associated with low NLR. Conclusion: Simple clinical biomarkers can predict response to ICIs. A score incorporating both clinical factors and established tissue/serum biomarkers may be useful in identifying NSCLC patients who would benefit from ICIs. © 2020 James Newman and Nagashree Seetharamu. © 2021 Future Medicine Ltd.. All rights reserved.
Keywords: smoking; nsclc; pd-l1; bmi; nlr; nlr and bmi
Journal Title: Lung Cancer Management
Volume: 10
Issue: 2
ISSN: 1758-1966
Publisher: Future Medicine  
Date Published: 2021-06-01
Start Page: LMT44
Language: English
DOI: 10.2217/lmt-2020-0024
PROVIDER: scopus
PMCID: PMC8162145
PUBMED: 34084210
DOI/URL:
Notes: Article -- Export Date: 1 July 2021 -- Source: Scopus
Altmetric
Citation Impact
BMJ Impact Analytics
MSK Authors