Open AccessSimple parameters to solve a complex issue: predicting response to checkpoint inhibitor therapy in lung cancer
Author(s) -
James Newman,
Isabel R. Preeshagul,
Nina Kohn,
Craig Devoe,
Nagashree Seetharamu
Publication year - 2021
Publication title -
lung cancer management
Language(s) - English
Resource type - Journals
eISSN - 1758-1974
pISSN - 1758-1966
DOI - 10.2217/lmt-2020-0024
Subject(s) - medicine , oncology , lung cancer , retrospective cohort study , predictive value , response evaluation criteria in solid tumors , cancer , biomarker , disease , progressive disease , biochemistry , chemistry
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 & 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.