James Newman, Isabel Preeshagul, Nina Kohn, Craig Devoe, Nagashree Seetharamu
{"title":"简单的参数解决一个复杂的问题:预测肺癌对检查点抑制剂治疗的反应。","authors":"James Newman, Isabel Preeshagul, Nina Kohn, Craig Devoe, Nagashree Seetharamu","doi":"10.2217/lmt-2020-0024","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Materials & methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/b2/ee/lmt-10-44.PMC8162145.pdf","citationCount":"3","resultStr":"{\"title\":\"Simple parameters to solve a complex issue: predicting response to checkpoint inhibitor therapy in lung cancer.\",\"authors\":\"James Newman, Isabel Preeshagul, Nina Kohn, Craig Devoe, Nagashree Seetharamu\",\"doi\":\"10.2217/lmt-2020-0024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Materials & methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":0,\"journal\":{\"name\":\"\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0,\"publicationDate\":\"2020-11-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/b2/ee/lmt-10-44.PMC8162145.pdf\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2217/lmt-2020-0024\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2217/lmt-2020-0024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simple parameters to solve a complex issue: predicting response to checkpoint inhibitor therapy in lung cancer.
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.
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