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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">MCO</journal-id>
<journal-title-group>
<journal-title>Molecular and Clinical Oncology</journal-title>
</journal-title-group>
<issn pub-type="ppub">2049-9450</issn>
<issn pub-type="epub">2049-9469</issn>
<publisher>
<publisher-name>D.A. Spandidos</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">MCO-20-4-02730</article-id>
<article-id pub-id-type="doi">10.3892/mco.2024.2730</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Articles</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Clinical predictors of response to single‑agent immune checkpoint inhibitors in chemotherapy‑pretreated non‑small cell lung cancer</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name><surname>Musaelyan</surname><given-names>Aram A.</given-names></name>
<xref rid="af1-MCO-20-4-02730" ref-type="aff">1</xref>
<xref rid="af2-MCO-20-4-02730" ref-type="aff">2</xref>
<xref rid="c1-MCO-20-4-02730" ref-type="corresp"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Moiseyenko</surname><given-names>Fedor V.</given-names></name>
<xref rid="af3-MCO-20-4-02730" ref-type="aff">3</xref>
<xref rid="af4-MCO-20-4-02730" ref-type="aff">4</xref>
<xref rid="af5-MCO-20-4-02730" ref-type="aff">5</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Emileva</surname><given-names>Tancholpon E.</given-names></name>
<xref rid="af1-MCO-20-4-02730" ref-type="aff">1</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Oganesyan</surname><given-names>Ani P.</given-names></name>
<xref rid="af3-MCO-20-4-02730" ref-type="aff">3</xref>
<xref rid="af4-MCO-20-4-02730" ref-type="aff">4</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Oganyan</surname><given-names>Karina A.</given-names></name>
<xref rid="af1-MCO-20-4-02730" ref-type="aff">1</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Urtenova</surname><given-names>Magaripa A.</given-names></name>
<xref rid="af1-MCO-20-4-02730" ref-type="aff">1</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Odintsova</surname><given-names>Svetlana V.</given-names></name>
<xref rid="af1-MCO-20-4-02730" ref-type="aff">1</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Chistyakov</surname><given-names>Ivan V.</given-names></name>
<xref rid="af1-MCO-20-4-02730" ref-type="aff">1</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Degtyarev</surname><given-names>Alexey M.</given-names></name>
<xref rid="af6-MCO-20-4-02730" ref-type="aff">6</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Akopov</surname><given-names>Andrey L.</given-names></name>
<xref rid="af1-MCO-20-4-02730" ref-type="aff">1</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Imyanitov</surname><given-names>Evgeny N.</given-names></name>
<xref rid="af2-MCO-20-4-02730" ref-type="aff">2</xref>
<xref rid="af3-MCO-20-4-02730" ref-type="aff">3</xref>
<xref rid="af4-MCO-20-4-02730" ref-type="aff">4</xref>
<xref rid="af7-MCO-20-4-02730" ref-type="aff">7</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Orlov</surname><given-names>Sergey V.</given-names></name>
<xref rid="af1-MCO-20-4-02730" ref-type="aff">1</xref>
<xref rid="af2-MCO-20-4-02730" ref-type="aff">2</xref>
</contrib>
</contrib-group>
<aff id="af1-MCO-20-4-02730"><label>1</label>Department of Clinical Oncology, Pavlov First Saint Petersburg State Medical University, Saint Petersburg 197022, Russia</aff>
<aff id="af2-MCO-20-4-02730"><label>2</label>Research Institute of Medical Primatology, Sochi 354376, Russia</aff>
<aff id="af3-MCO-20-4-02730"><label>3</label>N.P. Napalkov City Cancer Center, Ministry of Public Health of The Russian Federation, Saint Petersburg 197758, Russia</aff>
<aff id="af4-MCO-20-4-02730"><label>4</label>N.N. Petrov National Medical Research Center of Oncology, Ministry of Public Health of The Russian Federation, Saint Petersburg 197758, Russia</aff>
<aff id="af5-MCO-20-4-02730"><label>5</label>Department of Oncology, I.I. Mechnikov North-Western Medical University, Saint Petersburg 191015, Russia</aff>
<aff id="af6-MCO-20-4-02730"><label>6</label>Sochi Cancer City Hospital No. 2, Sochi 354057, Russia</aff>
<aff id="af7-MCO-20-4-02730"><label>7</label>Department of General and Molecular Medical Genetics, Saint Petersburg Pediatric Medical University, Saint Petersburg 194100, Russia</aff>
<author-notes>
<corresp id="c1-MCO-20-4-02730"><italic>Correspondence to:</italic> Dr Aram A. Musaelyan, Department of Clinical Oncology, Pavlov First Saint Petersburg State Medical University, Lev Tolstoy Street 6-8, Saint Petersburg 197022, Russia <email>amilyfish@126.com a.musaelyan8@gmail.com </email></corresp>
<fn><p><italic>Abbreviations:</italic> ALK, anaplastic lymphoma kinase; CI, confidence interval; ECOG PS, Eastern Cooperative Oncology Group performance status; EGFR, epidermal growth factor receptor; HR, hazard ratio; ICIs, immune checkpoint inhibitors; IHC, immunohistochemical; irAEs, immune-related adverse events; NLR, neutrophil-to-lymphocyte ratio; NSCLC, non-small cell lung cancer; NSE, NLR, smoking status, ECOG; ORR, objective response rate; OS, overall survival; PD-L1, programmed cell death-ligand 1; PFS, progression-free survival; ROC, receiver operating characteristic</p></fn>
</author-notes>
<pub-date pub-type="collection">
<month>04</month>
<year>2024</year></pub-date>
<pub-date pub-type="epub">
<day>20</day>
<month>02</month>
<year>2024</year></pub-date>
<volume>20</volume>
<issue>4</issue>
<elocation-id>32</elocation-id>
<history>
<date date-type="received">
<day>24</day>
<month>08</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>30</day>
<month>01</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2024, Spandidos Publications</copyright-statement>
<copyright-year>2024</copyright-year>
</permissions>
<abstract>
<p>Single-agent immune checkpoint inhibitors (ICIs) are the standard option for chemotherapy-pretreated metastatic non-small cell lung cancer (NSCLC), however only a subset of patients responds to this treatment. The present study aimed at the development of a tool for personalized prediction of the efficacy of ICIs. The study included 181 epidermal growth factor receptor/anaplastic lymphoma kinase-negative patients with metastatic NSCLC receiving single-agent ICI in the second or later line of therapy. For the comparison, a total of 63 metastatic patients with NSCLC treated by chemotherapy were also analyzed. Multivariate analysis revealed that Eastern Cooperative Oncology Group performance status (ECOG PS) &#x2265;2, never-smoking status and the baseline neutrophil-to-lymphocyte ratio (NLR) &#x2265;4.3 were associated with reduced progression-free survival (PFS) and overall survival (OS) &#x005B;ECOG PS: Hazard ratio (HR)=2.09; P=0.028 and HR=2.02; P=0.035, respectively; never-smoking: HR=3.53; P=0.007 and HR=1.80; P=0.004, respectively; NLR &#x2265;4.3: HR=4.34; P&#x003C;0.0001 and HR=4.89; P&#x003C;0.0001 respectively&#x005D;. Patients with an NLR &#x003C;4.3, who had a favorable ECOG PS (0-1) and smoking history in the past, derived the utmost benefit from ICI &#x005B;n=77; objective response rate (ORR)=35&#x0025;; PFS and OS: 17.1 and 33.7 months, respectively&#x005D;. The worst efficacy of ICI was observed in patients who had an NLR &#x2265;4.3 coupled with poor ECOG PS and/or never-smoking status (n=38; ORR=8&#x0025;; PFS=3.2 months and OS=7.2 months). The remaining patients belonged to the group with intermediate outcomes (n=66; ORR=17&#x0025;; PFS and OS: 4.3 and 12.2 months, respectively). While combination of these factors was highly predictive for ICIs, it was not associated with outcomes of chemotherapy treatment. Easily available characteristics of the patients allow for highly accurate predictions of outcomes of single-agent ICI therapy in chemotherapy-pretreated NSCLC.</p>
</abstract>
<kwd-group>
<kwd>immune checkpoint inhibitors</kwd>
<kwd>non-small cell lung cancer</kwd>
<kwd>smoking</kwd>
<kwd>ECOG</kwd>
<kwd>neutrophil-to-lymphocyte ratio</kwd>
<kwd>peripheral blood biomarker</kwd>
</kwd-group>
<funding-group>
<funding-statement><bold>Funding:</bold> The present study was supported by the Russian Science Foundation (grant no. 23-45-10038).</funding-statement>
</funding-group>
</article-meta>
</front>
<body>
<sec sec-type="intro">
<title>Introduction</title>
<p>Immune checkpoint inhibitors (ICIs) have become a standard of care for patients with metastatic non-small cell lung cancer (NSCLC) (<xref rid="b1-MCO-20-4-02730" ref-type="bibr">1</xref>). Immunotherapy may be utilized alone in the first-line treatment if the NSCLC has a high level of PD-L1 expression (<xref rid="b2-MCO-20-4-02730" ref-type="bibr">2</xref>). Single-agent ICIs can also be used in second and subsequent lines of NSCLC treatment, with different drugs having different requirements for programmed cell death-ligand 1 (PD-L1) status (<xref rid="b3-MCO-20-4-02730" ref-type="bibr">3</xref>). In addition, ICIs can be administered upfront in combination with chemotherapy in both PD-L1-positive and -negative patients in the first-line settings (<xref rid="b2-MCO-20-4-02730" ref-type="bibr">2</xref>). However, only a total of 20&#x0025; of patients with NSCLC treated with immunotherapy demonstrate a durable response (<xref rid="b1-MCO-20-4-02730" ref-type="bibr">1</xref>,<xref rid="b2-MCO-20-4-02730" ref-type="bibr">2</xref>). There is an intensive search for reliable predictive markers allowing clinically meaningful selection of patients for the treatment with anti-PD-1/PD-L1 antibodies, thus avoiding unnecessary adverse events and decreasing financial burden (<xref rid="b3-MCO-20-4-02730" ref-type="bibr">3</xref>).</p>
<p>Immunohistochemical (IHC) analysis of PD-L1 expression on tumor cells and/or tumor-infiltrating immune cells is the only companion test approved for ICI therapy of metastatic NSCLC (<xref rid="b2-MCO-20-4-02730" ref-type="bibr">2</xref>). The indication was based on the results of the study KEYNOTE-024(<xref rid="b4-MCO-20-4-02730" ref-type="bibr">4</xref>), which showed improved progression-free survival (PFS) and overall survival (OS) using anti-PD-1 monotherapy compared with standard chemotherapy in previously untreated metastatic NSCLC expressing PD-L1 &#x2265;50&#x0025; (<xref rid="b4-MCO-20-4-02730" ref-type="bibr">4</xref>). However, the predictive value of PD-L1 expression is controversial, as both positive and negative predictive value of this marker is relatively low (<xref rid="b5-MCO-20-4-02730" ref-type="bibr">5</xref>). Other biomarkers, such as tumor mutation burden (TMB) or various gene expression signatures, have shown promise, however their use requires sophisticated laboratory tests and they have not been rigorously validated for reproducibility (<xref rid="b6-MCO-20-4-02730" ref-type="bibr">6</xref>,<xref rid="b7-MCO-20-4-02730" ref-type="bibr">7</xref>). Therefore, there is an unmet need for robust predictive markers for ICI efficacy in metastatic NSCLC.</p>
<p>Cancer-associated inflammation was suggested as one of the crucial factors interacting with immune surveillance (<xref rid="b8-MCO-20-4-02730" ref-type="bibr">8</xref>,<xref rid="b9-MCO-20-4-02730" ref-type="bibr">9</xref>). High neutrophil-to-lymphocyte ratio (NLR) is a well-known peripheral blood marker of systemic inflammation (<xref rid="b10-MCO-20-4-02730" ref-type="bibr">10</xref>). Changes of the NLR may be an indicator of immune response in patients with various cancers, including metastatic NSCLC (<xref rid="b10-MCO-20-4-02730" ref-type="bibr">10</xref>). Several studies have revealed that increased NLR has a negative predictive value in patients with metastatic NSCLC treated with ICIs (<xref rid="b11-MCO-20-4-02730" ref-type="bibr">11</xref>,<xref rid="b12-MCO-20-4-02730" ref-type="bibr">12</xref>). Baseline and on-treatment clinical parameters, such as smoking status, Eastern Cooperative Oncology Group performance status (ECOG PS) and immune-related adverse events (irAEs), may also serve as non-invasive and feasible predictive markers for ICIs. The use of these indicators alone proved to have insufficient reliability for personalizing ICI treatment (<xref rid="b8-MCO-20-4-02730" ref-type="bibr">8</xref>). The accuracy of the prediction of the ICI response may be increased if other relevant parameters are taken into consideration (<xref rid="b13-MCO-20-4-02730" ref-type="bibr">13</xref>). In the present study, the predictive role of clinical and laboratory characteristics of patients with NSCLC were evaluated and it was demonstrated that these are predictive for a long-term outcome of the ICI therapy.</p>
</sec>
<sec sec-type="Materials|methods">
<title>Materials and methods</title>
<sec>
<title/>
<sec>
<title>Patients and data collection</title>
<p>The present retrospective study included 181 patients with metastatic NSCLC without epidermal growth factor receptor (EGFR) mutations or anaplastic lymphoma kinase (ALK) rearrangements, who received single-agent ICI in the second or subsequent lines of therapy. The median age at diagnosis was 65 years, with a range of 34-86 years. The ICI cohort consisted of 129 males (71.3&#x0025;) and 52 females (28.7&#x0025;). Patients were treated according to standard clinical practice. These patients received at least two doses of standard therapeutic regimens (pembrolizumab, 200 mg intravenously once every 3 weeks; nivolumab, 3 mg/kg every 2 weeks or 480 mg every 4 weeks; atezolizumab, 1,200 mg intravenously once every 3 weeks). The therapy was performed until disease progression, unacceptable toxicity, or for up to two years. ICI predictive factors were also analyzed in the comparison group, composed of 63 patients with metastatic NSCLC without activating mutations in EGFR/ALK genes, who were treated by the first-line standard platinum-based chemotherapy and did not receive ICIs in subsequent treatment lines (comparison cohort). The median age was 63 years (range, 41-80 years). The latter cohort was collected to determine whether the analyzed predictive factors are ICI-specific.</p>
<p>All patients were treated between February 2017 and September 2022 at the Pavlov First Saint Petersburg State Medical University or at the N.P. Napalkov City Cancer Center (both at Saint Petersburg, Russia). The investigation was approved by the local Ethics Committee of Pavlov First Saint Petersburg State Medical University (approval no. 312-2022). The study protocol conformed to the ethical guidelines of the Declaration of Helsinki and the ethical guidelines for medical and health research involving human subjects. All participants signed informed consent forms.</p>
<p>Inclusion criteria for both cohorts were as follows: Age, 18 years and older; ECOG PS, 0-3(<xref rid="b12-MCO-20-4-02730" ref-type="bibr">12</xref>); histologically confirmed NSCLC; absence of EGFR mutations and ALK translocations; and stage IV. The stage was classified based on the tumor node metastasis staging and the American Joint Committee on Cancer (8th edition, 2017) (<xref rid="b14-MCO-20-4-02730" ref-type="bibr">14</xref>). Exclusion criteria for the ICI group were as follows: Previous immunotherapy; concomitant infection including human immunodeficiency virus or hepatitis; therapy by systemic steroids; and previous or ongoing autoimmune disease. Exclusion criteria for the chemotherapy cohort was the presence of ICIs in subsequent lines of therapy.</p>
<p>Baseline demographics (age, sex, body mass index and smoking status), clinical (ECOG PS, number of metastases and their sites), morphological (histology and PD-L1 expression) and treatment data (previous and subsequent type of treatment, line of therapy and type of anti-PD-1/PD-L1 agents) were assessed. The main characteristics of the patients are summarized in <xref rid="tI-MCO-20-4-02730" ref-type="table">Table I</xref>. The tumor PD-L1 expression was assessed as part of standard clinical practice and was evaluated in 114 patients with NSCLC in the ICI cohort by two IHC kits: Dako PD-L1 clone 22C3 pharmDx (Agilent Technologies, Inc.) and Ventana PD-L1 clone SP142 (Ventana Medical Systems, Inc.).</p>
<p>The routine blood tests, including neutrophil and lymphocyte count for subsequent calculation of the ratio, were performed within one week before the start of therapy and after two cycles of treatment.</p>
<p>Tumor response was defined using the Immune Response Evaluation Criteria in Solid Tumors (iRECIST) (for ICIs cohort) and RECIST 1.1 (for comparison cohort) (<xref rid="b15-MCO-20-4-02730" ref-type="bibr">15</xref>). irAEs, which occurred during the period of ICI administration, were also recorded. The severity of irAEs was graded using the criteria of the National Cancer Institute Common Terminology Criteria for Adverse Events version 5.0(<xref rid="b16-MCO-20-4-02730" ref-type="bibr">16</xref>).</p>
</sec>
<sec>
<title>Statistical analysis</title>
<p>The endpoints of the study were objective response rate (ORR), PFS and OS. ORR was defined as a proportion of patients with complete and partial response according to iRECIST (for the ICI cohort) or RECIST 1.1 (for the comparison cohort). PFS was defined as the time from the start of ICI therapy to the progression of disease or censored at the date of the last patient contact or at the follow-up date. OS was defined as the time from the first cycle of ICI treatment until death or the date of last patient contact or the follow-up date.</p>
<p>Cut-off values were calculated using the receiver operating characteristic (ROC) analysis. Fisher&#x0027;s exact test and chi-squared test were used to compare qualitative parameters and Mann-Whitney U test was applied to quantitative characteristics. PFS and OS were compared between the groups using a log-rank test with HR analysis and subsequent graphical visualization was performed using the Kaplan-Meier method. Multivariate Cox proportional hazard regression analysis was used to determine the relationship between survival and different potential predictive variables.</p>
<p>All statistical analyses were performed using GraphPad Prism (v.9.3.1; GraphPad Software, Inc.; Dotmatics). P&#x003C;0.05 was considered to indicate a statistically significant difference.</p>
</sec>
</sec>
</sec>
<sec sec-type="Results">
<title>Results</title>
<p>The median follow-up for patients receiving ICI was 13.6 months (95&#x0025; CI, 11.5-16.1 months). The ORR was 41/181 (23&#x0025;) (<xref rid="tI-MCO-20-4-02730" ref-type="table">Table I</xref>). Median PFS in patients with NSCLC receiving ICI in the second or subsequent line of therapy approached 4.9 months (95&#x0025; CI, 4.2-5.6 months) and median OS was 13.7 months (95&#x0025; CI, 11.5-17.2 months) (<xref rid="tI-MCO-20-4-02730" ref-type="table">Table I</xref>).</p>
<p>No significant association was observed between age, sex, ECOG PS, smoking history, histological tumor type, PD-L1 expression or line of the therapy and ORR (<xref rid="tII-MCO-20-4-02730" ref-type="table">Table II</xref>) However, some clinical characteristics of the patients demonstrated statistically significant associations with PFS or OS. Median PFS was significantly longer in patients with good performance status (ECOG 0/1 vs. 2/3: 6.0 vs. 3.6 months, respectively; P&#x003C;0.0001) (<xref rid="f1-MCO-20-4-02730" ref-type="fig">Fig. 1A</xref>). This association was also maintained for OS (15.8 vs. 9.8 months, P=0.003) (<xref rid="f2-MCO-20-4-02730" ref-type="fig">Fig. 2A</xref>). The median PFS and OS were significantly longer in ever-smokers compared with never-smokers &#x005B;PFS: 11.3 vs. 4.0 months, P&#x003C;0.0001 (<xref rid="f1-MCO-20-4-02730" ref-type="fig">Fig. 1B</xref>); OS: 16.6 vs. 9.9 months, P=0.008 (<xref rid="f2-MCO-20-4-02730" ref-type="fig">Fig. 2B</xref>)&#x005D;. Presence of liver metastases was associated with shorter PFS &#x005B;3.6 vs. 5.1 months, P=0.004 (<xref rid="f1-MCO-20-4-02730" ref-type="fig">Fig. 1C</xref>)&#x005D;, however this trend did not reach statistical significance for OS (P=0.084) (<xref rid="f2-MCO-20-4-02730" ref-type="fig">Fig. 2C</xref>). In addition, no relationship was observed between histological tumor type (squamous cell carcinoma vs. non-squamous cell carcinoma) and PFS (P=0.239) and OS (P=0.378) (data not shown).</p>
<p>PD-L1 expression status was known for 114 patients with patients with NSCLC treated by ICI therapy. The optimal cut-off value for tumor PD-L1 expression was determined as &#x2265;1&#x0025; for both PFS and OS. There was no statistically significant relationship between PD-L1 expression &#x2265;1&#x0025; and longer PFS (5.6 vs. 4.1 months, HR 1.25; 95&#x0025; CI, 0.89-1.83; P=0.216) (<xref rid="f3-MCO-20-4-02730" ref-type="fig">Fig. 3A</xref>) and OS (14.6 vs. 10.9 months; HR 1.33; 95&#x0025; CI, 0.90-1.99; P=0.151) (<xref rid="f4-MCO-20-4-02730" ref-type="fig">Fig. 4A</xref>). Furthermore, stratification into three categories of PD-L1 expression (&#x003C;1&#x0025;, &#x2265;1-49&#x0025; and &#x2265;50&#x0025;) did not reveal a significant association with PFS (P=0.354) and OS (P=0.413) (data not shown).</p>
<p>irAEs were observed in 71/181 (39&#x0025;) patients with NSCLC receiving second or subsequent lines of ICI (<xref rid="tI-MCO-20-4-02730" ref-type="table">Table I</xref>). Grade &#x2265;3 toxicity was detected in 12/71 patients (17&#x0025;) (<xref rid="tI-MCO-20-4-02730" ref-type="table">Table I</xref>). The most common irAEs were thyroid dysfunction &#x005B;25/71 (35&#x0025;)&#x005D;, skin reactions &#x005B;17/71 (24&#x0025;)&#x005D;, pneumonitis &#x005B;8/71 (11&#x0025;)&#x005D; and hepatitis &#x005B;6/71 (8&#x0025;)&#x005D; (<xref rid="tI-MCO-20-4-02730" ref-type="table">Table I</xref>). The presence of irAEs was associated with prolonged OS (18.5 vs. 11.3 months, P=0.011) (<xref rid="f2-MCO-20-4-02730" ref-type="fig">Fig. 2D</xref>), but not with increased PFS (P=0.098) (<xref rid="f1-MCO-20-4-02730" ref-type="fig">Fig. 1D</xref>). In addition, no significant association was observed between irAEs and ORR (<xref rid="tII-MCO-20-4-02730" ref-type="table">Table II</xref>).</p>
<p>NLR was significantly associated with the outcome of ICI therapy. The highest predictive value was observed for the threshold equal to 4.3, as determined by the ROC analysis. PFS was significantly shorter in patients with baseline NLR &#x2265;4.3 compared with patients with NLR &#x003C;4.3: (3.2 vs. 15.4 months, P&#x003C;0.0001) (<xref rid="f3-MCO-20-4-02730" ref-type="fig">Fig. 3B</xref>). The median of OS was also evidently shorter in patients with the NLR &#x2265;4.3 compared with the NLR &#x003C;4.3 group (7.8 vs. 21.8 months, P&#x003C;0.0001) (<xref rid="f4-MCO-20-4-02730" ref-type="fig">Fig. 4B</xref>). The ORR was significantly higher in patients with baseline NLR &#x003C;4.3 compared with patients with NLR &#x2265;4.3: 27 and 12&#x0025;, respectively (P=0.034) (<xref rid="tII-MCO-20-4-02730" ref-type="table">Table II</xref>).</p>
<p>The cut-off value for NLR after two cycles was determined as &#x2265;4.5 for monitoring ICI efficacy. The NLR &#x2265;4.5 after two cycles was a predictor of worse PFS (3.4 vs. 13.9 months, P&#x003C;0.0001) (<xref rid="f3-MCO-20-4-02730" ref-type="fig">Fig. 3C</xref>) and OS (9.3 vs. 21.6 months, P&#x003C;0.0001) (<xref rid="f4-MCO-20-4-02730" ref-type="fig">Fig. 4C</xref>). It was further investigated whether the dynamic change of NLR (the difference between the ratio after two cycles and baseline value) observed during ICI therapy had a predictive value. The optimal cut-off level of the dynamic change of NLR was an increase of &#x2265;24&#x0025;. The NLR dynamic changes of &#x2265;24&#x0025; were associated with shorter PFS (4.0 vs. 6.3 months, P=0.029) (<xref rid="f3-MCO-20-4-02730" ref-type="fig">Fig. 3D</xref>) and OS (11.2 vs. 17.2 months, P&#x003C;0.0001) (<xref rid="f4-MCO-20-4-02730" ref-type="fig">Fig. 4D</xref>). The improvement of NLR during ICI exposure tended to indicate a better outcome, however none of the thresholds determined by ROC analysis produced statistically significant associations. In addition, no significant association was observed between NLR after two cycles, NLR dynamic changes and the ORR (<xref rid="tII-MCO-20-4-02730" ref-type="table">Table II</xref>). Univariate analysis of the patient data demonstrated that ECOG PS &#x2265;2 (HR, 1.98; 95&#x0025; CI, 1.30-2.93; P=0.001), never smoking (HR, 1.91; 95&#x0025; CI, 1.38-2.82; P=0.001), presence of liver metastasis (HR, 1.42; 95&#x0025; CI, 1.07-2.31; P=0.026), NLR &#x2265;4.3 (HR, 4.79; 95&#x0025; CI, 3.24-7.07; P&#x003C;0.0001) and NLR after two cycles of ICI (HR, 2.09; 95&#x0025; CI, 1.43-3.01; P=0.0001) were significantly associated with worse PFS (<xref rid="tIII-MCO-20-4-02730" ref-type="table">Table III</xref>). In multivariate analysis, only ECOG PS &#x2265;2 (HR, 2.09; 95&#x0025; CI, 1.09-4.07; P=0.028), never smoking status (HR, 3.53; 95&#x0025; CI, 2.07-9.29; P=0.007) and baseline NLR &#x2265;4.3 (HR, 4.34; 95&#x0025; CI, 2.65-7.03; P&#x003C;0.0001) retained significance for decreased PFS (<xref rid="tIII-MCO-20-4-02730" ref-type="table">Table III</xref>).</p>
<p>The univariate analysis for OS demonstrated that ECOG PS &#x2265;2 (HR, 2.09; 95&#x0025; CI, 1.35-3.16; P=0.001), never smoking (HR, 1.82; 95&#x0025; CI, 1.23-2.69; P=0.003), absence of irAEs (HR, 1.69; 95&#x0025; CI, 1.14-2.54; P=0.011), baseline NLR &#x2265;4.3 (HR, 5.07; 95&#x0025; CI 3.58-8.09; P&#x003C;0.0001), NLR after two cycles of the therapy (HR 2.67; 95&#x0025; CI, 1.78-3.96; P&#x003C;0.0001) and NLR dynamic changes &#x2265;24&#x0025; (HR, 1.66; 95&#x0025; CI, 1.11-2.46; P=0.012) were negative predictive factors (<xref rid="tIV-MCO-20-4-02730" ref-type="table">Table IV</xref>). However, in multivariate analysis only ECOG PS &#x2265;2 (HR, 2.02; 95&#x0025; CI, 1.06-3.91; P=0.035), never smoking (HR, 1.80; 95&#x0025; CI, 1.21-2.68; P=0.004) and baseline NLR &#x2265;4.3 (HR, 4.89; 95&#x0025; CI, 3.16-7.62; P&#x003C;0.0001) retained significance for OS (<xref rid="tIV-MCO-20-4-02730" ref-type="table">Table IV</xref>).</p>
<sec>
<title/>
<sec>
<title>Baseline prognostic score</title>
<p>In multivariate analysis, the independent predictors of both worse PFS and OS were pretreatment NLR &#x2265;4.3, non-smoking status and ECOG PS&#x2265;2. Based on the data, a baseline prognostic NLR, smoking status, ECOG (NSE) score named after the first letters of the included markers was developed (NLR at baseline &#x2265;4.3, 2 points; non-smoking status, 1 point; and ECOG &#x2265;2, 1 point) (<xref rid="tV-MCO-20-4-02730" ref-type="table">Table V</xref>). NSE score categorized three groups of patients with NSCLC depending on the outcome of ICI therapy: Good (group 1, 0 points); intermediate (group 2, 1-2 points) and poor (group 3, &#x2265;3 points) (<xref rid="tV-MCO-20-4-02730" ref-type="table">Table V</xref>). Among patients receiving ICIs, 77 patients (43&#x0025;) belonged to the NSE group 1, 66 (36&#x0025;) to group 2 and 38 (21&#x0025;) to group 3. The ORR in good, intermediate and poor prognostic groups was 35, 17 and 8&#x0025;, respectively (P=0.002) (<xref rid="tII-MCO-20-4-02730" ref-type="table">Table II</xref>). The median PFS for group 1 was 17.1 months, and for groups 2 and 3 it was 4.3 and 3.2 months, respectively (P&#x003C;0.0001) (<xref rid="f5-MCO-20-4-02730" ref-type="fig">Fig. 5A</xref>). The median OS was 33.7, 12.2 and 7.2 months, respectively (P&#x003C;0.0001) (<xref rid="f5-MCO-20-4-02730" ref-type="fig">Fig. 5B</xref>). Strong differences between these groups retained significance upon multivariate analysis (<xref rid="tVI-MCO-20-4-02730" ref-type="table">Table VI</xref>). In addition, no significant differences were revealed between the type of ICI (pembrolizumab, nivolumab or atezolizumab) and the endpoints of the study in each prognostic group (data not shown).</p>
</sec>
<sec>
<title>Chemotherapy cohort</title>
<p>Median follow-up was 15.3 months (95&#x0025; CI, 11.3-20.2 months) in the chemotherapy cohort. The ORR was 27&#x0025; in this group of patients. Median PFS and OS were 4.6 months (95&#x0025; CI, 4.0-5.9 months) and 10.4 months (95&#x0025; CI, 8.9-14.2 months), respectively (<xref rid="tI-MCO-20-4-02730" ref-type="table">Table I</xref>).</p>
<p>No significant association was observed between clinical parameters, peripheral blood markers (baseline NLR, NLR after two cycles and NLR dynamic changes) and treatment efficacy (ORR, PFS and OS) in patients receiving chemotherapy (<xref rid="tVII-MCO-20-4-02730" ref-type="table">Table VII</xref>).</p>
<p>It was also addressed whether NSE score as aforementioned is predictive for benefit from cytotoxic drugs. In the chemotherapy cohort according to the NSE score, a total of 20 patients (32&#x0025;) were assigned to group 1, 27 (42.9&#x0025;) to group 2 and 16 (25&#x0025;) to group 3 (data not shown). No difference was observed in terms of response rate according to scoring groups. The PFS and OS were similar in these groups &#x005B;PFS: 4.8, 4.1 and 4.6 months, respectively; P=0.226 (<xref rid="f5-MCO-20-4-02730" ref-type="fig">Fig. 5C</xref>); OS: 12.8, 10.2 and 10.1 months, respectively; P=0.389 (<xref rid="f5-MCO-20-4-02730" ref-type="fig">Fig. 5D</xref>)&#x005D;.</p>
</sec>
</sec>
</sec>
<sec sec-type="Discussion">
<title>Discussion</title>
<p>In the present study the predictive role of certain clinical characteristics and peripheral blood markers on efficacy to ICIs was investigated. ECOG performance status, smoking history, presence of liver metastasis, irAEs and NLR demonstrated associations with outcomes in metastatic patients with NSCLC receiving single-agent ICI in second and subsequent lines of therapy. Additionally, a combination of NLR, ECOG and smoking history yielded an accurate prediction of ICI therapy outcome. This combination was not predictive in the patients, who received chemotherapy without subsequent ICI administration. The comparison of these two groups is compromised by the fact that ICI treatment was applied in second or subsequent lines of therapy, while cytotoxic drugs were utilized upfront. However, it is considered that this approach is optimal to minimize the role of confounding factors. Notably, only a minority of patients with NSCLC receive ICI therapy without chemotherapy in the first line and the selection of these cases is based on strict criteria, thus, it was not possible to collect a substantial number of subjects in this setting. However, the responses of patients with NSCLC to chemotherapy in the second or third lines of treatment are usually minimal, thus this analysis was intentionally limited to the first line platinum-based doublets.</p>
<p>The investigation did not demonstrate that PD-L1 expression status was significant, although some patients did not undergo PD-L1 testing and two different IHC assays were used for the PD-L1 analysis. These results were consistent with studies, which utilized single-agent nivolumab or atezolizumab after failure of cytotoxic therapy (<xref rid="b17-MCO-20-4-02730" ref-type="bibr">17</xref>,<xref rid="b18-MCO-20-4-02730" ref-type="bibr">18</xref>). However, a clinical trial revealed that patients with NSCLC with PD-L1 expression in &#x003E;1&#x0025; of tumor cells had improved treatment outcomes (<xref rid="b19-MCO-20-4-02730" ref-type="bibr">19</xref>). A meta-analysis involving 3,688 patients from seven randomized trials, who were subjected to the second or subsequent lines of therapy and were evaluated for OS, revealed that ICIs outperform cytotoxic drugs across all PD-L1 expression subgroups (<xref rid="b20-MCO-20-4-02730" ref-type="bibr">20</xref>). At the same time, the most marked effect from ICIs was observed for NSCLCs expressing PD-L1 in &#x003E;50&#x0025; of tumor cells (<xref rid="b20-MCO-20-4-02730" ref-type="bibr">20</xref>).</p>
<p>In a number of studies, the immunotherapy survival benefit was shown to be associated with the anatomic location of metastasis (<xref rid="b21-MCO-20-4-02730" ref-type="bibr">21</xref>). The liver has an immunosuppressive microenvironment, thus the presence of metastases in this organ may influence the efficacy of the ICI (<xref rid="b22-MCO-20-4-02730" ref-type="bibr">22</xref>). A recent meta-analysis has shown that metastatic involvement of the liver was associated with worse PFS in patients with NSCLC, although it did not result in shorter OS (<xref rid="b23-MCO-20-4-02730" ref-type="bibr">23</xref>). The results of the present study provided some support for the aforementioned findings. Another clinical parameter, that may serve as a potential predictor of ICI efficacy, is the presence of irAEs. The rationale is that irAEs are caused by hyperactivation of the immune system during ICI therapy and, hence, are indirectly associated with antitumor response (<xref rid="b24-MCO-20-4-02730" ref-type="bibr">24</xref>). Similarly, to previous studies (<xref rid="b25-MCO-20-4-02730" ref-type="bibr">25</xref>,<xref rid="b26-MCO-20-4-02730" ref-type="bibr">26</xref>), the presence of irAEs in the data of the present study was associated with prolonged OS. However, this association was not retained upon multivariate analysis.</p>
<p>The contribution of ECOG performance status in determining treatment outcome is well established. Patients with poor overall condition usually have compromised &#x2018;defense&#x2019; mechanisms. In addition, the development of antitumor immune response may take time, which is another factor affecting outcomes in patients with short life expectancy (<xref rid="b27-MCO-20-4-02730" ref-type="bibr">27</xref>). ECOG PS &#x2265;2 was an independent predictor of short PFS and OS in the present study, which is consistent with other studies (<xref rid="b20-MCO-20-4-02730" ref-type="bibr">20</xref>,<xref rid="b28-MCO-20-4-02730" ref-type="bibr">28</xref>).</p>
<p>Smoking history is a particularly relevant predictive marker for ICI response in patients with NSCLC. Cigarette consumption is associated with high TMB and consequently, increased production of tumor neoantigens (<xref rid="b29-MCO-20-4-02730" ref-type="bibr">29</xref>). The data of the present study on improved ICI treatment outcomes in smokers are consistent with the results of meta-analysis and other individual studies (<xref rid="b30-MCO-20-4-02730 b31-MCO-20-4-02730 b32-MCO-20-4-02730" ref-type="bibr">30-32</xref>).</p>
<p>NLR is a surrogate marker of chronic inflammation (<xref rid="b33-MCO-20-4-02730" ref-type="bibr">33</xref>). Neutrophils in the peripheral blood represent precursors of immunosuppressive cells (tumor-associated neutrophils and granulocytic myeloid-derived suppressor cells) in the tumor microenvironment, which promote tumor progression (<xref rid="b11-MCO-20-4-02730" ref-type="bibr">11</xref>,<xref rid="b34-MCO-20-4-02730" ref-type="bibr">34</xref>). In turn, lymphocytes are responsible for cellular immune response (<xref rid="b11-MCO-20-4-02730" ref-type="bibr">11</xref>). A high NLR ratio is a predictor of worse prognosis in NSCLC, regardless of the treatment type. Increased NLR may predict for poor outcomes of chemotherapy (<xref rid="b35-MCO-20-4-02730" ref-type="bibr">35</xref>), however, the data of the present study did not confirm this association. In addition, NLR was predictive for poor efficacy of immune therapy, which is in agreement with previous research (<xref rid="b36-MCO-20-4-02730" ref-type="bibr">36</xref>). It was also demonstrated that a high level of NLR before and after two cycles of ICI and the dynamic increase of this ratio during the ICI treatment, were associated with worse survival outcomes. Similar results were produced by several other studies (<xref rid="b12-MCO-20-4-02730" ref-type="bibr">12</xref>,<xref rid="b37-MCO-20-4-02730" ref-type="bibr">37</xref>,<xref rid="b38-MCO-20-4-02730" ref-type="bibr">38</xref>). The elimination of immunosuppressive derivatives of peripheral blood neutrophils appears to be a promising strategy for overcoming the resistance to ICIs (<xref rid="b34-MCO-20-4-02730" ref-type="bibr">34</xref>). In accordance with this hypothesis, therapeutic modulators of immunosuppressive neutrophils increased the efficacy of ICI in preclinical models (<xref rid="b34-MCO-20-4-02730" ref-type="bibr">34</xref>). However, only a limited number of these combinations have reached clinical trials and are currently under investigation (<xref rid="b39-MCO-20-4-02730 b40-MCO-20-4-02730 b41-MCO-20-4-02730" ref-type="bibr">39-41</xref>).</p>
<p>The combined assessment of different markers in a predictive score, rather than using a single predictive marker, may improve identification of patients who are most likely to benefit from ICI therapy. Numerous predictive ICI-related scores have been studied in patients with advanced NSCLC, such as EPSILoN, ALI, LIPI, iSEND, LIPS-3 and combined NLR-TMB score (<xref rid="b8-MCO-20-4-02730" ref-type="bibr">8</xref>,<xref rid="b9-MCO-20-4-02730" ref-type="bibr">9</xref>,<xref rid="b14-MCO-20-4-02730" ref-type="bibr">14</xref>,<xref rid="b20-MCO-20-4-02730" ref-type="bibr">20</xref>,<xref rid="b42-MCO-20-4-02730" ref-type="bibr">42</xref>,<xref rid="b43-MCO-20-4-02730" ref-type="bibr">43</xref>). All these indices are included in the NLR. However, some of them included laboratory markers, such as TMB, PD-L1 and LDH, which are not routinely studied in a number of centers for ICI therapy in second and subsequent lines of treatment in patients with NSCLC.</p>
<p>A new baseline prognostic score named NSE was developed. It is based on markers that were independent predictors of survival outcomes in multivariate analysis. The advantage of the approach is the simplicity of it, as it is based on easily accessible characteristics of the patients. In brief, the data of the present study suggested that patients with an NLR ratio &#x003C;4.3, who have good performance status and history of smoking, are the most likely to derive benefit from ICI therapy. By contrast, patients with an NLR &#x2265;4.3 coupled with poor ECOG and/or lack of tobacco exposure, are highly unlikely to respond to ICI. The remaining subjects consist of the group of intermediate ICI therapy outcome. Notably, this reasoning is specific for immunotherapy, as the same scoring was not predictive for patients receiving cytotoxic drugs. The limitations of this investigation were the retrospective nature of the study and the absence of other routine blood tests, including absolute lymphocyte count and platelet-lymphocyte ratio, which were not considered in the data analysis.</p>
<p>In conclusion, the independent predictive factors for short PFS and OS, such as a baseline NLR &#x2265;4.3, non-smoking status and ECOG PS &#x2265;2 were demonstrated in the present study. In addition, the developed new NSE score based on these markers may assist the decision-making for NSCLC immunotherapy in second and subsequent line settings. However, the score requires validation in a prospective study.</p>
</sec>
</body>
<back>
<ack>
<title>Acknowledgements</title>
<p>The authors would like to cordially thank Professor William R. Miller (University of Edinburgh, United Kingdom) for his invaluable assistance in improving the language of this manuscript.</p>
</ack>
<sec sec-type="data-availability">
<title>Availability of data and materials</title>
<p>The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.</p>
</sec>
<sec>
<title>Authors&#x0027; contributions</title>
<p>AAM was responsible for the development of the research design, review of publications on the topic of the article, analysis of the data obtained, design of illustrative material, statistical analysis and article writing. FVM was responsible for the development of the research design, methodology and analysis of the data obtained. TEE, APO, KAO, MAU, SVOd, IVC and AMD were involved in curation of patients and data collection. ALA, ENI and SVOr were responsible for conception and design development, as well as scientific editing and research management. AAM and SVOr confirm the authenticity of all the raw data. All authors read and approved the final version of the manuscript.</p>
</sec>
<sec>
<title>Ethics approval and consent to participate</title>
<p>The study was approved (approval no. 312 2022) by the Ethics Committee of Pavlov First Saint Petersburg State Medical University (Saint Petersburg, Russia). All participants signed informed consent forms.</p>
</sec>
<sec>
<title>Patient consent for publication</title>
<p>Not applicable.</p>
</sec>
<sec sec-type="COI-statement">
<title>Competing interests</title>
<p>The authors declare that they have no competing interests.</p>
</sec>
<ref-list>
<title>References</title>
<ref id="b1-MCO-20-4-02730"><label>1</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Duchemann</surname><given-names>B</given-names></name><name><surname>Remon</surname><given-names>J</given-names></name><name><surname>Naigeon</surname><given-names>M</given-names></name><name><surname>Mezquita</surname><given-names>L</given-names></name><name><surname>Ferrara</surname><given-names>R</given-names></name><name><surname>Cassard</surname><given-names>L</given-names></name><name><surname>Jouniaux</surname><given-names>JM</given-names></name><name><surname>Boselli</surname><given-names>L</given-names></name><name><surname>Grivel</surname><given-names>J</given-names></name><name><surname>Auclin</surname><given-names>E</given-names></name><etal/></person-group><article-title>Integrating circulating biomarkers in the immune checkpoint inhibitor treatment in lung cancer</article-title><source>Cancers (Basel)</source><volume>12</volume><issue>3625</issue><year>2020</year><pub-id pub-id-type="pmid">33287347</pub-id><pub-id pub-id-type="doi">10.3390/cancers12123625</pub-id></element-citation></ref>
<ref id="b2-MCO-20-4-02730"><label>2</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Tang</surname><given-names>S</given-names></name><name><surname>Qin</surname><given-names>C</given-names></name><name><surname>Hu</surname><given-names>H</given-names></name><name><surname>Liu</surname><given-names>T</given-names></name><name><surname>He</surname><given-names>Y</given-names></name><name><surname>Guo</surname><given-names>H</given-names></name><name><surname>Yan</surname><given-names>H</given-names></name><name><surname>Zhang</surname><given-names>J</given-names></name><name><surname>Tang</surname><given-names>S</given-names></name><name><surname>Zhou</surname><given-names>H</given-names></name></person-group><article-title>Immune checkpoint inhibitors in non-small cell lung cancer: Progress, challenges, and prospects</article-title><source>Cells</source><volume>19</volume><issue>320</issue><year>2022</year><pub-id pub-id-type="pmid">35159131</pub-id><pub-id pub-id-type="doi">10.3390/cells11030320</pub-id></element-citation></ref>
<ref id="b3-MCO-20-4-02730"><label>3</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Ding</surname><given-names>H</given-names></name><name><surname>Xin</surname><given-names>W</given-names></name><name><surname>Tong</surname><given-names>Y</given-names></name><name><surname>Sun</surname><given-names>J</given-names></name><name><surname>Xu</surname><given-names>G</given-names></name><name><surname>Ye</surname><given-names>Z</given-names></name><name><surname>Rao</surname><given-names>Y</given-names></name></person-group><article-title>Cost effectiveness of immune checkpoint inhibitors for treatment of non-small cell lung cancer: A systematic review</article-title><source>PLoS One</source><volume>15</volume><issue>e0238536</issue><year>2020</year><pub-id pub-id-type="pmid">32877435</pub-id><pub-id pub-id-type="doi">10.1371/journal.pone.0238536</pub-id></element-citation></ref>
<ref id="b4-MCO-20-4-02730"><label>4</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Reck</surname><given-names>M</given-names></name><name><surname>Rodr&#x00ED;guez-Abreu</surname><given-names>D</given-names></name><name><surname>Robinson</surname><given-names>AG</given-names></name><name><surname>Hui</surname><given-names>R</given-names></name><name><surname>Cs&#x0151;szi</surname><given-names>T</given-names></name><name><surname>F&#x00FC;l&#x00F6;p</surname><given-names>A</given-names></name><name><surname>Gottfried</surname><given-names>M</given-names></name><name><surname>Peled</surname><given-names>N</given-names></name><name><surname>Tafreshi</surname><given-names>A</given-names></name><name><surname>Cuffe</surname><given-names>S</given-names></name><etal/></person-group><article-title>Pembrolizumab versus chemotherapy for PD-L1-positive non-small-cell lung cancer</article-title><source>N Engl J Med</source><volume>375</volume><fpage>1823</fpage><lpage>1833</lpage><year>2016</year><pub-id pub-id-type="pmid">27718847</pub-id><pub-id pub-id-type="doi">10.1056/NEJMoa1606774</pub-id></element-citation></ref>
<ref id="b5-MCO-20-4-02730"><label>5</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Signorelli</surname><given-names>D</given-names></name><name><surname>Giannatempo</surname><given-names>P</given-names></name><name><surname>Grazia</surname><given-names>G</given-names></name><name><surname>Aiello</surname><given-names>MM</given-names></name><name><surname>Bertolini</surname><given-names>F</given-names></name><name><surname>Mirabile</surname><given-names>A</given-names></name><name><surname>Buti</surname><given-names>S</given-names></name><name><surname>Vasile</surname><given-names>E</given-names></name><name><surname>Scotti</surname><given-names>V</given-names></name><name><surname>Pisapia</surname><given-names>P</given-names></name><etal/></person-group><article-title>Patients selection for immunotherapy in solid tumors: Overcome the Na&#x00EF;ve vision of a single biomarker</article-title><source>Biomed Res Int</source><volume>2019</volume><issue>9056417</issue><year>2019</year><pub-id pub-id-type="pmid">31179334</pub-id><pub-id pub-id-type="doi">10.1155/2019/9056417</pub-id></element-citation></ref>
<ref id="b6-MCO-20-4-02730"><label>6</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Kim</surname><given-names>J</given-names></name><name><surname>Ha</surname><given-names>H</given-names></name><name><surname>Park</surname><given-names>J</given-names></name><name><surname>Cho</surname><given-names>J</given-names></name><name><surname>Lim</surname><given-names>JH</given-names></name><name><surname>Lee</surname><given-names>MH</given-names></name></person-group><article-title>Association of smoking status with efficacy of first-line immune checkpoint inhibitors in advanced non-small cell lung cancers: A systematic review and meta-analysis</article-title><source>J Cancer</source><volume>13</volume><fpage>364</fpage><lpage>372</lpage><year>2022</year><pub-id pub-id-type="pmid">35069886</pub-id><pub-id pub-id-type="doi">10.7150/jca.65374</pub-id></element-citation></ref>
<ref id="b7-MCO-20-4-02730"><label>7</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Socinski</surname><given-names>M</given-names></name><name><surname>Velcheti</surname><given-names>V</given-names></name><name><surname>Mekhail</surname><given-names>T</given-names></name><name><surname>Chae</surname><given-names>YK</given-names></name><name><surname>Leal</surname><given-names>TA</given-names></name><name><surname>Dowell</surname><given-names>JE</given-names></name><name><surname>Tsai</surname><given-names>ML</given-names></name><name><surname>Dakhil</surname><given-names>CS</given-names></name><name><surname>Stella</surname><given-names>P</given-names></name><name><surname>Shen</surname><given-names>V</given-names></name><etal/></person-group><article-title>LBA83 - Final efficacy results from B-F1RST, a prospective phase II trial evaluating blood-based tumour mutational burden (bTMB) as a predictive biomarker for atezolizumab (atezo) in 1L non-small cell lung cancer (NSCLC)</article-title><source>Ann Oncol</source><volume>30</volume><fpage>v919</fpage><lpage>v920</lpage><year>2019</year></element-citation></ref>
<ref id="b8-MCO-20-4-02730"><label>8</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Mezquita</surname><given-names>L</given-names></name><name><surname>Auclin</surname><given-names>E</given-names></name><name><surname>Ferrara</surname><given-names>R</given-names></name><name><surname>Charrier</surname><given-names>M</given-names></name><name><surname>Remon</surname><given-names>J</given-names></name><name><surname>Planchard</surname><given-names>D</given-names></name><name><surname>Ponce</surname><given-names>S</given-names></name><name><surname>Ares</surname><given-names>LP</given-names></name><name><surname>Leroy</surname><given-names>L</given-names></name><name><surname>Audigier-Valette</surname><given-names>C</given-names></name><etal/></person-group><article-title>Association of the lung immune prognostic index with immune checkpoint inhibitor outcomes in patients with advanced non-small cell lung cancer</article-title><source>JAMA Oncol</source><volume>4</volume><fpage>351</fpage><lpage>357</lpage><year>2018</year><pub-id pub-id-type="pmid">29327044</pub-id><pub-id pub-id-type="doi">10.1001/jamaoncol.2017.4771</pub-id></element-citation></ref>
<ref id="b9-MCO-20-4-02730"><label>9</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Mountzios</surname><given-names>G</given-names></name><name><surname>Samantas</surname><given-names>E</given-names></name><name><surname>Senghas</surname><given-names>K</given-names></name><name><surname>Zervas</surname><given-names>E</given-names></name><name><surname>Krisam</surname><given-names>J</given-names></name><name><surname>Samitas</surname><given-names>K</given-names></name><name><surname>Bozorgmehr</surname><given-names>F</given-names></name><name><surname>Kuon</surname><given-names>J</given-names></name><name><surname>Agelaki</surname><given-names>S</given-names></name><name><surname>Baka</surname><given-names>S</given-names></name><etal/></person-group><article-title>Association of the advanced lung cancer inflammation index (ALI) with immune checkpoint inhibitor efficacy in patients with advanced non-small-cell lung cancer</article-title><source>ESMO Open</source><volume>6</volume><issue>100254</issue><year>2021</year><pub-id pub-id-type="pmid">34481329</pub-id><pub-id pub-id-type="doi">10.1016/j.esmoop.2021.100254</pub-id></element-citation></ref>
<ref id="b10-MCO-20-4-02730"><label>10</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Corbeau</surname><given-names>I</given-names></name><name><surname>Jacot</surname><given-names>W</given-names></name><name><surname>Guiu</surname><given-names>S</given-names></name></person-group><article-title>Neutrophil to lymphocyte ratio as prognostic and predictive factor in breast cancer patients: A systematic review</article-title><source>Cancers (Basel)</source><volume>12</volume><issue>958</issue><year>2020</year><pub-id pub-id-type="pmid">32295078</pub-id><pub-id pub-id-type="doi">10.3390/cancers12040958</pub-id></element-citation></ref>
<ref id="b11-MCO-20-4-02730"><label>11</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Li</surname><given-names>Y</given-names></name><name><surname>Zhang</surname><given-names>Z</given-names></name><name><surname>Hu</surname><given-names>Y</given-names></name><name><surname>Yan</surname><given-names>X</given-names></name><name><surname>Song</surname><given-names>Q</given-names></name><name><surname>Wang</surname><given-names>G</given-names></name><name><surname>Chen</surname><given-names>R</given-names></name><name><surname>Jiao</surname><given-names>S</given-names></name><name><surname>Wang</surname><given-names>J</given-names></name></person-group><article-title>Pretreatment neutrophil-to-lymphocyte ratio (NLR) may predict the outcomes of advanced non-small-cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs)</article-title><source>Front Oncol</source><volume>10</volume><issue>654</issue><year>2020</year><pub-id pub-id-type="pmid">32656072</pub-id><pub-id pub-id-type="doi">10.3389/fonc.2020.00654</pub-id></element-citation></ref>
<ref id="b12-MCO-20-4-02730"><label>12</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Diem</surname><given-names>S</given-names></name><name><surname>Schmid</surname><given-names>S</given-names></name><name><surname>Krapf</surname><given-names>M</given-names></name><name><surname>Flatz</surname><given-names>L</given-names></name><name><surname>Born</surname><given-names>D</given-names></name><name><surname>Jochum</surname><given-names>W</given-names></name><name><surname>Templeton</surname><given-names>AJ</given-names></name><name><surname>Fr&#x00FC;h</surname><given-names>M</given-names></name></person-group><article-title>Neutrophil-to-Lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) as prognostic markers in patients with non-small cell lung cancer (NSCLC) treated with nivolumab</article-title><source>Lung Cancer</source><volume>111</volume><fpage>176</fpage><lpage>181</lpage><year>2017</year><pub-id pub-id-type="pmid">28838390</pub-id><pub-id pub-id-type="doi">10.1016/j.lungcan.2017.07.024</pub-id></element-citation></ref>
<ref id="b13-MCO-20-4-02730"><label>13</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Banna</surname><given-names>GL</given-names></name><name><surname>Cortellini</surname><given-names>A</given-names></name><name><surname>Cortinovis</surname><given-names>DL</given-names></name><name><surname>Tiseo</surname><given-names>M</given-names></name><name><surname>Aerts</surname><given-names>JGJV</given-names></name><name><surname>Barbieri</surname><given-names>F</given-names></name><name><surname>Giusti</surname><given-names>R</given-names></name><name><surname>Bria</surname><given-names>E</given-names></name><name><surname>Grossi</surname><given-names>F</given-names></name><name><surname>Pizzutilo</surname><given-names>P</given-names></name><etal/></person-group><article-title>The lung immuno-oncology prognostic score (LIPS-3): A prognostic classification of patients receiving first-line pembrolizumab for PD-L1 &#x2265;50&#x0025; advanced non-small-cell lung cancer</article-title><source>ESMO Open</source><volume>6</volume><issue>100078</issue><year>2021</year><pub-id pub-id-type="pmid">33735802</pub-id><pub-id pub-id-type="doi">10.1016/j.esmoop.2021.100078</pub-id></element-citation></ref>
<ref id="b14-MCO-20-4-02730"><label>14</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Amin</surname><given-names>MB</given-names></name><name><surname>Greene</surname><given-names>FL</given-names></name><name><surname>Edge</surname><given-names>SB</given-names></name><name><surname>Compton</surname><given-names>CC</given-names></name><name><surname>Gershenwald</surname><given-names>JE</given-names></name><name><surname>Brookland</surname><given-names>RK</given-names></name><name><surname>Meyer</surname><given-names>L</given-names></name><name><surname>Gress</surname><given-names>DM</given-names></name><name><surname>Byrd</surname><given-names>DR</given-names></name><name><surname>Winchester</surname><given-names>DP</given-names></name></person-group><article-title>The eighth edition AJCC cancer staging manual: Continuing to build a bridge from a population-based to a more &#x2018;personalized&#x2019; approach to cancer staging</article-title><source>CA Cancer J</source><volume>67</volume><fpage>93</fpage><lpage>99</lpage><year>2017</year><pub-id pub-id-type="pmid">28094848</pub-id><pub-id pub-id-type="doi">10.3322/caac.21388</pub-id></element-citation></ref>
<ref id="b15-MCO-20-4-02730"><label>15</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Seymour</surname><given-names>L</given-names></name><name><surname>Bogaerts</surname><given-names>J</given-names></name><name><surname>Perrone</surname><given-names>A</given-names></name><name><surname>Ford</surname><given-names>R</given-names></name><name><surname>Schwartz</surname><given-names>LH</given-names></name><name><surname>Mandrekar</surname><given-names>S</given-names></name><name><surname>Lin</surname><given-names>NU</given-names></name><name><surname>Liti&#x00E8;re</surname><given-names>S</given-names></name><name><surname>Dancey</surname><given-names>J</given-names></name><name><surname>Chen</surname><given-names>A</given-names></name><etal/></person-group><article-title>iRECIST: Guidelines for response criteria for use in trials testing immunotherapeutics</article-title><source>Lancet Oncol</source><volume>18</volume><fpage>e143</fpage><lpage>e152</lpage><year>2017</year><pub-id pub-id-type="pmid">28271869</pub-id><pub-id pub-id-type="doi">10.1016/S1470-2045(17)30074-8</pub-id></element-citation></ref>
<ref id="b16-MCO-20-4-02730"><label>16</label><element-citation publication-type="journal"><comment>US Department of Health and Human Services. Common Terminology Criteria for Adverse Events (CTCAE) Version 5. <ext-link ext-link-type="uri" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://ctep.cancer.gov/protocoldevelopment/electronic_applications/docs/ctcae_v5_quick_reference_5x7.pdf">https://ctep.cancer.gov/protocoldevelopment/electronic_applications/docs/ctcae_v5_quick_reference_5x7.pdf</ext-link>.</comment></element-citation></ref>
<ref id="b17-MCO-20-4-02730"><label>17</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Borghaei</surname><given-names>H</given-names></name><name><surname>Paz-Ares</surname><given-names>L</given-names></name><name><surname>Horn</surname><given-names>L</given-names></name><name><surname>Spigel</surname><given-names>DR</given-names></name><name><surname>Steins</surname><given-names>M</given-names></name><name><surname>Ready</surname><given-names>NE</given-names></name><name><surname>Chow</surname><given-names>LQ</given-names></name><name><surname>Vokes</surname><given-names>EE</given-names></name><name><surname>Felip</surname><given-names>E</given-names></name><name><surname>Holgado</surname><given-names>E</given-names></name><etal/></person-group><article-title>Nivolumab versus Docetaxel in advanced Nonsquamous non-small-cell lung cancer</article-title><source>N Engl J Med</source><volume>373</volume><fpage>1627</fpage><lpage>1639</lpage><year>2015</year><pub-id pub-id-type="pmid">26412456</pub-id><pub-id pub-id-type="doi">10.1056/NEJMoa1507643</pub-id></element-citation></ref>
<ref id="b18-MCO-20-4-02730"><label>18</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Mazieres</surname><given-names>J</given-names></name><name><surname>Rittmeyer</surname><given-names>A</given-names></name><name><surname>Gadgeel</surname><given-names>S</given-names></name><name><surname>Hida</surname><given-names>T</given-names></name><name><surname>Gandara</surname><given-names>DR</given-names></name><name><surname>Cortinovis</surname><given-names>DL</given-names></name><name><surname>Barlesi</surname><given-names>F</given-names></name><name><surname>Yu</surname><given-names>W</given-names></name><name><surname>Matheny</surname><given-names>C</given-names></name><name><surname>Ballinger</surname><given-names>M</given-names></name><name><surname>Park</surname><given-names>K</given-names></name></person-group><article-title>Atezolizumab Versus docetaxel in pretreated patients with NSCLC: Final results from the randomized phase 2 POPLAR and phase 3 OAK clinical trials</article-title><source>J Thorac Oncol</source><volume>16</volume><fpage>140</fpage><lpage>150</lpage><year>2021</year><pub-id pub-id-type="pmid">33166718</pub-id><pub-id pub-id-type="doi">10.1016/j.jtho.2020.09.022</pub-id></element-citation></ref>
<ref id="b19-MCO-20-4-02730"><label>19</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Kim</surname><given-names>J</given-names></name><name><surname>Cho</surname><given-names>J</given-names></name><name><surname>Lee</surname><given-names>MH</given-names></name><name><surname>Lim</surname><given-names>JH</given-names></name></person-group><article-title>Relative efficacy of checkpoint inhibitors for advanced NSCLC according to programmed death-ligand-1 expression: A systematic review and network meta-analysis</article-title><source>Sci Rep</source><volume>8</volume><issue>11738</issue><year>2018</year><pub-id pub-id-type="pmid">30082893</pub-id><pub-id pub-id-type="doi">10.1038/s41598-018-30277-0</pub-id></element-citation></ref>
<ref id="b20-MCO-20-4-02730"><label>20</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Prelaj</surname><given-names>A</given-names></name><name><surname>Rebuzzi</surname><given-names>SE</given-names></name><name><surname>Pizzutilo</surname><given-names>P</given-names></name><name><surname>Bilancia</surname><given-names>M</given-names></name><name><surname>Montrone</surname><given-names>M</given-names></name><name><surname>Pesola</surname><given-names>F</given-names></name><name><surname>Longo</surname><given-names>V</given-names></name><name><surname>Del Bene</surname><given-names>G</given-names></name><name><surname>Lapadula</surname><given-names>V</given-names></name><name><surname>Cassano</surname><given-names>F</given-names></name><etal/></person-group><article-title>EPSILoN: A prognostic score using clinical and blood biomarkers in advanced non-small-cell lung cancer treated with immunotherapy</article-title><source>Clin Lung Cancer</source><volume>21</volume><fpage>365</fpage><lpage>377.e5</lpage><year>2020</year><pub-id pub-id-type="pmid">32245624</pub-id><pub-id pub-id-type="doi">10.1016/j.cllc.2019.11.017</pub-id></element-citation></ref>
<ref id="b21-MCO-20-4-02730"><label>21</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Rounis</surname><given-names>K</given-names></name><name><surname>Makrakis</surname><given-names>D</given-names></name><name><surname>Papadaki</surname><given-names>C</given-names></name><name><surname>Monastirioti</surname><given-names>A</given-names></name><name><surname>Vamvakas</surname><given-names>L</given-names></name><name><surname>Kalbakis</surname><given-names>K</given-names></name><name><surname>Gourlia</surname><given-names>K</given-names></name><name><surname>Xanthopoulos</surname><given-names>I</given-names></name><name><surname>Tsamardinos</surname><given-names>I</given-names></name><name><surname>Mavroudis</surname><given-names>D</given-names></name><name><surname>Agelaki</surname><given-names>S</given-names></name></person-group><article-title>Prediction of outcome in patients with non-small cell lung cancer treated with second line PD-1/PDL-1 inhibitors based on clinical parameters: Results from a prospective, single institution study</article-title><source>PLoS One</source><volume>16</volume><issue>e0252537</issue><year>2021</year><pub-id pub-id-type="pmid">34061904</pub-id><pub-id pub-id-type="doi">10.1371/journal.pone.0252537</pub-id></element-citation></ref>
<ref id="b22-MCO-20-4-02730"><label>22</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Maugeais</surname><given-names>M</given-names></name><name><surname>P&#x00E9;ron</surname><given-names>J</given-names></name><name><surname>Dalle</surname><given-names>S</given-names></name><name><surname>Boespflug</surname><given-names>A</given-names></name><name><surname>Duruissaux</surname><given-names>M</given-names></name><name><surname>Corbaux</surname><given-names>P</given-names></name><name><surname>Reverdy</surname><given-names>T</given-names></name><name><surname>Sahin</surname><given-names>G</given-names></name><name><surname>Rabier</surname><given-names>A</given-names></name><name><surname>Lopez</surname><given-names>J</given-names></name><etal/></person-group><article-title>Impact of liver metastases and number of metastatic sites on immune-checkpoint inhibitors efficacy in patients with different solid tumors: A retrospective study</article-title><source>Biomedicines</source><volume>29</volume><issue>83</issue><year>2022</year><pub-id pub-id-type="pmid">36672591</pub-id><pub-id pub-id-type="doi">10.3390/biomedicines11010083</pub-id></element-citation></ref>
<ref id="b23-MCO-20-4-02730"><label>23</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Xia</surname><given-names>H</given-names></name><name><surname>Zhang</surname><given-names>W</given-names></name><name><surname>Zhang</surname><given-names>Y</given-names></name><name><surname>Shang</surname><given-names>X</given-names></name><name><surname>Liu</surname><given-names>Y</given-names></name><name><surname>Wang</surname><given-names>X</given-names></name></person-group><article-title>Liver metastases and the efficacy of immune checkpoint inhibitors in advanced lung cancer: A systematic review and meta-analysis</article-title><source>Front Oncol</source><volume>12</volume><issue>978069</issue><year>2022</year><pub-id pub-id-type="pmid">36330494</pub-id><pub-id pub-id-type="doi">10.3389/fonc.2022.978069</pub-id></element-citation></ref>
<ref id="b24-MCO-20-4-02730"><label>24</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Vaddepally</surname><given-names>R</given-names></name><name><surname>Doddamani</surname><given-names>R</given-names></name><name><surname>Sodavarapu</surname><given-names>S</given-names></name><name><surname>Madam</surname><given-names>NR</given-names></name><name><surname>Katkar</surname><given-names>R</given-names></name><name><surname>Kutadi</surname><given-names>AP</given-names></name><name><surname>Mathew</surname><given-names>N</given-names></name><name><surname>Garje</surname><given-names>R</given-names></name><name><surname>Chandra</surname><given-names>AB</given-names></name></person-group><article-title>Review of immune-related adverse events (irAEs) in non-small-cell lung cancer (NSCLC)-their incidence, management, multiorgan irAEs, and rechallenge</article-title><source>Biomedicines</source><volume>10</volume><issue>790</issue><year>2022</year><pub-id pub-id-type="pmid">35453540</pub-id><pub-id pub-id-type="doi">10.3390/biomedicines10040790</pub-id></element-citation></ref>
<ref id="b25-MCO-20-4-02730"><label>25</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Grangeon</surname><given-names>M</given-names></name><name><surname>Tomasini</surname><given-names>P</given-names></name><name><surname>Chaleat</surname><given-names>S</given-names></name><name><surname>Jeanson</surname><given-names>A</given-names></name><name><surname>Souquet-Bressand</surname><given-names>M</given-names></name><name><surname>Khobta</surname><given-names>N</given-names></name><name><surname>Bermudez</surname><given-names>J</given-names></name><name><surname>Trigui</surname><given-names>Y</given-names></name><name><surname>Greillier</surname><given-names>L</given-names></name><name><surname>Blanchon</surname><given-names>M</given-names></name><etal/></person-group><article-title>Association between immune-related adverse events and efficacy of immune checkpoint inhibitors in non-small-cell lung cancer</article-title><source>Clin Lung Cancer</source><volume>20</volume><fpage>201</fpage><lpage>207</lpage><year>2019</year><pub-id pub-id-type="pmid">30442524</pub-id><pub-id pub-id-type="doi">10.1016/j.cllc.2018.10.002</pub-id></element-citation></ref>
<ref id="b26-MCO-20-4-02730"><label>26</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Okada</surname><given-names>N</given-names></name><name><surname>Kawazoe</surname><given-names>H</given-names></name><name><surname>Takechi</surname><given-names>K</given-names></name><name><surname>Matsudate</surname><given-names>Y</given-names></name><name><surname>Utsunomiya</surname><given-names>R</given-names></name><name><surname>Zamami</surname><given-names>Y</given-names></name><name><surname>Goda</surname><given-names>M</given-names></name><name><surname>Imanishi</surname><given-names>M</given-names></name><name><surname>Chuma</surname><given-names>M</given-names></name><name><surname>Hidaka</surname><given-names>N</given-names></name><etal/></person-group><article-title>Association between immune-related adverse events and clinical efficacy in patients with melanoma treated with Nivolumab: A multicenter retrospective study</article-title><source>Clin Ther</source><volume>41</volume><fpage>59</fpage><lpage>67</lpage><year>2019</year><pub-id pub-id-type="pmid">30528047</pub-id><pub-id pub-id-type="doi">10.1016/j.clinthera.2018.11.004</pub-id></element-citation></ref>
<ref id="b27-MCO-20-4-02730"><label>27</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>G&#x00E4;rtner</surname><given-names>F</given-names></name><name><surname>A&#x00DF;mus</surname><given-names>J</given-names></name><name><surname>Fl&#x00F8;tten</surname><given-names>&#x00D8;</given-names></name><name><surname>Ramnefjell</surname><given-names>MP</given-names></name><name><surname>Aanerud</surname><given-names>M</given-names></name></person-group><article-title>Characteristics and survival of patients with non-small cell lung cancer treated with immune-checkpoint inhibitors in the real-world: Experiences from Bergen, Norway</article-title><source>Acta Oncol (Madr)</source><volume>61</volume><fpage>814</fpage><lpage>818</lpage><year>2022</year><pub-id pub-id-type="pmid">35481424</pub-id><pub-id pub-id-type="doi">10.1080/0284186X.2022.2068969</pub-id></element-citation></ref>
<ref id="b28-MCO-20-4-02730"><label>28</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Takeuchi</surname><given-names>E</given-names></name><name><surname>Kondo</surname><given-names>K</given-names></name><name><surname>Okano</surname><given-names>Y</given-names></name><name><surname>Kunishige</surname><given-names>M</given-names></name><name><surname>Kondo</surname><given-names>Y</given-names></name><name><surname>Kadota</surname><given-names>N</given-names></name><name><surname>Machida</surname><given-names>H</given-names></name><name><surname>Hatakeyama</surname><given-names>N</given-names></name><name><surname>Naruse</surname><given-names>K</given-names></name><name><surname>Ogino</surname><given-names>H</given-names></name><etal/></person-group><article-title>Early mortality factors in immune checkpoint inhibitor monotherapy for advanced or metastatic non-small cell lung cancer</article-title><source>J Cancer Res Clin Oncol</source><volume>149</volume><fpage>3139</fpage><lpage>3147</lpage><year>2023</year><pub-id pub-id-type="pmid">35871700</pub-id><pub-id pub-id-type="doi">10.1007/s00432-022-04215-7</pub-id></element-citation></ref>
<ref id="b29-MCO-20-4-02730"><label>29</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Corke</surname><given-names>LK</given-names></name><name><surname>Li</surname><given-names>JJN</given-names></name><name><surname>Leighl</surname><given-names>NB</given-names></name><name><surname>Eng</surname><given-names>L</given-names></name></person-group><article-title>Tobacco use and response to immune checkpoint inhibitor therapy in non-small cell lung cancer</article-title><source>Curr Oncol</source><volume>29</volume><fpage>6260</fpage><lpage>6276</lpage><year>2022</year><pub-id pub-id-type="pmid">36135061</pub-id><pub-id pub-id-type="doi">10.3390/curroncol29090492</pub-id></element-citation></ref>
<ref id="b30-MCO-20-4-02730"><label>30</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Zhao</surname><given-names>W</given-names></name><name><surname>Jiang</surname><given-names>W</given-names></name><name><surname>Wang</surname><given-names>H</given-names></name><name><surname>He</surname><given-names>J</given-names></name><name><surname>Su</surname><given-names>C</given-names></name><name><surname>Yu</surname><given-names>Q</given-names></name></person-group><article-title>Impact of smoking history on response to immunotherapy in non-small-cell lung cancer: A systematic review and meta-analysis</article-title><source>Front Oncol</source><volume>11</volume><issue>703143</issue><year>2021</year><pub-id pub-id-type="pmid">34497760</pub-id><pub-id pub-id-type="doi">10.3389/fonc.2021.703143</pub-id></element-citation></ref>
<ref id="b31-MCO-20-4-02730"><label>31</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Wang</surname><given-names>X</given-names></name><name><surname>Ricciuti</surname><given-names>B</given-names></name><name><surname>Alessi</surname><given-names>JV</given-names></name><name><surname>Nguyen</surname><given-names>T</given-names></name><name><surname>Awad</surname><given-names>MM</given-names></name><name><surname>Lin</surname><given-names>X</given-names></name><name><surname>Johnson</surname><given-names>BE</given-names></name><name><surname>Christiani</surname><given-names>DC</given-names></name></person-group><article-title>Smoking history as a potential predictor of immune checkpoint inhibitor efficacy in metastatic non-small cell lung cancer</article-title><source>J Natl Cancer Inst</source><volume>113</volume><fpage>1761</fpage><lpage>1769</lpage><year>2021</year><pub-id pub-id-type="pmid">34115098</pub-id><pub-id pub-id-type="doi">10.1093/jnci/djab116</pub-id></element-citation></ref>
<ref id="b32-MCO-20-4-02730"><label>32</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Popat</surname><given-names>S</given-names></name><name><surname>Liu</surname><given-names>SV</given-names></name><name><surname>Scheuer</surname><given-names>N</given-names></name><name><surname>Gupta</surname><given-names>A</given-names></name><name><surname>Hsu</surname><given-names>GG</given-names></name><name><surname>Ramagopalan</surname><given-names>SV</given-names></name><name><surname>Griesinger</surname><given-names>F</given-names></name><name><surname>Subbiah</surname><given-names>V</given-names></name></person-group><article-title>Association between smoking history and overall survival in patients receiving Pembrolizumab for first-line treatment of advanced non-small cell lung cancer</article-title><source>JAMA Netw Open</source><volume>5</volume><issue>e2214046</issue><year>2022</year><pub-id pub-id-type="pmid">35612853</pub-id><pub-id pub-id-type="doi">10.1001/jamanetworkopen.2022.14046</pub-id></element-citation></ref>
<ref id="b33-MCO-20-4-02730"><label>33</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Cedr&#x00E9;s</surname><given-names>S</given-names></name><name><surname>Torrejon</surname><given-names>D</given-names></name><name><surname>Mart&#x00ED;nez</surname><given-names>A</given-names></name><name><surname>Martinez</surname><given-names>P</given-names></name><name><surname>Navarro</surname><given-names>A</given-names></name><name><surname>Zamora</surname><given-names>E</given-names></name><name><surname>Mulet-Margalef</surname><given-names>N</given-names></name><name><surname>Felip</surname><given-names>E</given-names></name></person-group><article-title>Neutrophil to lymphocyte ratio (NLR) as an indicator of poor prognosis in stage IV non-small cell lung cancer</article-title><source>Clin Transl Oncol</source><volume>14</volume><fpage>864</fpage><lpage>869</lpage><year>2012</year><pub-id pub-id-type="pmid">22855161</pub-id><pub-id pub-id-type="doi">10.1007/s12094-012-0872-5</pub-id></element-citation></ref>
<ref id="b34-MCO-20-4-02730"><label>34</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Raskov</surname><given-names>H</given-names></name><name><surname>Orhan</surname><given-names>A</given-names></name><name><surname>Gaggar</surname><given-names>S</given-names></name><name><surname>G&#x00F6;genur</surname><given-names>I</given-names></name></person-group><article-title>Neutrophils and polymorphonuclear myeloid-derived suppressor cells: An emerging battleground in cancer therapy</article-title><source>Oncogenesis</source><volume>11</volume><issue>22</issue><year>2022</year><pub-id pub-id-type="pmid">35504900</pub-id><pub-id pub-id-type="doi">10.1038/s41389-022-00398-3</pub-id></element-citation></ref>
<ref id="b35-MCO-20-4-02730"><label>35</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Peng</surname><given-names>B</given-names></name><name><surname>Wang</surname><given-names>YH</given-names></name><name><surname>Liu</surname><given-names>YM</given-names></name><name><surname>Ma</surname><given-names>LX</given-names></name></person-group><article-title>Prognostic significance of the neutrophil to lymphocyte ratio in patients with non-small cell lung cancer: A systemic review and meta-analysis</article-title><source>Int J Clin Exp Med</source><volume>8</volume><fpage>3098</fpage><lpage>3106</lpage><year>2015</year><pub-id pub-id-type="pmid">26064198</pub-id></element-citation></ref>
<ref id="b36-MCO-20-4-02730"><label>36</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Cao</surname><given-names>D</given-names></name><name><surname>Xu</surname><given-names>H</given-names></name><name><surname>Xu</surname><given-names>X</given-names></name><name><surname>Guo</surname><given-names>T</given-names></name><name><surname>Ge</surname><given-names>W</given-names></name></person-group><article-title>A reliable and feasible way to predict the benefits of Nivolumab in patients with non-small cell lung cancer: A pooled analysis of 14 retrospective studies</article-title><source>Oncoimmunology</source><volume>7</volume><issue>e1507262</issue><year>2018</year><pub-id pub-id-type="pmid">30377569</pub-id><pub-id pub-id-type="doi">10.1080/2162402X.2018.1507262</pub-id></element-citation></ref>
<ref id="b37-MCO-20-4-02730"><label>37</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Suh</surname><given-names>KJ</given-names></name><name><surname>Kim</surname><given-names>SH</given-names></name><name><surname>Kim</surname><given-names>YJ</given-names></name><name><surname>Kim</surname><given-names>M</given-names></name><name><surname>Keam</surname><given-names>B</given-names></name><name><surname>Kim</surname><given-names>TM</given-names></name><name><surname>Kim</surname><given-names>DW</given-names></name><name><surname>Heo</surname><given-names>DS</given-names></name><name><surname>Lee</surname><given-names>JS</given-names></name></person-group><article-title>Post-treatment neutrophil-to-lymphocyte ratio at week 6 is prognostic in patients with advanced non-small cell lung cancers treated with anti-PD-1 antibody</article-title><source>Cancer Immunol Immunother</source><volume>67</volume><fpage>459</fpage><lpage>470</lpage><year>2018</year><pub-id pub-id-type="pmid">29204702</pub-id><pub-id pub-id-type="doi">10.1007/s00262-017-2092-x</pub-id></element-citation></ref>
<ref id="b38-MCO-20-4-02730"><label>38</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Lim</surname><given-names>JU</given-names></name><name><surname>Kang</surname><given-names>HS</given-names></name><name><surname>Yeo</surname><given-names>CD</given-names></name><name><surname>Kim</surname><given-names>JS</given-names></name><name><surname>Park</surname><given-names>CK</given-names></name><name><surname>Kim</surname><given-names>JW</given-names></name><name><surname>Kim</surname><given-names>SJ</given-names></name><name><surname>Lee</surname><given-names>SH</given-names></name></person-group><article-title>Predictability of early changes in derived neutrophil-to-lymphocyte ratio and neutrophil-to-lymphocyte ratio in patients with advanced non-small cell lung cancer treated with immune checkpoint inhibitors</article-title><source>J Thorac Dis</source><volume>13</volume><fpage>2824</fpage><lpage>2832</lpage><year>2021</year><pub-id pub-id-type="pmid">34164174</pub-id><pub-id pub-id-type="doi">10.21037/jtd-20-3416</pub-id></element-citation></ref>
<ref id="b39-MCO-20-4-02730"><label>39</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Simonelli</surname><given-names>M</given-names></name><name><surname>Calvo</surname><given-names>E</given-names></name><name><surname>Davar</surname><given-names>D</given-names></name><name><surname>Richards</surname><given-names>D</given-names></name><name><surname>Gutierrez</surname><given-names>M</given-names></name><name><surname>Garcia</surname><given-names>VM</given-names></name><name><surname>Marron</surname><given-names>T</given-names></name><name><surname>Rottey</surname><given-names>S</given-names></name><name><surname>Orcurto</surname><given-names>A</given-names></name><name><surname>Renouf</surname><given-names>DJ</given-names></name><etal/></person-group><article-title>200MO Anti-IL-8 BMS-986253 + nivolumab (NIVO) &#x00B1; ipilimumab (IPI) in patients (pts) with advanced cancer: Update of initial phase I results</article-title><source>Immuno-Oncology and Technology</source><volume>16</volume><issue>100311</issue><year>2022</year></element-citation></ref>
<ref id="b40-MCO-20-4-02730"><label>40</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Barlesi</surname><given-names>F</given-names></name><name><surname>Isambert</surname><given-names>N</given-names></name><name><surname>Felip</surname><given-names>E</given-names></name><name><surname>Cho</surname><given-names>BC</given-names></name><name><surname>Lee</surname><given-names>DH</given-names></name><name><surname>Peguero</surname><given-names>J</given-names></name><name><surname>Jerusalem</surname><given-names>G</given-names></name><name><surname>Penel</surname><given-names>N</given-names></name><name><surname>Saada-Bouzid</surname><given-names>E</given-names></name><name><surname>Garrido</surname><given-names>P</given-names></name><etal/></person-group><article-title>Bintrafusp Alfa, a Bifunctional fusion protein targeting TGF-&#x03B2; and PD-L1, in patients with non-small cell lung cancer resistant or refractory to immune checkpoint inhibitors</article-title><source>Oncologist</source><volume>28</volume><fpage>258</fpage><lpage>267</lpage><year>2023</year></element-citation></ref>
<ref id="b41-MCO-20-4-02730"><label>41</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Nadal</surname><given-names>E</given-names></name><name><surname>Saleh</surname><given-names>M</given-names></name><name><surname>Aix</surname><given-names>SP</given-names></name><name><surname>Ochoa-de-Olza</surname><given-names>M</given-names></name><name><surname>Patel</surname><given-names>SP</given-names></name><name><surname>Antonia</surname><given-names>S</given-names></name><name><surname>Zhao</surname><given-names>Y</given-names></name><name><surname>Gueorguieva</surname><given-names>I</given-names></name><name><surname>Man</surname><given-names>M</given-names></name><name><surname>Estrem</surname><given-names>ST</given-names></name><etal/></person-group><article-title>A phase Ib/II study of galunisertib in combination with nivolumab in solid tumors and non-small cell lung cancer</article-title><source>BMC Cancer</source><volume>23</volume><issue>708</issue><year>2023</year><pub-id pub-id-type="pmid">37507657</pub-id><pub-id pub-id-type="doi">10.1186/s12885-023-11153-1</pub-id></element-citation></ref>
<ref id="b42-MCO-20-4-02730"><label>42</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Park</surname><given-names>W</given-names></name><name><surname>Mezquita</surname><given-names>L</given-names></name><name><surname>Okabe</surname><given-names>N</given-names></name><name><surname>Chae</surname><given-names>YK</given-names></name><name><surname>Kwon</surname><given-names>D</given-names></name><name><surname>Saravia</surname><given-names>D</given-names></name><name><surname>Auclin</surname><given-names>E</given-names></name><name><surname>Planchard</surname><given-names>D</given-names></name><name><surname>Caramella</surname><given-names>C</given-names></name><name><surname>Ferrara</surname><given-names>R</given-names></name><etal/></person-group><article-title>Association of the prognostic model iSEND with PD-1/L1 monotherapy outcome in non-small-cell lung cancer</article-title><source>Br J Cancer</source><volume>122</volume><fpage>340</fpage><lpage>347</lpage><year>2020</year><pub-id pub-id-type="pmid">31761899</pub-id><pub-id pub-id-type="doi">10.1038/s41416-019-0643-y</pub-id></element-citation></ref>
<ref id="b43-MCO-20-4-02730"><label>43</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Valero</surname><given-names>C</given-names></name><name><surname>Lee</surname><given-names>M</given-names></name><name><surname>Hoen</surname><given-names>D</given-names></name><name><surname>Weiss</surname><given-names>K</given-names></name><name><surname>Kelly</surname><given-names>DW</given-names></name><name><surname>Adusumilli</surname><given-names>PS</given-names></name><name><surname>Paik</surname><given-names>PK</given-names></name><name><surname>Plitas</surname><given-names>G</given-names></name><name><surname>Ladanyi</surname><given-names>M</given-names></name><name><surname>Postow</surname><given-names>MA</given-names></name><etal/></person-group><article-title>Pretreatment neutrophil-to-lymphocyte ratio and mutational burden as biomarkers of tumor response to immune checkpoint inhibitors</article-title><source>Nat Commun</source><volume>12</volume><issue>729</issue><year>2021</year><pub-id pub-id-type="pmid">33526794</pub-id><pub-id pub-id-type="doi">10.1038/s41467-021-20935-9</pub-id></element-citation></ref>
</ref-list>
</back>
<floats-group>
<fig id="f1-MCO-20-4-02730" position="float">
<label>Figure 1</label>
<caption><p>Kaplan-Meier curves for PFS according to (A) ECOG PS, (B) smoking status, (C) liver metastases and (D) irAEs in patients with metastatic non-small cell lung cancer receiving second and subsequent lines of immunotherapy. PFS, progression-free survival; ECOG PS, Eastern Cooperative Oncology Group performance status; irAEs, immune-related adverse events.</p></caption>
<graphic xlink:href="mco-20-04-02730-g00.tif" />
</fig>
<fig id="f2-MCO-20-4-02730" position="float">
<label>Figure 2</label>
<caption><p>Kaplan-Meier curves for OS according to (A) ECOG PS, (B) smoking status, (C) liver metastases and (D) irAEs in patients with metastatic non-small cell lung cancer receiving second and subsequent lines of immunotherapy. OS, overall survival; ECOG PS, Eastern Cooperative Oncology Group performance status; irAEs, immune-related adverse events.</p></caption>
<graphic xlink:href="mco-20-04-02730-g01.tif" />
</fig>
<fig id="f3-MCO-20-4-02730" position="float">
<label>Figure 3</label>
<caption><p>Kaplan-Meier curves for PFS according to (A) PD-L1 expression, (B) baseline NLR, (C) NLR after two cycles and (D) NLR dynamic changes in patients with metastatic non-small cell lung cancer receiving second and subsequent lines of immune checkpoint inhibitors. PFS, progression-free survival; PD-L1, programmed cell death-ligand 1; NLR, neutrophil-to-lymphocyte ratio.</p></caption>
<graphic xlink:href="mco-20-04-02730-g02.tif" />
</fig>
<fig id="f4-MCO-20-4-02730" position="float">
<label>Figure 4</label>
<caption><p>Kaplan-Meier curves for OS according to (A) PD-L1 expression, (B) baseline NLR, (C) NLR after two cycles and (D) NLR dynamic changes in patients with metastatic non-small cell lung cancer receiving second and subsequent lines of immune checkpoint inhibitors. OS, overall survival; PD-L1, programmed cell death-ligand 1; NLR, neutrophil-to-lymphocyte ratio.</p></caption>
<graphic xlink:href="mco-20-04-02730-g03.tif" />
</fig>
<fig id="f5-MCO-20-4-02730" position="float">
<label>Figure 5</label>
<caption><p>Kaplan-Meier curves for (A) PFS and (B) OS according to the NSE score in patients with metastatic non-small cell lung cancer receiving second and subsequent lines of immune checkpoint inhibitors. (C) PFS and (D) OS according to the NSE groups in the chemotherapy cohort. PFS, progression-free survival; OS, overall survival; NSE, NLR, smoking status, ECOG.</p></caption>
<graphic xlink:href="mco-20-04-02730-g04.tif" />
</fig>
<table-wrap id="tI-MCO-20-4-02730" position="float">
<label>Table I</label>
<caption><p>Main baseline characteristics of patients receiving ICIs and chemotherapy.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="middle">Characteristics</th>
<th align="center" valign="middle">ICIs cohort (n=181)</th>
<th align="center" valign="middle">Comparison cohort (n=63)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Sex, n (&#x0025;)</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Male</td>
<td align="center" valign="middle">129 (71.3)</td>
<td align="center" valign="middle">43 (68.3)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Female</td>
<td align="center" valign="middle">52 (28.7)</td>
<td align="center" valign="middle">20 (31.7)</td>
</tr>
<tr>
<td align="left" valign="middle">Age (years), median (IQR), n (&#x0025;)</td>
<td align="center" valign="middle">65 (57-72)</td>
<td align="center" valign="middle">63 (54-70)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x003C;65</td>
<td align="center" valign="middle">98 (54.1)</td>
<td align="center" valign="middle">37 (58.7)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x2265; 65</td>
<td align="center" valign="middle">83 (45.9)</td>
<td align="center" valign="middle">26 (41.3)</td>
</tr>
<tr>
<td align="left" valign="middle">ECOG PS</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;0-1</td>
<td align="center" valign="middle">147 (81.2)</td>
<td align="center" valign="middle">53 (84.1)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x2265;2</td>
<td align="center" valign="middle">34 (18.8)</td>
<td align="center" valign="middle">10 (15.9)</td>
</tr>
<tr>
<td align="left" valign="middle">Smoking status</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Ever smoking</td>
<td align="center" valign="middle">116 (64.1)</td>
<td align="center" valign="middle">38 (60.3)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Never smoking</td>
<td align="center" valign="middle">65 (35.9)</td>
<td align="center" valign="middle">25 (39.7)</td>
</tr>
<tr>
<td align="left" valign="middle">Histological type, n (&#x0025;)</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Adenocarcinoma</td>
<td align="center" valign="middle">95 (52.5)</td>
<td align="center" valign="middle">26 (41.3)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Squamous cell carcinoma</td>
<td align="center" valign="middle">82 (45.3)</td>
<td align="center" valign="middle">36 (57.1)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Other NSCLCs</td>
<td align="center" valign="middle">4 (2.2)</td>
<td align="center" valign="middle">1 (1.6)</td>
</tr>
<tr>
<td align="left" valign="middle">PD-L1 IHC expression</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x003C;1&#x0025;</td>
<td align="center" valign="middle">30 (16.6)</td>
<td align="center" valign="middle">0 (0.0)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x2265;1-49&#x0025;</td>
<td align="center" valign="middle">66 (36.5)</td>
<td align="center" valign="middle">0 (0.0)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x2265;50&#x0025;</td>
<td align="center" valign="middle">18 (9.9)</td>
<td align="center" valign="middle">63 (100.0)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;No data</td>
<td align="center" valign="middle">67 (37.0)</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">Line of therapy, n (&#x0025;)</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;1</td>
<td align="center" valign="middle">0 (0.0)</td>
<td align="center" valign="middle">63 (100.0)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;2</td>
<td align="center" valign="middle">137 (74.7)</td>
<td align="center" valign="middle">0 (0.0)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x2265;3</td>
<td align="center" valign="middle">44 (24.3)</td>
<td align="center" valign="middle">0 (0.0)</td>
</tr>
<tr>
<td align="left" valign="middle">Type of therapy, n (&#x0025;)</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Nivolumab</td>
<td align="center" valign="middle">92 (50.8)</td>
<td align="center" valign="middle">0 (0.0)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Pembrolizumab</td>
<td align="center" valign="middle">76 (42.0)</td>
<td align="center" valign="middle">0 (0.0)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Atezolizumab</td>
<td align="center" valign="middle">13 (7.2)</td>
<td align="center" valign="middle">0 (0.0)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Platinum-based doublet</td>
<td align="center" valign="middle">0 (0.0)</td>
<td align="center" valign="middle">63 (100.0)</td>
</tr>
<tr>
<td align="left" valign="middle">ORR, n (&#x0025;)</td>
<td align="center" valign="middle">41(23)</td>
<td align="center" valign="middle">17(27)</td>
</tr>
<tr>
<td align="left" valign="middle">Median PFS, months (95&#x0025; CI)</td>
<td align="center" valign="middle">4.9 (4.2-5.6)</td>
<td align="center" valign="middle">4.6 (4.0-5.9)</td>
</tr>
<tr>
<td align="left" valign="middle">Median OS, months (95&#x0025; CI)</td>
<td align="center" valign="middle">13.7 (11.5-17.2)</td>
<td align="center" valign="middle">10.4 (8.9-14.2)</td>
</tr>
<tr>
<td align="left" valign="middle">Any irAEs, n (&#x0025;)</td>
<td align="center" valign="middle">71(39)</td>
<td align="center" valign="middle">0 (0.0)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Any grade &#x2265;3 irAE, n (&#x0025; of total irAEs)</td>
<td align="center" valign="middle">12(17)</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Thyroid dysfunction</td>
<td align="center" valign="middle">25(35)</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Skin reactions</td>
<td align="center" valign="middle">17(24)</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Pneumonitis</td>
<td align="center" valign="middle">8(11)</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Hepatitis</td>
<td align="center" valign="middle">6(8)</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>ICI, immune checkpoint inhibitor; IQR, interquartile range; ECOG PS, Eastern Cooperative Oncology Group performance status; NSCLC, non-small lung cell cancer; PD-L1, programmed cell death-ligand 1; IHC, immunohistochemical; ORR, objective response rate; PFS, progression-free survival; OS, overall survival; CI, confidence interval; irAEs, immune-related adverse events.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="tII-MCO-20-4-02730" position="float">
<label>Table II</label>
<caption><p>ORRs according to main characteristics in patients receiving ICIs.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="middle">Characteristics</th>
<th align="center" valign="middle">ORR, &#x0025; (N)</th>
<th align="center" valign="middle">P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Age (&#x003C;65 vs. &#x2265; 65)</td>
<td align="center" valign="middle">24 (24/98) vs. 20 (17/83)</td>
<td align="center" valign="middle">0.594</td>
</tr>
<tr>
<td align="left" valign="middle">Sex (male vs. female)</td>
<td align="center" valign="middle">24 (31/129) vs. 19 (10/52)</td>
<td align="center" valign="middle">0.560</td>
</tr>
<tr>
<td align="left" valign="middle">ECOG PS (0/1 vs. &#x2265;2)</td>
<td align="center" valign="middle">25 (37/147) vs. 12 (4/34)</td>
<td align="center" valign="middle">0.113</td>
</tr>
<tr>
<td align="left" valign="middle">Smoking (former/active vs. never)</td>
<td align="center" valign="middle">26 (30/116) vs. 17 (11/65)</td>
<td align="center" valign="middle">0.198</td>
</tr>
<tr>
<td align="left" valign="middle">Liver metastasis (no vs. yes)</td>
<td align="center" valign="middle">24 (36/153) vs. 14 (4/28)</td>
<td align="center" valign="middle">0.329</td>
</tr>
<tr>
<td align="left" valign="middle">Histology (non-squamous vs. squamous)</td>
<td align="center" valign="middle">26 (25/95) vs. 19 (16/86)</td>
<td align="center" valign="middle">0.286</td>
</tr>
<tr>
<td align="left" valign="middle">irAEs (yes vs. no)</td>
<td align="center" valign="middle">28 (20/71) vs. 19 (21/110)</td>
<td align="center" valign="middle">0.203</td>
</tr>
<tr>
<td align="left" valign="middle">NLR (&#x003C;4.3 vs. &#x2265;4.3)</td>
<td align="center" valign="middle">27 (34/124) vs. 12 (7/57)</td>
<td align="center" valign="middle">0.034</td>
</tr>
<tr>
<td align="left" valign="middle">NLR after two cycles (&#x003C;4.5 vs. &#x2265;4.5)</td>
<td align="center" valign="middle">27 (31/116) vs. 15 (10/65)</td>
<td align="center" valign="middle">0.098</td>
</tr>
<tr>
<td align="left" valign="middle">NLR dynamic changes (&#x003C;24&#x0025; vs. &#x2265;24&#x0025;)</td>
<td align="center" valign="middle">26 (28/106) vs. 19 (14/75)</td>
<td align="center" valign="middle">0.284</td>
</tr>
<tr>
<td align="left" valign="middle">NSE score</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">0.002</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Group 1</td>
<td align="center" valign="middle">35 (27/77)</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Group 2</td>
<td align="center" valign="middle">17 (11/66)</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;&#x00A0;&#x00A0;&#x00A0;&#x00A0;Group 3</td>
<td align="center" valign="middle">8 (3/38)</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">ORR, objective response rate; ICIs, immune checkpoint inhibitors; ECOG PS, Eastern Cooperative Oncology Group performance status; irAEs, immune-related adverse events; NLR, neutrophil-to-lymphocyte ratio; NSE, NLR, smoking status, ECOG.</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="tIII-MCO-20-4-02730" position="float">
<label>Table III</label>
<caption><p>Univariate and multivariate analyses for PFS using Cox proportional hazards regression model in ICIs cohort.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="middle">&#x00A0;</th>
<th align="center" valign="middle" colspan="2">Univariate analysis</th>
<th align="center" valign="middle" colspan="2">Multivariate analysis</th>
</tr>
<tr>
<th align="left" valign="middle">Characteristics</th>
<th align="center" valign="middle">HR (95&#x0025; CI)</th>
<th align="center" valign="middle">P-value</th>
<th align="center" valign="middle">HR (95&#x0025; CI)</th>
<th align="center" valign="middle">P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">PFS</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">Age</td>
<td align="center" valign="middle">1.00 (0.98-1.02)</td>
<td align="center" valign="middle">0.962</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">Sex (male vs. female)</td>
<td align="center" valign="middle">0.73 (0.49-1.19)</td>
<td align="center" valign="middle">0.249</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">BMI</td>
<td align="center" valign="middle">0.99 (0.94-1.03)</td>
<td align="center" valign="middle">0.605</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">ECOG PS (&#x2265;2 vs. 0/1)</td>
<td align="center" valign="middle">1.98 (1.30-2.93)</td>
<td align="center" valign="middle">0.001</td>
<td align="center" valign="middle">2.09 (1.09-4.07)</td>
<td align="center" valign="middle">0.028</td>
</tr>
<tr>
<td align="left" valign="middle">Smoking (never vs. former/active)</td>
<td align="center" valign="middle">1.91 (1.38-2.82)</td>
<td align="center" valign="middle">0.001</td>
<td align="center" valign="middle">3.53 (2.07-9.29)</td>
<td align="center" valign="middle">0.007</td>
</tr>
<tr>
<td align="left" valign="middle">Liver metastasis (yes vs. no)</td>
<td align="center" valign="middle">1.42 (1.07-2.31)</td>
<td align="center" valign="middle">0.026</td>
<td align="center" valign="middle">1.55 (0.92-2.54)</td>
<td align="center" valign="middle">0.083</td>
</tr>
<tr>
<td align="left" valign="middle">Brain metastasis (yes vs. no)</td>
<td align="center" valign="middle">0.89 (0.44-1.62)</td>
<td align="center" valign="middle">0.731</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">Bone metastasis (no vs. yes)</td>
<td align="center" valign="middle">0.91 (0.58-1.50)</td>
<td align="center" valign="middle">0.709</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">Metastatic sites (&#x2265; 2 vs. &#x003C;2)</td>
<td align="center" valign="middle">1.12 (0.76-1.65)</td>
<td align="center" valign="middle">0.419</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">Histology (squamous vs. adenocarcinoma)</td>
<td align="center" valign="middle">1.19 (0.84-1.72)</td>
<td align="center" valign="middle">0.333</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">Previous radiotherapy (no vs. yes)</td>
<td align="center" valign="middle">1.22 (0.69-2.34)</td>
<td align="center" valign="middle">0.519</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">Immunotherapy &#x005B;anti-PD-1 (pembrolizumab/nivolumab) vs. anti-PD-L1 (atezolizumab)&#x005D;</td>
<td align="center" valign="middle">1.09 (0.66-1.71)</td>
<td align="center" valign="middle">0.718</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">Line of therapy (2L vs. 3L+)</td>
<td align="center" valign="middle">1.28 (0.80-1.92)</td>
<td align="center" valign="middle">0.305</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">NLR (&#x2265;4.3 vs. &#x003C;4.3)</td>
<td align="center" valign="middle">4.79 (3.24-7.07)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
<td align="center" valign="middle">4.34 (2.65-7.03)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="middle">NLR after two cycles (&#x2265;4.5 vs. &#x003C;4.5)</td>
<td align="center" valign="middle">2.09 (1.43-3.01)</td>
<td align="center" valign="middle">0.0001</td>
<td align="center" valign="middle">1.27 (0.84-1.91)</td>
<td align="center" valign="middle">0.252</td>
</tr>
<tr>
<td align="left" valign="middle">NLR dynamic changes (&#x2265;24&#x0025; vs. &#x003C;24&#x0025;)</td>
<td align="center" valign="middle">1.23 (0.85-1.76)</td>
<td align="center" valign="middle">0.259</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">irAEs (no vs. yes)</td>
<td align="center" valign="middle">1.36 (0.95-1.97)</td>
<td align="center" valign="middle">0.099</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>PFS, progression-free survival; ICIs, immune checkpoint inhibitors; HR, hazard ratio; CI, confidence interval; BMI, body mass index; ECOG PS, Eastern Cooperative Oncology Group performance status; PD-L1, programmed cell death-ligand 1; NLR, neutrophil-to-lymphocyte ratio; irAEs, immune-related adverse events; NSE, NLR, smoking status.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="tIV-MCO-20-4-02730" position="float">
<label>Table IV</label>
<caption><p>Univariate and multivariate analyses for OS using Cox proportional hazards regression model in ICIs cohort.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="middle">&#x00A0;</th>
<th align="center" valign="middle" colspan="2">Univariate analysis</th>
<th align="center" valign="middle" colspan="2">Multivariate analysis</th>
</tr>
<tr>
<th align="left" valign="middle">Characteristics</th>
<th align="center" valign="middle">HR (95&#x0025; CI)</th>
<th align="center" valign="middle">P-value</th>
<th align="center" valign="middle">HR (95&#x0025; CI)</th>
<th align="center" valign="middle">P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">OS</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">Age</td>
<td align="center" valign="middle">1.01 (0.99-1.03)</td>
<td align="center" valign="middle">0.417</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">Sex (male vs. female)</td>
<td align="center" valign="middle">0.78 (0.52-1.18)</td>
<td align="center" valign="middle">0.234</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">BMI</td>
<td align="center" valign="middle">0.97 (0.92-1.02)</td>
<td align="center" valign="middle">0.218</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">ECOG PS (&#x2265;2 vs. 0/1)</td>
<td align="center" valign="middle">2.09 (1.35-3.16)</td>
<td align="center" valign="middle">0.001</td>
<td align="center" valign="middle">2.02 (1.06-3.91)</td>
<td align="center" valign="middle">0.035</td>
</tr>
<tr>
<td align="left" valign="middle">Smoking (never vs. former/active)</td>
<td align="center" valign="middle">1.82 (1.23-2.69)</td>
<td align="center" valign="middle">0.003</td>
<td align="center" valign="middle">1.80 (1.21-2.68)</td>
<td align="center" valign="middle">0.004</td>
</tr>
<tr>
<td align="left" valign="middle">Liver metastasis (yes vs. no)</td>
<td align="center" valign="middle">1.48 (0.88-2.36)</td>
<td align="center" valign="middle">0.119</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">Brain metastasis (yes vs. no)</td>
<td align="center" valign="middle">0.91 (0.43-1.69)</td>
<td align="center" valign="middle">0.780</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">Bone metastasis (no vs. yes)</td>
<td align="center" valign="middle">0.81 (0.50-1.37)</td>
<td align="center" valign="middle">0.407</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">Metastatic sites (&#x2265;2 vs. &#x003C;2)</td>
<td align="center" valign="middle">1.12 (0.76-1.65)</td>
<td align="center" valign="middle">0.559</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">Histology (squamous vs. adenocarcinoma)</td>
<td align="center" valign="middle">1.30 (0.73-2.59)</td>
<td align="center" valign="middle">0.409</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">Previous radiotherapy (no vs. yes)</td>
<td align="center" valign="middle">1.45 (0.79-2.98)</td>
<td align="center" valign="middle">0.266</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">Immunotherapy &#x005B;anti-PD-1 (pembrolizumab/nivolumab) vs. anti PD-L1 (atezolizumab)&#x005D;</td>
<td align="center" valign="middle">0.89 (0.49-1.50)</td>
<td align="center" valign="middle">0.629</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">Line of therapy (2L vs. 3L+)</td>
<td align="center" valign="middle">1.23 (0.72-1.98)</td>
<td align="center" valign="middle">0.419</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">-</td>
</tr>
<tr>
<td align="left" valign="middle">NLR baseline (&#x2265;4.3 vs. &#x003C;4.3)</td>
<td align="center" valign="middle">5.07 (3.58-8.09)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
<td align="center" valign="middle">4.89 (3.16-7.62)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="middle">NLR after two cycles (&#x2265;4.5 vs. &#x003C;4.5)</td>
<td align="center" valign="middle">2.67 (1.78-3.96)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
<td align="center" valign="middle">1.41 (0.58-2.93)</td>
<td align="center" valign="middle">0.398</td>
</tr>
<tr>
<td align="left" valign="middle">NLR dynamic changes (&#x2265;24&#x0025; vs. &#x003C;24&#x0025;)</td>
<td align="center" valign="middle">1.66 (1.11-2.46)</td>
<td align="center" valign="middle">0.012</td>
<td align="center" valign="middle">1.59 (0.97-2.63)</td>
<td align="center" valign="middle">0.064</td>
</tr>
<tr>
<td align="left" valign="middle">irAEs (no vs. yes)</td>
<td align="center" valign="middle">1.69 (1.14-2.54)</td>
<td align="center" valign="middle">0.011</td>
<td align="center" valign="middle">1.63 (0.91-2.82)</td>
<td align="center" valign="middle">0.088</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>OS, overall survival; ICIs, immune checkpoint inhibitors; HR, hazard ratio; CI, confidence interval; BMI, body mass index; ECOG PS, Eastern Cooperative Oncology Group performance status; PD-L1, programmed cell death-ligand 1; NLR, neutrophil-to-lymphocyte ratio; irAEs, immune-related adverse events.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="tV-MCO-20-4-02730" position="float">
<label>Table V</label>
<caption><p>NSE predictive scoring system and risk stratification.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="middle">Predictive factor</th>
<th align="center" valign="middle">Value</th>
<th align="center" valign="middle">Points</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">NLR at baseline</td>
<td align="center" valign="middle">&#x2265;4.3</td>
<td align="center" valign="middle">2</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">&#x003C;4.3</td>
<td align="center" valign="middle">0</td>
</tr>
<tr>
<td align="left" valign="middle">Smoking status</td>
<td align="center" valign="middle">Never</td>
<td align="center" valign="middle">1</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">Ever</td>
<td align="center" valign="middle">0</td>
</tr>
<tr>
<td align="left" valign="middle">ECOG PS</td>
<td align="center" valign="middle">&#x2265;2</td>
<td align="center" valign="middle">1</td>
</tr>
<tr>
<td align="left" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">0-1</td>
<td align="center" valign="middle">0</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>Predictive groups: Good (group 1), 0 points; intermediate (group 2), 1-2 points; and poor (group 3), &#x2265;3 points. NSE, NLR, smoking status, ECOG; NLR, neutrophil-to-lymphocyte ratio; ECOG PS, Eastern Cooperative Oncology Group performance status.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="tVI-MCO-20-4-02730" position="float">
<label>Table VI</label>
<caption><p>Multivariate analysis for PFS and OS according to NSE score groups.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="middle">&#x00A0;</th>
<th align="center" valign="middle" colspan="2">PFS</th>
<th align="center" valign="middle" colspan="2">OS</th>
</tr>
<tr>
<th align="left" valign="middle">NSE score</th>
<th align="center" valign="middle">HR (95&#x0025; CI)</th>
<th align="center" valign="middle">P-value</th>
<th align="center" valign="middle">HR (95&#x0025; CI)</th>
<th align="center" valign="middle">P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Group 1</td>
<td align="center" valign="middle">1 (Reference)</td>
<td align="center" valign="middle">&#x00A0;</td>
<td align="center" valign="middle">1 (Reference)</td>
<td align="center" valign="middle">&#x00A0;</td>
</tr>
<tr>
<td align="left" valign="middle">Group 2</td>
<td align="center" valign="middle">3.09 (1.94-4.99)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
<td align="center" valign="middle">2.61 (1.49-4.32)</td>
<td align="center" valign="middle">0.0003</td>
</tr>
<tr>
<td align="left" valign="middle">Group 3</td>
<td align="center" valign="middle">7.31 (3.95-11.68)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
<td align="center" valign="middle">6.99 (3.89-10.03)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>NSE, NLR, smoking status, ECOG; PFS, progression-free survival; OS, overall survival; HR, hazard ratio; CI, confidence interval.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="tVII-MCO-20-4-02730" position="float">
<label>Table VII</label>
<caption><p>Univariate analysis for PFS and OS using Cox proportional hazards regression model in a chemotherapy cohort.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="middle">&#x00A0;</th>
<th align="center" valign="middle" colspan="2">PFS</th>
<th align="center" valign="middle" colspan="2">OS</th>
</tr>
<tr>
<th align="left" valign="middle">Characteristics</th>
<th align="center" valign="middle">HR (95&#x0025; CI)</th>
<th align="center" valign="middle">P-value</th>
<th align="center" valign="middle">HR (95&#x0025; CI)</th>
<th align="center" valign="middle">P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Age</td>
<td align="center" valign="middle">1.09 (0.86-1.34)</td>
<td align="center" valign="middle">0.545</td>
<td align="center" valign="middle">1.04 (0.86-1.32)</td>
<td align="center" valign="middle">0.704</td>
</tr>
<tr>
<td align="left" valign="middle">Sex (male vs. female)</td>
<td align="center" valign="middle">1.15 (0.66-2.32)</td>
<td align="center" valign="middle">0.694</td>
<td align="center" valign="middle">1.09 (0.46-1.74)</td>
<td align="center" valign="middle">0.781</td>
</tr>
<tr>
<td align="left" valign="middle">ECOG PS (&#x2265;2 vs. 0/1)</td>
<td align="center" valign="middle">1.25 (0.85-1.75)</td>
<td align="center" valign="middle">0.232</td>
<td align="center" valign="middle">1.42 (0.90-1.81)</td>
<td align="center" valign="middle">0.131</td>
</tr>
<tr>
<td align="left" valign="middle">Smoking (never vs. former/active)</td>
<td align="center" valign="middle">0.74 (0.44-1.30)</td>
<td align="center" valign="middle">0.292</td>
<td align="center" valign="middle">0.77 (0.58-1.21)</td>
<td align="center" valign="middle">0.176</td>
</tr>
<tr>
<td align="left" valign="middle">Liver metastasis (yes vs. no)</td>
<td align="center" valign="middle">1.44 (0.70-2.94)</td>
<td align="center" valign="middle">0.319</td>
<td align="center" valign="middle">1.31 (0.68-2.98)</td>
<td align="center" valign="middle">0.476</td>
</tr>
<tr>
<td align="left" valign="middle">Bone metastasis (no vs. yes)</td>
<td align="center" valign="middle">0.78 (0.63-1.42)</td>
<td align="center" valign="middle">0.345</td>
<td align="center" valign="middle">0.64 (0.58-1.63)</td>
<td align="center" valign="middle">0.254</td>
</tr>
<tr>
<td align="left" valign="middle">Metastatic sites (&#x2265;2 vs. &#x003C;2)</td>
<td align="center" valign="middle">1.32 (0.81-1.86)</td>
<td align="center" valign="middle">0.249</td>
<td align="center" valign="middle">1.22 (0.76-2.14)</td>
<td align="center" valign="middle">0.312</td>
</tr>
<tr>
<td align="left" valign="middle">Histology (squamous vs. adenocarcinoma)</td>
<td align="center" valign="middle">1.16 (0.67-1.98)</td>
<td align="center" valign="middle">0.582</td>
<td align="center" valign="middle">1.20 (0.76-2.04)</td>
<td align="center" valign="middle">0.483</td>
</tr>
<tr>
<td align="left" valign="middle">NLR baseline (&#x2265;3.1 vs. &#x003C;3.1)</td>
<td align="center" valign="middle">1.30 (0.86-1.91)</td>
<td align="center" valign="middle">0.250</td>
<td align="center" valign="middle">1.54 (0.88-2.82)</td>
<td align="center" valign="middle">0.151</td>
</tr>
<tr>
<td align="left" valign="middle">NLR after two cycles (&#x2265;3.9 vs. &#x003C;3.9)</td>
<td align="center" valign="middle">1.27 (0.77-2.11)</td>
<td align="center" valign="middle">0.346</td>
<td align="center" valign="middle">1.37 (0.84-2.32)</td>
<td align="center" valign="middle">0.219</td>
</tr>
<tr>
<td align="left" valign="middle">NLR dynamic changes (&#x2265;15&#x0025; vs. &#x003C;15&#x0025;)</td>
<td align="center" valign="middle">1.64 (0.60-3.45)</td>
<td align="center" valign="middle">0.344</td>
<td align="center" valign="middle">1.28 (0.68-2.38)</td>
<td align="center" valign="middle">0.476</td>
</tr>
<tr>
<td align="left" valign="middle">NSE score (group 1 vs. group 2/3)</td>
<td align="center" valign="middle">1.28 (0.83-1.98)</td>
<td align="center" valign="middle">0.276</td>
<td align="center" valign="middle">1.25 (0.76-2.02)</td>
<td align="center" valign="middle">0.387</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>PFS, progression-free survival; OS, overall survival; HR, hazard ratio; CI, confidence interval; ECOG PS, Eastern Cooperative Oncology Group performance status; NLR, neutrophil-to-lymphocyte ratio; NSE, NLR, smoking status, ECOG.</p></fn>
</table-wrap-foot>
</table-wrap>
</floats-group>
</article>
