Literature DB >> 32953525

Neutrophil-to-lymphocyte ratio in combination with PD-L1 or lactate dehydrogenase as biomarkers for high PD-L1 non-small cell lung cancer treated with first-line pembrolizumab.

Giuseppe Luigi Banna1, Diego Signorelli2, Giulio Metro3, Domenico Galetta4, Alessandro De Toma2, Ornella Cantale5, Marco Banini3, Alex Friedlaender6, Pamela Pizzutillo4, Marina Chiara Garassino2, Alfredo Addeo6.   

Abstract

The identification of prognostic and predictive biomarkers for high-programmed cell death-ligand 1 (PD-L1) advanced non-small cell lung cancer (aNSCLC) treated with first-line pembrolizumab could support the decision-making about possible combination therapies. To explore the baseline neutrophil-to-lymphocyte ratio (NLR) with the possible addition of PD-L1 tumour proportion score (TPS) level or lactate dehydrogenase (LDH) as possible prognostic biomarkers by a multicenter retrospective exploratory analysis aiming at identifying favourable-risk patients. Baseline NLR was available for all 132 high PD-L1 aNSCLC patients, PD-L1 level and LDH for 81 (61%) and 85 (64%) patients, respectively. NLR, PD-L1 and LDH cut-offs by receiver operating characteristic (ROC) curves were 4.9, 77.5% and 268.5, respectively. Seventy-one patients (54%) had NLR <5; 25 out of 81 NLR <5 (31%) had PD-L1 >80%, 26 out of 85 (31%) NLR <5 and normal LDH (nLDH). Median follow-up was 16.3 months. As compared to NLR >5, significantly better 2-year overall survival (OS) and progression-free survival (PFS) were observed with NLR <5 [62% vs. 41%, P=0.005, hazard ratio (HR) 0.45, and median of 12.0 vs. 5.7 months, P=0.01, HR 0.56, respectively], NLR <5 + PD-L1 >80% (81%, P=0.006, HR 0.20 and median of 14.7, P=0.03, HR 0.44, respectively), and NLR <5 + nLDH (74%, P=0.009, HR 0.25 and median of 14.7, P=0.02, HR 0.40, respectively). NLR <5 and NLR <5 + nLDH significantly associated with PD (P=0.008 and P=0.025, respectively) but not response rate (RR) (P=0.09 and P=0.07, respectively); NLR <5 + PD-L1 >80% both RR (P=0.03) and PD (P=0.02). NLR <5 ± PD-L1 >80% or nLDH could represent easy-to-assess tools to identify high PD-L1 aNSCLC patients with favourable outcome following first-line pembrolizumab monotherapy. 2020 Translational Lung Cancer Research. All rights reserved.

Entities:  

Keywords:  Lung cancer; PD-L1; immunotherapy; lactate dehydrogenase (LDH); neutrophil-to-lymphocyte ratio (NLR)

Year:  2020        PMID: 32953525      PMCID: PMC7481583          DOI: 10.21037/tlcr-19-583

Source DB:  PubMed          Journal:  Transl Lung Cancer Res        ISSN: 2218-6751


Introduction

The current standard first-line treatment in advanced non-small cell lung cancer (aNSCLC) with programmed cell death-ligand 1 (PD-L1) tumour proportion score (TPS) of at least 50% includes pembrolizumab monotherapy (1), with a 3-year overall survival (OS) rate of 43.7% as compared to 24.9% with chemotherapy, supported by durable disease responses (2). However, pembrolizumab monotherapy is being challenged by the addition of chemotherapy (3) or a different immune-checkpoint inhibitor (ICI) (4). Hence, there is a need for reliable biomarkers to predict patients’ outcome and disease response following pembrolizumab monotherapy (5,6). The neutrophil-to-lymphocyte ratio (NLR) is a surrogate for tumour-associated inflammation and likely represents the frequency and activity of myeloid-derived suppressor cells (MDSCs), that hinder T-cell proliferation and expansion (7). Lactate dehydrogenase (LDH) has been investigated as a potential inflammatory biomarker in patients with cancer and is associated with poor outcomes in several cancer types (8). In aNSCLC, high NLR and its combination with high LDH, namely the immune prognostic index (LIPI), were correlated with worse outcomes for ICIs, but not for chemotherapy (8,9). We explored the NLR in combination with PD-L1 or LDH as possible biomarkers for high PD-L1 aNSCLC with first-line pembrolizumab. We present the following analysis in accordance with the REMARK Guideline (10) (available at http://dx.doi.org/10.21037/tlcr-19-583).

Patients and methods

The study analysis aimed to explore the prognostic value of low NLR, high PD-L1 TPS level and normal LDH, and of the combination of low NLR with high PD-L1 or normal LDH, in high PD-L1 aNSCLC treated with first-line pembrolizumab treated in five European Centers (three in Italy, one in the UK, one in Switzerland), as possible tools to identify patients with favourable outcome. Patients aged more than 18 years, with histologically confirmed aNSCLC, Eastern Cooperative Oncology Group (ECOG) Performance Status (PS) ≤2, PD-L1 TPS >50%, treated with first-line pembrolizumab were retrospectively assessed. The analysis followed the principles outlined in the Declaration of Helsinki (as revised in 2013) for all human or animal experimental investigations. The analysis involved a real-world series of patients treated according to the clinical practice; ethical approval was waived because all patients in each Center signed a specific consent form for their data collection and sharing with other Institutions. Three baseline parameters, from fresh routine blood or histopathological samples, were retrospectively analyzed: (I) the NLR, or the ratio between absolute neutrophils and lymphocytes; (II) the PD-L1 TPS level on the histological sample; (III) the blood level of LDH (in units/litre). The blood for NLR and LDH values was yielded within seven days from the ICI treatment start and routinely analyzed by local laboratories. PD-L1 was assessed by the platform and antibody used in each Center (see ).
Table 1

Patients and disease characteristics (No. 132)

CharacteristicNo.% [range]
Age, median68[31–85]
Gender
   Male/female87/4566/34
Tobacco use
   Never/current/former12/42/759/32/57
   NK32
Histology
   Adenocarcinoma8061
   Squamous3527
   Sarcomatoid75
   Adenosquamous32
   Pleomorphic22
   Other54
Initial stage
   I/II/III2/3/142/2/11
   IV11386
Previous treatments
   Surgery/NACT/RT7/7/55/5/4
Brain metastases1914
   CK-GK/ WBRT4/721/37
   Pembrolizumab842
Steroids (on pembrolizumab)2720
   ECOG PS
   0/1/242/68/2232/52/17
Autoimmune diseasea75%
PD-L1 expression
   ≥50% (NOS)5139
   50–70%/70–80%32/824/6
   80–90%/90–100%23/1817/14
   22C3/SP263/E1L3N101/22/977/17/7
EGFR/ALK/ROS13/0/04b
Radiotherapy (metastases)4131
Response to pembrolizumab
   CR/PR/SD/PD/NA1/55/25/36/152/42/19/27/11
Discontinuation for toxicity1411
Symptomatic PD4030
Second-line3728
   PR/SD/PD10/7/627/19/16

a, psoriasis in 3 (in 2 with associated arthritis), Crohn’s disease in 2, connectivities and myasthenia gravis each in one; b, of 80 patients with adenocarcinoma. CK, cyberknife; ECOG PS, Eastern Cooperative Oncology Group Performance Status; GK, gammaknife; NK, not known; No. Number; NA, not assessable; NACT, neoadjuvant chemotherapy; No., number; NOS, not otherwise specified; PD, progressive disease; PD-L1, programmed cell death-ligand-1; RT, radiotherapy; WBRT, whole brain radiotherapy.

a, psoriasis in 3 (in 2 with associated arthritis), Crohn’s disease in 2, connectivities and myasthenia gravis each in one; b, of 80 patients with adenocarcinoma. CK, cyberknife; ECOG PS, Eastern Cooperative Oncology Group Performance Status; GK, gammaknife; NK, not known; No. Number; NA, not assessable; NACT, neoadjuvant chemotherapy; No., number; NOS, not otherwise specified; PD, progressive disease; PD-L1, programmed cell death-ligand-1; RT, radiotherapy; WBRT, whole brain radiotherapy. The cut-offs for NLR, PD-L1 and LDH were identified by receiver operating characteristic (ROC) curves. For the combined biomarkers analysis patients with low NLR were grouped with those with available and high PD-L1 or available and normal LDH, with a possible overlapping between these two cohorts, or high PD-L1 and normal LDH. The prognostic role in OS and progression-free survival (PFS) was assessed by the two-sided log-rank test; the association with response rate (RR) and progressive disease (PD) by the 2-tailed Fisher exact test. RR, including complete response (CR) and partial response (PR), and PD, as the best response to the treatment, were assessed by the Response Evaluation Criteria in Solid Tumours (RECIST) criteria version 1.1 (11). Statistical significance was investigated by Chi-square test and 2-tailed Fisher exact tests with an acceptable significance value of P<0.05. The OS and PFS were calculated from the date of ICI treatment start until death or last date of follow-up, and of progression or death from any cause, respectively, were estimated using the Kaplan-Meier, reported as medians with confidence limits (95% CI) and compared using two-sided log-rank test, with an acceptable significance value of P<0.05. Patients who did not have events at the time of the analysis have been censored. Considering an expected 2-year OS of 52% in this patient population (2) and aimed at finding a difference in the 2-year OS of 25% with the combined biomarker analysis, the required sample size was 113 patients.

Results

Patients’ characteristics are summarized in . One hundred thirty-two patients treated with pembrolizumab from December 2016 to June 2019 were analyzed. Twenty-two patients (17%) discontinued the treatment, 11 due to toxicity; 6 of them because of pneumonia and one due to worsening of pre-existent myasthenia gravis. NLR was available for all patients, while PD-L1 level and LDH were available only for 81 (61%) and 85 (64%) patients, respectively. With a median follow-up of 16.3 months (95% CI: 15.0–17.7), the 2-year OS of all patients was 52.0% (95% CI: 49.3–55.0) and the median PFS 9.7 months (95% CI: 6.9–12.5) (see Figure S1A,B). Both OS and PFS were significantly associated with the disease response, CR/PR (2-year OS 89.3%, median PFS not reached) vs. SD (47.5%, 9.7 months) vs. PD (0%, 3.7 months) (P<0.001 for both, respectively) (see and Figure S1C,D).
Table 2

Prognostic value of NLR, PD-L1, LDH and association with disease response

ParameterNo. [%] (95% CI)No. [%] (95% CI)Total No. [%] or HR (P value) [95% CI]Log-rank, P valueχ2, P valueFishera, P value
NLR<5≥5
   CR/PR36 [55]20 [38]56 [48]0.06860.0936
   PD13 [20]23 [44]36 [31]0.00480.0083
   NA6 [8]9 [15]15 [11]
   Total71 [54]61 [46]132
   2-year OS, %62.0 (57.7–66.6)41.2 (38.1–44.6)0.45 (0.006) [0.26–0.80]0.005
   Median PFS, month12.0 (9.0–15.0)5.7 (3.9–7.6)0.56 (0.01) [0.35–0.89]0.012
NLR/PD-L1<5/≥80≥5/<80
   CR/PR15 [63]6 [33]0.01820.0308
   PD3 [13]11 [61]0.01140.0172
   NA1 [4]2 [10]
   Total25b [31]c20 [25]c
   2-year OS, %81.0 [72.9–89.5]42.9 [37.8–48.5]0.17 (0.007) [0.05–0.62]0.002
   Median PFS, month14.7 [11.4–18.0]4.7 [2.2–7.3]0.32 (0.01) [0.14–0.77]0.007
NLR/PD-L1≥5/≥80<5/<80
   CR/PR10 [67]5 [26]0.7919d1.0000d
   PD3 [20]9 [47]0.5277d0.6580d
   NA1 [6]1 [5]
   Total16 [20]c20 [25]c
   2-year OS, %47.7 [39.9–56.1]39.7 [34.0–46.0]3.11 (0.11)d [0.78–12.45]0.09d
   Median PFS, month19.2 [2.3–40.6]9.5 [5.5–13.5]1.18 (0.73)d [0.46–3.01]0.73d
NLR/LDH<5/<269≥5/≥269
   CR/PR14 [54]5 [24]0.03700.0716
   PD4 [15]10 [48]0.01630.0250
   NA0 [0]3 [12.5]
   Tot.26e [31]f24 [28]f
   2-year OS, %74.3 (65.5–83.5)36.0 (32.3–40.1)0.20 (0.004) [0.07–0.61]0.002
   Median PFS, month14.7 [NA]5.4 (3.0–7.9)0.35 (0.007) [0.16–0.75]0.007
NLR/LDH≥5/<269<5/≥269
   CR/PR6 [50]12 [63]0.8253g1.0000g
   PD5 [42]4 [21]0.0765g0.1082g
   NA1 [8]3 [14]
   Total13 [15]f22 [26]f
   2-year OS, %65.9 (56.8–75.6)53.0 (47.1–59.4)0.43 (0.23)g [0.11–1.71]0.214g
   Median PFS, month6.4 (5.0–7.8)10.4 (6.0–14.8)2.06 (0.15)g [0.78–5.45]0.139g
ResponseCR/PR; SDPD
   2-year OS, %89.3 (84.6–94.2); 47.5 (41.1–54.4)0.0 [NA]0.02 (<0.001) [0.008–0.08]; 0.14 (<0.001) [0.06–0.32]<0.001
   Median PFS, monthNR; 9.7 (5.8–13.6)3.7 (3.1–4.3)0.08 (<0.001) [0.05–0.16]; 0.18 (<0.001) [0.09–0.34]<0.001

a, 2-tailed Fisher test; b, 45 (63%) out of 71 patients with NLR <5 had available PD-L1 scores; 25 patients with NLR <5 and PD-L1 >80% included 16 patients with LDH scores whose 14 (87.5%) had normal LDH (nLDH); c, percentages refer to 81 patients with NLR and PDL1 scores; d, comparison between NLR/PD-L1 <5/≥80 and ≥5/≥80 cohorts; e, 48 (68%) out of 71 patients had available PD-L1 and LDH scores; 26 patients with NLR <5 and nLDH included 23 patients with PD-L1 scores whose 14 (61%) had PD-L1 >80%; f, percentages refer to 85 patients with NLR and LDH scores; g, comparison between NLR/PD-L1 <5/<269 and ≥5/<269 cohorts. CI, confidence interval; CR, complete response; HR, hazard ratio; LDH, lactate dehyidrogenase; NLR, neutrophils-to-lymphocytes ratio; No. Number; OS, overall survival; PD, progressive disease; PD-L1, programmed cell death-ligand-1; PFS, progression-free survival; PR, partial response; SD, stable disease.

a, 2-tailed Fisher test; b, 45 (63%) out of 71 patients with NLR <5 had available PD-L1 scores; 25 patients with NLR <5 and PD-L1 >80% included 16 patients with LDH scores whose 14 (87.5%) had normal LDH (nLDH); c, percentages refer to 81 patients with NLR and PDL1 scores; d, comparison between NLR/PD-L1 <5/≥80 and ≥5/≥80 cohorts; e, 48 (68%) out of 71 patients had available PD-L1 and LDH scores; 26 patients with NLR <5 and nLDH included 23 patients with PD-L1 scores whose 14 (61%) had PD-L1 >80%; f, percentages refer to 85 patients with NLR and LDH scores; g, comparison between NLR/PD-L1 <5/<269 and ≥5/<269 cohorts. CI, confidence interval; CR, complete response; HR, hazard ratio; LDH, lactate dehyidrogenase; NLR, neutrophils-to-lymphocytes ratio; No. Number; OS, overall survival; PD, progressive disease; PD-L1, programmed cell death-ligand-1; PFS, progression-free survival; PR, partial response; SD, stable disease. NLR, PD-L1 and LDH cut-offs by ROC curves were 4.9, 77.5% and 268.5, respectively (see ).
Figure S2

Receiver operating characteristic (ROC) curves of NLR, PD-L1 and LDH on PD. CI, confidence interval; DCR, disease control rate (= complete response, partial response, stable disease); HR, hazard ratio; LDH, lactate dehydrogenase; NA, not assessable; NLR, neutrophils-to-lymphocytes ratio; NR, not reached; OS, overall survival; mo., months; PD, progressive disease; PD-L1, programmed death ligand 1; PFS, progression-free survival.

Seventy-one patients (54%) had NLR <5, 45 (63%) and 48 (68%) of them had available PD-L1 and LDH scores, respectively. Twenty-five patients out of the 81 with NLR and PD-L1 scores (31%) had NLR <5 and PD-L1 >80% and included 16 patients with LDH scores whose 14 (87.5%) had normal LDH (nLDH); 26 patients out of 85 patients with NLR and LDH scores (31%) had NLR <5 and nLDH and included 23 patients with PD-L1 scores whose 14 (61%) had PD-L1 >80%. NLR <5, PD-L1 ≥80% and LDH <269 significantly associated with both OS and PFS (see ), with 2-year OS of 62.0% versus 41.2% and median PFS of 12.0 versus 5.7 months, for patients with NLR <5 as compared to those with NLR >5 [P=0.005, hazard ratio (HR) 0.45 and P=0.012, HR 0.56, respectively); 65.7% versus 40.6% and 14.7 versus 6.1 months, for PD-L1 ≥80% versus PD-L1 <80% (P=0.007, HR 0.35, and P=0.006, HR 0.44, respectively); and 72.1% versus 44.3% and 12.9 versus 8.0 months, for LDH <269 versus LDH ≥269 (P=0.026, HR 0.41, and P=0.052, HR 0.56, respectively).
Figure 1

Overall and progression-free survival according to NLR <5, PD-L1 ≥80% and LDH <269.

Overall and progression-free survival according to NLR <5, PD-L1 ≥80% and LDH <269. Data on outcomes by NLR, PD-L1 and LDH cut-offs are reported in and . Better 2-year OS and PFS were seen in patients with low NLR <5 and high PD-L1≥80% as compared to those with high NLR and low PD-L1 (81.0% vs. 42.9%, P=0.002, HR 0.17, and median of 14.7 vs. 4.7 months, P=0.007, HR 0.32, respectively); a trend toward better OS but not PFS was observed in patients with low NLR and high PD-L1 as compared to those with high NLR and high PD-L1 (81.0% vs. 47.7%, P=0.09, HR 3.11, and median of 14.7 vs. 19.2 months, P=0.73, HR 1.18, respectively). Better 2-year OS and PFS were seen in patients with low NLR <5 and nLDH <269 as compared to those with high NLR and high LDH (74.3% vs. 36.0%, P=0.002, HR 0.20, and median of 14.7 vs. 5.4 months, P=0.007, HR 0.35, respectively); a trend toward better OS and PFS was observed in patients with low NLR and nLDH as compared to those with high NLR and low PD-L1 (74.3% vs. 65.9%, P=0.214, HR 0.43, and median of 14.7 vs. 6.4 months, P=0.139, HR 2.06, respectively).
Figure 2

Overall and progression-free survival according to NLR <5 ± PD-L1 ≥80% or LDH <269.

Overall and progression-free survival according to NLR <5 ± PD-L1 ≥80% or LDH <269. As far as the disease response is concerned, low NLR <5 significantly associated with PD (P=0.008) but not RR (P=0.09); low NLR <5 with high PD-L1 >80% both RR (P=0.03) and PD (P=0.02), low NLR <5 with nLDH with PD but not RR (P=0.025 and P=0.07, respectively).

Discussion

We found that low NLR <5, high PD-L1 >80% and LDH <269, especially when low NLR <5 was combined with one of the other two factors, significantly associated with favourable outcomes following first-line pembrolizumab monotherapy in aNSCLC. This underlines the essential role of tumour inflammation and microenvironment (12). Differently from other reported series, the cut-offs we used for NLR, PD-L1 and LDH were ROC-based and quantitative. This could raise the issue of their external validity, of the need for their validation or just of comparison with those currently reported. As far as the NLR is concerned, our ROC-based cut-off of 5 mirrored what has already been reported in patients with NSCLC (9) and previously validated in those with metastatic melanoma treated with ipilimumab (13). In the LIPI score for NSCLC patients (8), the NLR cut-off used was instead 3, based on a larger and updated series of patients with metastatic melanoma treated with ipilimumab (14). Regarding LDH, there is no current standard cut-off. The upper limit of normal (ULN) value according to the limit of each center was for example adopted for the LIPI score, where the median LDH value of all patients was 248.5 (8). In the largest series of patients with metastatic melanoma treated with pembrolizumab an LDH value of at least 2.5 times ULN resulted as an independent prognostic value (15), while in another series a quantitative cut-off of 480 U/L was reported (16). No validated cut-off of PD-L1 expression levels over the threshold of 50% has been formally explored. In a series of 187 patients with high PD-L1 NSCLCs treated with first-line pembrolizumab, patients’ clinical outcomes were significantly improved in very high PD-L1 ≥90% positive tumours (17). Thus, our ROC analyses suggested that in patients with NSCLC treated with an ICI, 5 is an appropriate NLR cut-off for patients with aNSCLC, a quantitative LDH cut-off of 269 could be considered as an alternative to the ULN and a lower threshold of 80% PD-L1 NSCLC expression could be considered. Furthermore, our combined analyses differed from the LIPI (8), besides the use of ROC-based and quantitative cut-offs, for the inclusion of PD-L1 expression level, which currently represents the only validated predictive biomarker. Regarding the association with disease response, only PD-L1 ≥80% was associated with both RR and PD, while NLR <5 and nLDH with the only PD. Intriguingly, although high PD-L1 seemed to be associated with RR independently of NLR, a nonsignificant trend toward better OS in patients with low NLR and high PD-L1 as compared to those with high NLR and high PD-L1 was observed. This suggests further investigations in comparative trials to explore the predictive value of PD-L1 >80% against the prognostic value of NLR and LDH. One limitation of this study is the lack of a control cohort. This does not allow the discrimination between the prognostic and predictive value of the factors we investigated. Ideally, the proper control cohort to explore the predictive value of our factors in this specific setting would be the cohort of patients treated with chemotherapy plus the ICI, which currently is unlikely in the clinical practice for patients with high PD-L1 tumours. We are, therefore, conscious that the output of our analysis was to explore an easy-to-assess lab prognostic tool, which could currently aid the decision-making about the addition of chemotherapy to ICI in patients with high PD-L1 tumours, alongside other clinical factors, while waiting for evidence from randomized clinical trials in this setting and the possible exploration of their predictive value. Identifying patients who are likely to benefit from pembrolizumab monotherapy thanks to low NLR and high PD-L1 or nLDH (approximately one third) would be highly relevant to us. The opposite could be even more interesting. Patients with a high PD-L1 (>80%), but NLR >5 and/or high LDH may warrant a combination strategy to offer them the best outcomes. We advocate the clinical evaluation of this easy-to-assess tool based on the combination of low NLR <5 and high PD-L1 >80% or nLDH <269 for retrospective and prospective analyses in clinical trials, comparing the addition of chemotherapy or a different ICI to single-agent immunotherapy. If the validity of this simple tool were confirmed, it could be of crucial importance in the current therapeutic landscape. Another possible limitation of our study, other than the lack of a validation set, could be the relatively short follow-up time. However, currently available evidence and approval of ICIs in the first-line treatment of NSCLC are based on a median follow-up time from the 12 available studies of 13.0 months, ranging from 7.7 to 25.2. Particularly, the 4 studies with pembrolizumab in the first-line setting had median follow-up of 11.7 months, ranging from 7.7 to 25.2 (1,3). As above mentioned, since the present study did not compare immunotherapy to chemotherapy plus ICI, we cannot support the predictive value of PD-L1 >80%, or of low NLR <5, but we can suggest their prognostic value, alongside with that of nLDH. In conclusion, we suggest that low NLR <5, when combined with high PD-L1 >80% or nLDH <269 represents an easily assessable and affordable tool to explore the outcomes of aNSCLC patients with high PD-L1 likely to benefit from pembrolizumab monotherapy. This tool could have a role in therapeutic decision-making alongside other clinical factors. Its validation in retrospective and prospective randomised trials is warranted. Overall and progression-free survival of all patients and according to disease response (DCR versus PD). Receiver operating characteristic (ROC) curves of NLR, PD-L1 and LDH on PD. CI, confidence interval; DCR, disease control rate (= complete response, partial response, stable disease); HR, hazard ratio; LDH, lactate dehydrogenase; NA, not assessable; NLR, neutrophils-to-lymphocytes ratio; NR, not reached; OS, overall survival; mo., months; PD, progressive disease; PD-L1, programmed death ligand 1; PFS, progression-free survival. The article’s supplementary files as
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7.  Association of the Lung Immune Prognostic Index With Immune Checkpoint Inhibitor Outcomes in Patients With Advanced Non-Small Cell Lung Cancer.

Authors:  Laura Mezquita; Edouard Auclin; Roberto Ferrara; Melinda Charrier; Jordi Remon; David Planchard; Santiago Ponce; Luis Paz Ares; Laura Leroy; Clarisse Audigier-Valette; Enriqueta Felip; Jorge Zerón-Medina; Pilar Garrido; Solenn Brosseau; Gérard Zalcman; Julien Mazieres; Caroline Caramela; Jihene Lahmar; Julien Adam; Nathalie Chaput; Jean Charles Soria; Benjamin Besse
Journal:  JAMA Oncol       Date:  2018-03-01       Impact factor: 31.777

8.  A Novel Paradigm Between Leukocytosis, G-CSF Secretion, Neutrophil-to-Lymphocyte Ratio, Myeloid-Derived Suppressor Cells, and Prognosis in Non-small Cell Lung Cancer.

Authors:  Montreh Tavakkoli; Cy R Wilkins; Jodi V Mones; Michael J Mauro
Journal:  Front Oncol       Date:  2019-04-26       Impact factor: 6.244

9.  Nivolumab plus Ipilimumab in Advanced Non-Small-Cell Lung Cancer.

Authors:  Matthew D Hellmann; Luis Paz-Ares; Reyes Bernabe Caro; Bogdan Zurawski; Sang-We Kim; Enric Carcereny Costa; Keunchil Park; Aurelia Alexandru; Lorena Lupinacci; Emmanuel de la Mora Jimenez; Hiroshi Sakai; Istvan Albert; Alain Vergnenegre; Solange Peters; Konstantinos Syrigos; Fabrice Barlesi; Martin Reck; Hossein Borghaei; Julie R Brahmer; Kenneth J O'Byrne; William J Geese; Prabhu Bhagavatheeswaran; Sridhar K Rabindran; Ravi S Kasinathan; Faith E Nathan; Suresh S Ramalingam
Journal:  N Engl J Med       Date:  2019-09-28       Impact factor: 91.245

10.  REporting recommendations for tumour MARKer prognostic studies (REMARK).

Authors:  L M McShane; D G Altman; W Sauerbrei; S E Taube; M Gion; G M Clark
Journal:  Br J Cancer       Date:  2005-08-22       Impact factor: 7.640

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  18 in total

Review 1.  Diagnostic and prognostic biomarkers in oligometastatic non-small cell lung cancer: a literature review.

Authors:  Diego Cortinovis; Umberto Malapelle; Fabio Pagni; Alessandro Russo; Giuseppe Luigi Banna; Elisa Sala; Christian Rolfo
Journal:  Transl Lung Cancer Res       Date:  2021-07

2.  Association of Dynamic Changes in Peripheral Blood Indexes With Response to PD-1 Inhibitor-Based Combination Therapy and Survival Among Patients With Advanced Non-Small Cell Lung Cancer.

Authors:  Yuzhong Chen; Shaodi Wen; Jingwei Xia; Xiaoyue Du; Yuan Wu; Banzhou Pan; Wei Zhu; Bo Shen
Journal:  Front Immunol       Date:  2021-05-14       Impact factor: 7.561

3.  Prognostic models for immunotherapy: emerging factors for an evolving treatment landscape.

Authors:  Howard West
Journal:  Transl Lung Cancer Res       Date:  2021-01

4.  A Scoring System Based on Nutritional and Inflammatory Parameters to Predict the Efficacy of First-Line Chemotherapy and Survival Outcomes for De Novo Metastatic Nasopharyngeal Carcinoma.

Authors:  Wang-Zhong Li; Xin Hua; Shu-Hui Lv; Hu Liang; Guo-Ying Liu; Nian Lu; Wei-Xin Bei; Wei-Xiong Xia; Yan-Qun Xiang
Journal:  J Inflamm Res       Date:  2021-03-10

5.  First-line immunotherapy in non-small cell lung cancer patients with poor performance status: a systematic review and meta-analysis.

Authors:  Francesco Facchinetti; Massimo Di Maio; Fabiana Perrone; Marcello Tiseo
Journal:  Transl Lung Cancer Res       Date:  2021-06

6.  Artificial intelligence-based analysis for immunohistochemistry staining of immune checkpoints to predict resected non-small cell lung cancer survival and relapse.

Authors:  Haoyue Guo; Li Diao; Xiaofeng Zhou; Jie-Neng Chen; Yue Zhou; Qiyu Fang; Yayi He; Rafal Dziadziuszko; Caicun Zhou; Fred R Hirsch
Journal:  Transl Lung Cancer Res       Date:  2021-06

7.  The Gustave Roussy Immune (GRIm)-Score Variation Is an Early-on-Treatment Biomarker of Outcome in Advanced Non-Small Cell Lung Cancer (NSCLC) Patients Treated with First-Line Pembrolizumab.

Authors:  Edoardo Lenci; Luca Cantini; Federica Pecci; Valeria Cognigni; Veronica Agostinelli; Giulia Mentrasti; Alessio Lupi; Nicoletta Ranallo; Francesco Paoloni; Silvia Rinaldi; Linda Nicolardi; Andrea Caglio; Sophie Aerts; Alessio Cortellini; Corrado Ficorella; Rita Chiari; Massimo Di Maio; Anne-Marie C Dingemans; Joachim G J V Aerts; Rossana Berardi
Journal:  J Clin Med       Date:  2021-03-02       Impact factor: 4.241

Review 8.  Biomarkers for predicting the efficacy of immune checkpoint inhibitors.

Authors:  Chengji Wang; He-Nan Wang; Liang Wang
Journal:  J Cancer       Date:  2022-01-01       Impact factor: 4.207

9.  Pretreatment Fibrinogen-Albumin Ratio (FAR) Associated with Treatment Response and Survival in Advanced Non-Small Cell Lung Cancer Patients Treated with First-Line Anti-PD-1 Therapy Plus Platinum-Based Combination Chemotherapy.

Authors:  Chengliang Yuan; Meifang Huang; Huilin Wang; Wei Jiang; Cuiyun Su; Shaozhang Zhou
Journal:  Cancer Manag Res       Date:  2022-01-26       Impact factor: 3.989

10.  Inflammatory indices and clinical factors in metastatic renal cell carcinoma patients treated with nivolumab: the development of a novel prognostic score (Meet-URO 15 study).

Authors:  Sara Elena Rebuzzi; Alessio Signori; Giuseppe Luigi Banna; Marco Maruzzo; Ugo De Giorgi; Paolo Pedrazzoli; Andrea Sbrana; Paolo Andrea Zucali; Cristina Masini; Emanuele Naglieri; Giuseppe Procopio; Sara Merler; Laura Tomasello; Lucia Fratino; Cinzia Baldessari; Riccardo Ricotta; Stefano Panni; Veronica Mollica; Maria Sorarù; Matteo Santoni; Alessio Cortellini; Veronica Prati; Hector Josè Soto Parra; Marco Stellato; Francesco Atzori; Sandro Pignata; Carlo Messina; Marco Messina; Franco Morelli; Giuseppe Prati; Franco Nolè; Francesca Vignani; Alessia Cavo; Giandomenico Roviello; Francesco Pierantoni; Chiara Casadei; Melissa Bersanelli; Silvia Chiellino; Federico Paolieri; Matteo Perrino; Matteo Brunelli; Roberto Iacovelli; Camillo Porta; Sebastiano Buti; Giuseppe Fornarini
Journal:  Ther Adv Med Oncol       Date:  2021-05-18       Impact factor: 8.168

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