Sixth-week immune-nutritional-inflammatory biomarkers: Can they predict clinical outcomes in patients with advanced non-small-cell lung cancer treated with immune checkpoint inhibitors?

doi:10.21203/rs.3.rs-2376158/v1

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Research Article

Sixth-week immune-nutritional-inflammatory biomarkers: Can they predict clinical outcomes in patients with advanced non-small-cell lung cancer treated with immune checkpoint inhibitors?

https://doi.org/10.21203/rs.3.rs-2376158/v1

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Background

We explored the relationship between inflammatory markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), Lung Immune Prognostic Index (LIPI), and the modified Glasgow Prognostic Score (mGPS) to determine whether they could predict treatment response to pembrolizumab or nivolumab (immunotherapy). The data of 83 patients with non-small-cell lung cancer (NSCLC) treated with immunotherapy as first/second-line treatment were retrospectively analyzed. We conducted a retrospective analysis to investigate the usefulness of NLR, PLR, LIPI, and the mGPS at baseline and 6 weeks after the start of treatment (post-treatment).

Methods

We included all patients with lung cancer who were treated with immune checkpoint inhibitors (ICIs) from March 2017 to November 2021 at Burhan Nalbantoğlu Government Hospital and Near East University Hospital (North Cyprus). We examined NLR, PLR LIPI, and mGPS trends and explored the association with progression-free survival (PFS) overall survival (OS), and response rates (RR) at 6 weeks.The relationship was evaluated by Cox regression analysis.

Results

Eighty-three patients were enrolled in the study. The presence of liver metastasis, low post-treatment NLR (< 5), low post-treatment PLR (< 170), intermediate post-treatment LIPI, and immune-related adverse events were significantly associated with response. Patients with a high post-treatment NLR (≥ 5) had significantly shorter PFS (HR: 1.1, p < 0.001), shorter OS (HR: 1.2, p < 0.001). Multivariate analysis demonstrated that high post-treatment NLR was an independent prognostic factor of shorter OS. Patients with a high post-treatment PLR (≥ 170) had significantly shorterPFS (HR: 1.0, p < 0.001) and OS (HR: 0.9, p < 0.001). A high post-treatment PLR remained an independent prognostic factor for OS in multivariate analysis (HR: 0.9, p < 0.001). A good LIPI status was associated with better PFS (p < 0.020)and OS (p < 0.065)in ICI therapy compared with intermediate or poor LIPI status. Post-treatment GPS independently predicted anti-PD1 treatment efficacy; a good post-treatment GPS (GPS 0–2) was significantly associated with improved PFS (p < 0.009) and OS (p < 0.064)

Conclusion

Posttreatment NLR, PLR, LIPI, and mGPS are associated with worse OS and recurrence. These findings should be validated independently and prospectively in further studies.

Immune-based prognostic scores

neutrophil-to-lymphocyte ratio (NLR)

platelet-to-lymphocyte ratio (PLR)

Lung Immune Prognostic Index (LIPI)

modified Glasgow Prognostic Score (mGPS)

Lung cancer is the most prevalent, life-threatening malignancy and cancer-related death worldwide.(1) The primary traditional treatments for patients with lung cancer are surgery and chemotherapy. Most cases are diagnosed at advanced stages, and the benefits achieved from chemotherapy and the prognosis of non-small-cell lung cancer (NSCLC) remain poor in advanced stages. In recent years, immunotherapy has developed as a novel strategy for the management of NSCLC. Many studies have identified that tumor cells can evade the antitumor responses of T cells, also nivolumab and pembrolizumab inhibit programmed cell-death protein-1 (PD-1) mediated signaling by blocking its ligand (PD-L1).(2)

Immune checkpoint inhibitors have been identified and clinically validated as predictive biomarkers such as PDL-1 expression, tumor mutational burden (TMB) and microsatellite instability high (MSI-H); however, these biomarkers have some limitations; therefore, physicians need an effective biomarker for risk stratification.(3)

Tumor-associated inflammation in patients with cancer is believed to influence the host immune response and resistance, growth, and migration of tumors via certain inflammatory factors.(4) Due to the interplay between systemic inflammation, the immune system, and immunotherapy, pretreatment neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), Lung Immune Prognostic Index (LIPI), and modified Glasgow Prognostic Scores (mGPS) have been indicated to predict the therapeutic effect or outcomes related to poor survival in patients with solid tumors.(5–7)

In recent years, scientists found that pretreatment and post-treatment changes in the composition of peripheral blood cells could reflect the body’s antitumor status more accurately, thus, affecting prognosis.(8)

In this study, we aimed to determine the prognostic use of posttreatment NLR, PLR, LIPI, and mGPS

obtained at the 6th week to reveal a reliable, robust, inexpensive, and potentially tumor-agnostic posttreatment indicator for predicting the response of anti-PD-1 combined therapy.

Study population

We conducted a retrospective analysis of consecutive patients with NSCLC who had undergone anti-PD-1 antibody (nivolumab or pembrolizumab) treatment at Burhan Nalbantoglu Research hospital and Near East University hospital between March 2017 and March 2021.

The inclusion criteria were as follows: (a) pathologically confirmed NSCLC; (b) initial stage IIIB or IV, recurrence after curative surgery or maintenance after chemoradiotherapy; and (c) administration of nivolumab at 3 mg/kg every 2 weeks or pembrolizumab at 200-mg flat dose every 3 weeks as palliative therapy. All patients had anti-PD-1 therapy and some received additional anti-neoplastic therapies.

Complete blood cell counts and some biochemistry parameters were assessed before each drug administration. Total white blood cell (WBC) counts, absolute neutrophil counts (ANC), absolute lymphocyte counts (ALC), platelet (PLT) counts, lactate dehydrogenase (LDH), albumin, and C-reactive protein (CRP) were analyzed 6 weeks after the start of treatment.

NLR was calculated as the ratio of ANC to ALC, and an NLR ≥ 5 was considered as high.(9) PLR was defined as the ratio of PLT to ALC and categorized using a threshold value of PLR ≥ 150.(10)

The LIPI score was grouped according to the derived neutrophil-lymphocyte ratio (dNLR) and LDH levels. The dNLR was calculated as the ratio of ANC to [WBC count − ANC]. LIPI was stratified into three risk groups: good (dNLR < 3 + LDH < upper limit of normal (ULN); intermediate (dNLR > 3 or LDH > ULN); and poor risk (dNLR > 3 + LDH > ULN).(11)

mGPS was scored as 0, 1, or 2 based on CRP (> 1.0 mg/dL) and albumin (< 35 g/L) levels; mGPS0 = albumin (> 35 g/L), CRP (< 1.0 mg/dL), or albumin (< 35 g/L) CRP (< 1.0 mg/dL), mGPS1 = albumin (> 35 g/L) CRP (> 1.0 mg/dL), mGPS2 = albumin (< 35 g/L) CRP (> 1.0 mg/dL).(12)

Thoracoabdominopelvic computed tomography or positron emission tomography (PET)-CT scans were also performed every 12 weeks according to the study protocol depending on patient clinical status, additionally as needed, to assess earlier disease progression. All responses were evaluated according to the revised Response Evaluation Criteria in Solid Tumors (RECIST) guideline (version 1.1).

Hyperprogression, as determined using RECIST, is unexpected rapid disease progression under immunotherapy compared with baseline in the first evaluation after immunotherapy with a ≥ 2-fold increase in growth rate. Pseudoprogression is the phenomenon in which an initial increase in target lesion length occurs or new lesions appear, followed by tumor shrinkage; these changes can be demonstrated through tumor biopsy or a continuous radiography scan.(13)

All analyses were conducted using SPSS (version 22.0). The Cox proportional hazards model was used to test the relationships between the variables and PFS,OS and RR. P < 0.05 was considered statistically significant in all analyses. PFS describes the time from the start of immunotherapy treatment to the date of disease progression or death. OS is the period from the date of starting immunotherapy treatment that patients that are still alive or to death. ORR describes the percentage of responses among all treated patients.

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by Local Ethical Committee of Burhan Nalbantoğlu Research Hospital approved the study in April 2021 with decision number E-21/21.

Table 1

Baseline patient and tumor characteristics
Age at start (years) Median Range < 70 > 70	66 42–88 64 (69.5) 28 (30.4)
Sex n (%) Male Female	73 (88) 10 (12)
ECOG performance status score n (%) 0–1 2–4	46 (50.0) 46 (50.0)
Tumor Histology (%) Squamous cell carcinoma Adenocarcinoma NSCL, NOS Adenosquamos cell carcinoma	32 (38.6) 48 (57.8) 2 (2.4) 1 (1.2)
PD-L1 n (%) Negative 1–49% ≥50% Unknown	11 (13.3) 3 (3.6) 5 (6.0) 64 (77.1)
Smoking status n (%) Current or former smoker Never smoked	79 (95.2) 4 (4.8)
Immunotherapy line step n (%) 1st step 2nd Step 3th step Maintenance	41 (49.4) 41 (49.4) 1 (1.2)
Posttreatment neutrophil-to-lymphocyte ratio n (%) Median < 5 > 5	14.15 (1.07–115.0) 1 (1.9) 91 (98.1)
Postreatment platelet-to-lymphocyte ratio n (%) Median < 150 > 150	797.00 (4.00-3223.0) 11 (10.9) 82 (89.1)
Posttreatment LIPI (%) GOOD INTERMEDIATE POOR Unkown	26 (31.3) 33 (39.8) 23 (27.7) 1 (1.2)
Posttreatment mGPS (%) Median 0 1 2 Unknown	5 (6.0) 29 (34.9) 16 (19.3) 33 (39.8)
Posttreatment imunotherapy related adverse event (%) Non-adverse event Adverse event	66 (79.5%) 17 (20.5%)
Pretreatment liver metastasis (%) Median Non-liver met Liver met	63 (75.9) 20 (24.1)
Immunotherapy type (%) Pembrolizumab Nivolumab Nivolumab + ipilumab then nivolumab	44 (53) 38 (45.8) 1 (1.2)

Patient demographics.

This study included 83 patients with advanced NSCLC (88% men, 12% women); their demographic characteristics are shown in Table I. The median age at treatment onset was 66 (range, 42–88) years, 95.2% were smokers, and 50% had ECOG PS 2 or higher. The present study group included 57.8% patients with adenocarcinoma, 38.6% with squamous cell carcinoma, two with poorly differentiated carcinoma, and one with adenosquamous carcinoma. One patient had epidermal growth factor receptor (EGFR) mutations, one showed anaplastic lymphoma kinase (ALK) rearrangements; no c-ROS oncogene (ROS 1) rearrangement or BRAF gene mutations were determined. According to the site of metastasis, 24.1% of patients had liver metastasis. All patients received immunotherapy; 53% of patients received pembrolizumab, 45.8% received nivolumab, and one patient received nivolumab plus ipilimumab therapy. According to the treatment arrangement, 41 patients ranked 1st and 41 patients ranked 2nd carried out of this treatment. The results showed that 20.5% of the patients had immune-related adverse effects.

Immunologic biomarkers

The biomarker results after the third nivolumab infusions are given in Table 1. The 6th-week blood counts and NLR, PLR, LIPI, and mPGS were investigated.

Patients were divided into two groups with the threshold value of NLR < 5 at 6 weeks post-treatment, which was associated with poorer PFS. According to the NLR reduction, anti-PD-1 antibody treatment was

associated with a higher objective response rate (HR = 0.703, 95% CI: [0.556–0.888]; p = 0.003), a significantly improved PFS (HR = 1.162, 95% CI: [1.091–1.237]; p < 0.001), and improved OS (HR = 1.182, 95% CI: [1.107–1.261]; p < 0.001). All results were statistically significant (Table 2). We performed multivariate analyses to identify the prognostic importance of clinical characteristics of NLR on improved PFS (HR = 1.212, 95% CI: [0.924–1.59]; p = 0.165), which was not statistically significant, but the improved OS was statistically significant (HR = 1.456, 95% CI: [1.128–1.880]; p = 0.004).

This study also reported the relationship between PLR levels on RR, PFS, and OS in patients with cancer with immunotherapy treatment. PLR thresholds (< 170 and ≥ 170) were used as the factors of subgroup analysis. Univariate analysis for PFS (HR = 1.001, 95% CI: [1.001–1.002]; p = 0.001) also OS (HR = 0.996, 95% CI: [0.994–0.999]; p = 0.001) showed an additional significant association for PLR. Multivariate analysis for higher PLR at baseline was associated with shorter PFS (HR = 0.998, 95% CI: [0.995–1.001]; p = 0.188) and an independent prognostic factor of OS (HR = 0.996, 95% CI: [0.994–0.999]; p = 0.001).

We then investigated the association between different LIPI cut-off value clinical outcomes of patients and the prognostic value of post-treatment LIPI for OS. The intermediate OS group (HR = 1.650, 95% CI: [0.913–2.982]; p = 0.097) and poor OS group (HR = 2.086, 95% CI: [1.111–3.916]; p = 0.022). The intermediate PFS group (HR = 1.985, 95% CI: [1.115–3.534]; p = 0.020) and poor PFS group (HR = 2.24, 95% CI: [1.214–4.156]; p = 0.010). The intermediate RR group (HR = 0.138, 95% CI: [0.24–1.82]; p = 0.001) and the poor RR group (HR = 0.196, 95% CI: [0.17–2.10]; p = 0.009). Univariate analysis demonstrated that elevated LIPI was statistically significantly related to and an independent prognostic factor of OS, PFS, and RR, except in the intermediate group. Multivariate analyses showed that only the intermediate LIPI group (HR = 0.188, 95% CI: [0.053–0.664]; p = 0.009) was a significant prognostic factor (Tables 2 and 3).

This study had dynamic mGPS status and we further analyzed the relationship between dynamic mGPS and PFS, OS, and RR. PFS on mGPS1 (HR = 2.168, 95% CI: [0.747–6.291]; p = 0.015) and PFS on mGPS2 (HR = 4.803, 95% CI: [1.531–15.065]; p = 0.007). OS on mGPS1 (HR = 1.81, 95% CI: [0.625–5.265]: p = 0.273) and OS on mGPS2 (HR = 3.22, 95% CI: [1.062–9.762]; p = 0.039). RR on mGPS 1 (HR = 0.789, 95% CI: [0.113–5.528]; p = 0.812) and RR on mGPS2 (HR = 0.214, 95% CI: [0.021–2.187]; p = 0.194). There was a significant association between mGPS1 and mGPS2 cut-off values and increased PFS benefit (p = 0.155 and p = 0.007, respectively). Although the mGPS cut-off value seemed to be associated with increased HRs of OS, only mGPS2 was statistically significant (p = 0.039). Interestingly, the HRs of PFS showed a significant correlation with the HRs of OS, suggesting that PFS could be a potential surrogate for OS in these study designs.

Table 2

Univariable and multivariable analyses of overall survival and progression-free survival
Variables	Progression-free survival
Variables	Unadjusted HR (95% CI), P	Adjusted HR (95% CI), P	Unadjusted HR (95% CI), P	Adjusted HR (95% CI), P
ECOG PS ≥ 2	1.48 (0.925–2.383) .101	-	1.61 (0.989–2.640) .056	-
Histology-Non-SQ	0.58 (0.343-1.000) .050	-	0.69 (0.402–1.187) .180	-
> 75 years of age	0.98 (0.96–1.006) .137		0.55 (0.969–1.017) .993
Presence of brain metastasis	1.16 (0.502–2.688) .725	-	1.144 (0.458–2.855) .773	-
Presence of bone metastasis	1.383 (0.844–2.26) .199		1.18 (0.718–1.94) .512
Presence of adrenal gland metastasis	1.51 (0.849–2.685) .161	-	1.592 (0.876–2.895) 0.127	-
Presence of malignant pleural metastasis	1.931 (1.062–3.508) .031	1.675 (0.563–4.982) .354	1.223 (0.666–2.248) 0.516	-
Presence of liver metastasis	1.994 (1.179–3.373) .010	3.093 (1.017–9.405) .047	2.060 (1.195–3.550) .009	1.97 (0.926–4.21) .078
irAEs	0.444 (0.241–0.817) .009	0.339 (0.086–1.339) .123	0.523 (0.279–0.981) .043	0.120 (0.036–0.402) .001
NLR	1.162 (1.091–1.237) .000	1.212 (0.924–1.59) .165	1.182 (1.107–1.261) .000	1.456 (1.128–1.880) .004
PLR	1.001 (1.001–1.002) .001	0.998 (0.995–1.001) .188	1.001 (1.000-1.002) .003	0.996 (0.994–0.999) .001
LIPI status • Good • Intermediate • Poor	N/A .002 1 1.985 (1.115–3.534) .020 2.24 (1.214–4.156) .010	N/A .940 1 0.802 (0.213–3.01) .744 0.729 (0.111-4.80) .743	N/A .065 1 1.650 (0.913–2.982) .097 2.086 (1.111–3.916) .022	N/A .786 1 0.731 (0.246–2.17) .928 0.837 (0.245–2.86) .576
Pdl1 • 0 • 1–49 > 50	N/A .395 1 0.342 (0.72–1.616) .176 0.753 (0.250–2.270) .614		N/A .779 1 0.848 (0.226–3.181) .807 1.381 (0.454–4.199) .570	N/A
CRP level	1.097 (1.034–1.165) .002	1.015 (0.916–1.125) .771	1.032 (0.978–1.089) .246
mGPS • 0 • 1 • 2	N/A .009 1 (reference) 2.168 (0.747–6.291) .015 4.803 (1.531–15.065) .007	N/A .373 1 (reference) 2.65 (0.527–13.36) .237 4.37 (0.557–34.39) .161	N/A .064 1 (reference) 1.81 (0.625–5.265) .273 3.22 (1.062–9.762) .039	N/A .180 1 (reference) 2.49 (0.739–8.420) .141 4.34 (0.918–20.558) .064

Table 3

Univariate and multivariate analyses of clinicopathologic factors and immune-inflammation-nutritional parameters
Variables	OR for response		OR for disease control
	Unadjusted OR (95% CI), P	Adjusted OR (95% CI), P	Unadjusted OR (95% CI), P	Adjusted OR (95% CI), P
ECOG PS ≥ 2	0.361 (0.147–0.884) .026	0.338 (0.112–1.017) .054
Histology-SQ		-
> 75 years of age		-
Presence of brain metatasis	0.977 (0.205–4.670) .977	-
Presence of bone metastasis	0.737 (0.298–1.822) .509
Presence of adrenal gland metastasis	0.327 (0.096–1.108) .073	-
Presence of malignant pleural metastasis	0.844 (0.270–2.636) .771	-
Presence of liver metastasis	0.631 (0.222–1.793) .388	-
irAEs	3.007 (0.989–9.143) .052
NLR	0.703 (0.556–0.888) .003	0.737 (0.513–1.059) .099-
PLR	0.995 (0.994-1.000) .001	1.000 (0.995–1.005) .974-
LIPI status • Good • Intermediate • Poor	N/A .002 1 0.138 (0.24–1.82) .001 0.196 (0.17–2.10) .009	N/A, .015 1 0.188 (0.053–0.664) .009 0.956 (0.195–4.693) .956-
Pdl1 • 0 • 1–49 • > 50
CRP level	0.961 (0.836–1.104) .574
mGPS • 0 • 1 • 2	N/A .269 1 (reference) 0.789 (0.113–5.528) .812 0.214 (0.021–2.187) .194	-

This study, with multiple post-treatment and immune-based prognostic scores, aimed to investigate the prognostic role of post-treatment 6th-week NLR, PLR, LIPI, and mGPS scores in patients with locally advanced or metastatic lung cancer. Pretreatment NLR, PLR, LIPI, and mGPS is a manifestation of baseline immune function, their posttreatment results are theoretically modifiable factors that could be influenced by several factors, such as radiation prescriptions or therapy dosing. These findings may indicate a potential predictive marker of response. Eighty-three patients were examined, revealing that post-treatment NLR, PLR, LIPI, and mGPS were statistically significantly associated with poor prognosis in the study population. Besides determining a predictive value, our data also demonstrated an independent association with survival.

There are multiple research articles and meta-analyses about the prognostic effect of pretreatment NLR in lung cancer but changes of NLR status depending on treatment have not yet been determined. Our hypothesis was that post-treatment NLR and NLR dynamics after immunotherapy would be prognostic. In our study, posttreatment NLR values (> 5) up to the threshold had shorter PFS, shorter OS, and lower RR, consistent with all previous study results. In univariate analysis, all inflammatory parameters were independent prognostic indicators, but on multivariate analysis, only OS had relevant results with NLR. In one study, 54 patients with NSCLC were treated with anti-PD-1 treatment, NLR was assessed at baseline and 6 weeks, and low post-treatment NLR (> 5) and immune-related adverse events were significantly associated with low response, shorter PFS, and OS. Liver metastasis was also an independent prognostic indicator of shorter PFS.(14) Another study on patients with NSCLC who received conventional chemotherapy and gefitinib demonstrated that an early reduction in NLR was a surrogate marker of survival.(15)

The backbone treatment for patients with advanced NSCLC is platinum with cytotoxic chemotherapy.(16) We know about chemotherapy-induced neutropenia associated with increased survival in patients with advanced NSCLC.(17) Neutropenia should be a surrogate marker of chemotherapy efficacy, deficient neutropenia in patients may indicate insufficient dosing and inadequate tumor elimination.(18) Neutrophils can also be manipulated to develop different functional polarization and phenotypic states, which induces antitumor or protumor effects In the tumor microenvironment.(19) Finally, the patterns of NLR change after the 6th week of treatment as a prognostic factor for PFS and OS were consistent with immunotherapy treatment regimens.

High platelet levels have an active role in inflammation, tissue regeneration, or acceleration of tumor progression.(20) In contrast, lymphocytes release some types of cytokines that activate anti-tumor immunity.(21) Recently, elevated PLR was shown to be closely related to poor prognosis in various solid tumors.(22) Our study shows that PLR level elevation during the 6th week of ICI treatment was significantly associated with the initial response, PFS, and OS of ICI treatment. We should speculate that differences between studies in cancer type, demographic specialties, treatment modalities, sample size, and the threshold PLR value used to bisection may be responsible. In patients with NSCLC receiving predominately nivolumab or pembrolizumab, higher PLR has been correlated with worse OS.(23) A metanalysis of 12 studies reported that pretreatment PLR could be a routine potential prognostic factor and have a predictive role concerning the survival of patients with cancer treated with immunotherapy.(24) Another two studies related to NSCLC found no significant difference in survival between patients with NSCLC with high and low baseline PLR levels [15.4, 15.5].(25–26)

In 2018, Mezquita et al. (27) developed a new potential blood-based biomarker, LIPI, which stratified baseline dNLR and LDH, in patients with NSCLC under anti-PDL1 treatment according to survival outcomes. Previous studies indicated that LIPI could predict clinical outcomes across many tumor types, such as renal cell carcinoma, melanoma, small-cell lung cancer, and especially NSCLC; however, the prognostic value of LIPI remains a divisive issue. Mostly, the combination of baseline dNLR and LDH is correlated with resistance to ICI therapy in patients with advanced NSCLC. We also explored the predictive value of LIPI in these contexts. The present study shows that the intermediate LIPI group had significantly different response rates compared with the poor group during the 6th week of ICI treatment. Also, the poor LIPI group versus had worse OS and PFS with ICI treatment compared with the good group.

The LDH level is a known prognostic inflammatory marker in patients with cancer and has been widely studied in lung cancer treated with chemotherapy or patients with EGFR-mutant NSCLC. LDH was associated with DCR, PFS, and OS during the first month of erlotinib treatment.(28) Neutrophils are a crucial component of inflammation, playing an essential role in initiating tumorigenesis by damaging specific tissues. In cancer, neutrophils can promote or prevent tumor progression. Both increased and decreased neutrophil counts have been associated with tumor initiation.(29) Another mechanism is the neutrophil pro-inflammatory status, which induces uncontrolled granulopoiesis, releasing immature or poorly differentiated neutrophils, and has been associated with tumor progression.(30)

The exact mechanisms of inflammation related to prognosis remain unclear.(2) One of the suggested pathways should identify with GPS. There are increasing data showing the presence of patient-related factors, especially nutritional and functional status, associated with poorer outcomes in addition to the tumor stage. mGPS has been used as a biomarker to reflect the degree of cancer-associated inflammation and malnutrition. mGPS is a kind of systemic inflammatory response (SIR) based scoring system that combines the indicators of decreased plasma albumin and elevated CRP.(31) In our study, patients with higher mGPS showed impaired disease-free and OS. The mGPS has been evaluated as a prognostic parameter in accordance with findings in various malignancies.(32) Serum CRP levels, which are identified by activation of proinflammatory cytokines, might lead to tumor invasion, progression, and formation of metastases.(33) Most studies have shown a possible relationship between a chronic, systemic inflammatory response, compromised cellular immune response (34), and tumor cachexia (35), caused by low serum albumin.

Another aspect of our study is that the presenting site of metastasis was associated with the outcome of anti-PD-1 antibody treatment; liver metastasis (HR = 3.093, 95% CI: [1.017–9.405]; p = 0.047) was an independent prognostic indicator of shorter PFS. As we know, the liver has an immunologic organ interplay between immune tolerance and immune activation, which provides for the development of novel therapeutic strategies for cancer.(36) Kupfer cells, liver sinusoidal endothelial cells, dendritic cells play important roles in reducing the immune response and maintenance of immune-suppressive status.(37) The poor response and shorter PFS to anti-PD-1 antibody treatment in patients with liver metastases could be explained by the maintenance of immunotolerance.

In daily clinical practice, oncologists expect to quickly determine the treatment response because lung cancer usually develops extremely progressively in this state. The measurement of serum inflammatory parameters is noninvasive and inexpensive in the assessment of the efficacy of immunotherapy treatment in patients with lung cancer. Quickly rising inflammatory markers may be related to primary refractory disease, indicating a poorer prognosis. If posttreatment 6th-week NLR, PLR, LIPI, and mGPS ratio tend to reduce, this may reassure the physician that they are on the right track to directing the response and better survival.

Ethics approval and consent to participate
All procedures in the study which involved human participants were performed in accordance with the ethical standards of the institutional and/or national research committee, and also in accordance with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. All participants provided written informed consent for storage of medical information in the hospital database and use of this information for research purposes. . The Ethical Committee of the Burhan Nalbantoglu Government Hospital Review Board approved the study protocol (Approval Number:21/21) and written informed consent was obtained from participants.

Consent for publication

Not applicable.

Availability of data and materials

Data cannot be shared publicly because the data is owned and saved by Burhan Nalbantoglu Research hospital and Near East University hospital. Data are available from the Burhan Nalbantoglu Research Hospital Oncology Institutional Data Access/Ethics Committee (contact via Burhan Nalbantoglu Research Hospital Ethics Committee) for researchers who meet the criteria for access to confidential data: contact address, neareasthospital.com and bndh.gov.ct.tr.Datasets are available on request from the corresponding author upon reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

No funding.

Authors’ contributions

The authors are fully responsible for all content and editorial decisions, they were also involved at all stages of manuscript development and have approved the final version.

Acknowledgements

Special thanks are to all patients and involved investigator.

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No competing interests reported.

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Sixth-week immune-nutritional-inflammatory biomarkers: Can they predict clinical outcomes in patients with advanced non-small-cell lung cancer treated with immune checkpoint inhibitors?

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