Basal and one-month differed neutrophil, lymphocyte and platelet values and their ratios strongly predict the efficacy of checkpoint inhibitors immunotherapy in patients with advanced BRAF wild-type melanoma

Granulocytes and mast cells in AllergoOncology-Bridging allergy to cancer: An EAACI position paper

Derived from the myeloid lineage, granulocytes, including basophils, eosinophils, and neutrophils, along with mast cells, play important, often disparate, roles across the allergic disease spectrum. While these cells and their mediators are commonly associated with allergic inflammation, they also exhibit several functions either promoting or restricting tumor growth. In this Position Paper we discuss common granulocyte and mast cell features relating to immunomodulatory functions in allergy and in cancer. We highlight key mechanisms which may inform cancer treatment and propose pertinent areas for future research. We suggest areas where understanding the communication between granulocytes, mast cells, and the tumor microenvironment, will be crucial for identifying immune mechanisms that may be harnessed to counteract tumor development. For example, a comprehensive understanding of allergic and immune factors driving distinct neutrophil states and those mechanisms that link mast cells with immunotherapy resistance, might enable targeted manipulation of specific subpopulations, leading to precision immunotherapy in cancer. We recommend specific areas of investigation in AllergoOncology and knowledge exchange across disease contexts to uncover pertinent reciprocal functions in allergy and cancer and allow therapeutic manipulation of these powerful cell populations. These will help address the unmet needs in stratifying and managing patients with allergic diseases and cancer.

Hybridizing mechanistic modeling and deep learning for personalized survival prediction after immune checkpoint inhibitor immunotherapy

We present a study where predictive mechanistic modeling is combined with deep learning methods to predict individual patient survival probabilities under immune checkpoint inhibitor (ICI) immunotherapy. This hybrid approach enables prediction based on both measures that are calculable from mechanistic models of key mechanisms underlying ICI therapy that may not be directly measurable in the clinic and easily measurable quantities or patient characteristics that are not always readily incorporated into predictive mechanistic models. A deep learning time-to-event predictive model trained on a hybrid mechanistic + clinical data set from 93 patients achieved higher per-patient predictive accuracy based on event-time concordance, Brier score, and negative binomial log-likelihood-based criteria than when trained on only mechanistic model-derived values or only clinical data. Feature importance analysis revealed that both clinical and model-derived parameters play prominent roles in increasing prediction accuracy, further supporting the advantage of our hybrid approach.

Nomogram for predicting survival after first-line anti-PD-1-based immunotherapy in unresectable stage IV melanoma: a multicenter international study

BACKGROUND

The introduction of anti-programmed cell death protein 1 (PD-1) immunotherapy has revolutionized the treatment landscape for melanoma, enhancing both response rates and survival outcomes in patients with advanced stages of the disease. Despite these remarkable advances, a noteworthy subset of patients (40%-60%) does not derive advantage from this therapeutic approach. This study aims to identify key predictive factors and create a user-friendly predictive nomogram for stage IV melanoma patients receiving first-line anti-PD-1-based immunotherapy, improving treatment decisions.

MATERIALS AND METHODS

In this retrospective study, we included patients with unresectable stage IV melanoma who received first-line treatment with either anti-PD-1 monotherapy or anti-PD-1 plus anti-cytotoxic T-lymphocyte associated protein 4 between 2014 and 2018. We documented clinicopathological features and blood markers upon therapy initiation. By employing the random survival forest model and backward variable selection of the Cox model, we identified variables associated with progression-free survival (PFS) after the first-line anti-PD-1-based treatment. We developed and validated a predictive nomogram for PFS utilizing the identified variables. We assessed calibration and discrimination performance metrics as part of the evaluation process.

RESULTS

The study involved 719 patients, divided into a training cohort of 405 (56%) patients and a validation cohort of 314 (44%) patients. We combined findings from the random survival forest and the Cox model to create a nomogram that incorporates the following factors: lactate dehydrogenase (LDH), S100, melanoma subtype, neutrophil-to-lymphocyte ratio (NLR), body mass index, type of immune checkpoint inhibitor, and presence of liver or brain metastasis. The resultant model had a C-index of 0.67 in the training cohort and 0.66 in the validation cohort. Performance remained in different patient subgroups. Calibration analysis revealed a favorable correlation between predicted and actual PFS rates.

CONCLUSIONS

We developed and validated a predictive nomogram for long-term PFS in patients with unresectable stage IV melanoma undergoing first-line anti-PD-1-based immunotherapy.

Prognostic role of circulating cytokines and inflammation indexes for avelumab maintenance in metastatic urothelial carcinoma

Background

Avelumab maintenance after first-line platinum-based chemotherapy represents a cornerstone for the treatment of metastatic urothelial carcinoma (mUC). However, identifying prognostic biomarkers is paramount for optimizing patients' benefits while minimizing toxicity. Cytokines represent circulating mediators of the complex interaction between cancer, the immune system, and inflammation. Inflammation, a hallmark of cancer, can be expressed by circulating factors. In different tumor subtypes, peripheral blood biomarkers, such as circulating cytokines, and systemic inflammatory indexes, have been addressed as potential prognostic factors for immune checkpoint inhibitors. However, their role in mUC still needs to be determined.

Methods

Between February 2021 and April 2023, we prospectively collected plasma cytokines and inflammation indexes in 28 patients with mUC before starting avelumab as first-line maintenance. The primary endpoint was the relationship between baseline cytokines and inflammatory indexes with the clinical benefit (CB), defined as the number of Responders. Secondary endpoints included the correlation of baseline cytokines and inflammatory indexes with progression-free survival (PFS), overall survival (OS), and the number and grade of immune-related adverse events.

Results

High pre-treatment levels of interferon (IFN)-γ and interleukin (IL)-2, and low levels of IL-6, IL-8, neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and systemic-inflammation index (SII) were associated with clinical benefit and longer survival. In the multivariate analysis, low IL-8, NLR, and SII levels maintained a positive prognostic value for OS.

Conclusion

Our data suggest that, in mUC patients receiving avelumab, pre-treatment levels of plasma cytokines and inflammatory indexes may serve as potential prognostic biomarkers for response and efficacy. In particular, patients with signs of pre-therapeutic inflammation showed a significantly lower response and survival to avelumab. On the contrary, low systemic inflammation and high levels of cytokines characterized responders and longer survivors.

Immunotherapy in melanoma: Can we predict response to treatment with circulating biomarkers?

Melanoma is the most aggressive form of skin cancer, representing approximately 4% of all cutaneous neoplasms and accounting for up to 80% of deaths. Advanced stages of melanoma involve metastatic processes and are associated with high mortality and morbidity, mainly due to the rapid dissemination and heterogeneous responses to current therapies, including immunotherapy. Immune checkpoint inhibitors (ICIs) are currently used in the treatment of metastatic melanoma (MM) and despite being linked to an increase in patient survival, a high percentage of them still do not benefit from it. Accordingly, the number of therapeutic regimens for MM patients using ICIs either alone or in combination with other therapies has increased, together with the need for reliable biomarkers that can both predict and monitor response to ICIs. In this context, circulating biomarkers, such as DNA, RNA, proteins, and cells, have emerged due to their ability to reflect disease status. Moreover, blood tests are minimally invasive and provide an attractive option to detect biomarkers, avoiding stressful medical procedures. This systematic review aims to evaluate the possibility of a non-invasive biomarker signature that can guide therapeutic decisions. The studies reported here offer valuable insight into how circulating biomarkers can have a role in personalized treatments for melanoma patients receiving ICIs therapy, emphasizing the need for rigorous clinical trials to confirm findings and establish standardized procedures.

S100A9+CD14+ monocytes contribute to anti-PD-1 immunotherapy resistance in advanced hepatocellular carcinoma by attenuating T cell-mediated antitumor function

BACKGROUND

The paucity of reliable biomarkers for predicting immunotherapy efficacy in patients with advanced hepatocellular carcinoma (HCC) has emerged as a burgeoning concern with the expanding use of immunotherapy. This study endeavors to delve into the potential peripheral biomarkers capable of prognosticating efficacy in HCC patients who are poised to receive anti-PD-1 monotherapy within the phase III clinical trial, KEYNOTE394. Additionally, we sought to elucidate the underlying molecular mechanisms for resistance to immune checkpoint blockade (ICB) and propose innovative combination immunotherapy strategies for future clinical application.

METHODS

Patient blood samples were collected for single-cell RNA sequencing to evaluate the immune cell signature before receiving ICB therapy. Subsequently, in vitro assays and in vivo murine model experiments were conducted to validate the mechanism that S100A9+CD14+ monocytes play a role in ICB resistance.

RESULTS

Our study demonstrates a notable enrichment of S100A9+CD14+ monocytes in the peripheral blood of patients exhibiting suboptimal responses to anti-PD-1 therapy. Moreover, we identified the Mono_S100A9 signature as a predictive biomarker, indicative of reduced efficacy in immunotherapy and decreased survival benefits across various tumor types. Mechanistically, S100A9 activates PD-L1 transcription by directly binding to the CD274 (PD-L1) gene promoter, thereby suppressing T-cell proliferation and cytotoxicity via the PD-1/PD-L1 axis, consequently diminishing the therapeutic effectiveness of subsequent anti-PD-1 treatments. Furthermore, our in vivo studies revealed that inhibiting S100A9 can synergistically enhance the efficacy of anti-PD-1 drugs in the eradication of hepatocellular carcinoma.

CONCLUSIONS

Our study underscores the significance of S100A9+CD14+ monocytes in predicting inadequate response to ICB treatment and provides insights into the monocyte cell-intrinsic mechanisms of resistance to ICB therapy. We also propose a combined therapeutic approach to enhance ICB efficacy by targeting S100A9.

Neutrophil-to-lymphocyte ratio (NLR) predicts mortality in hospitalized geriatric patients independent of the admission diagnosis: a multicenter prospective cohort study

BACKGROUND

The Neutrophil-to-lymphocyte ratio (NLR) is a marker of poor prognosis in hospitalized older patients with different diseases, but there is still no consensus on the optimal cut-off value to identify older patients at high-risk of in-hospital mortality. Therefore, in this study we aimed at both validating NLR as a predictor of death in older hospitalized patients and assess whether the presence of specific acute diseases can modify its predictive value.

METHODS

This prospective cohort study included 5034 hospitalizations of older patients admitted to acute care units in the context of the ReportAge study. NLR measured at admission was considered as the exposure variable, while in-hospital mortality was the outcome of the study. ROC curves with Youden's method and restricted cubic splines were used to identify the optimal NLR cut-off of increased risk. Cox proportional hazard models, stratified analyses, and Kaplan-Meier survival curves were used to analyse the association between NLR and in-hospital mortality.

RESULTS

Both continuous and categorical NLR value (cut-off ≥ 7.95) predicted mortality in bivariate and multivariate prognostic models with a good predictive accuracy. The magnitude of this association was even higher in patients without sepsis, congestive heart failure, and pneumonia, and those with higher eGFR, albumin, and hemoglobin (p < 0.001). A negative multiplicative interaction was found between NLR and eGFR < 45 (p = 0.001).

CONCLUSIONS

NLR at admission is a readily available and cost-effective biomarker that could improve identification of geriatric patients at high risk of death during hospital stay independent of admitting diagnosis, kidney function and hemoglobin levels.

Neutrophil-lymphocyte ratio and platelet-lymphocyte ratio as potential predictive markers of treatment response in cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis

Background

The role of platelet-lymphocyte ratio (PLR) and neutrophil-lymphocyte ratio (NLR) as independent prognostic markers in different tumors is well established. However, there is a limited review of the potential of NLR and PLR as predictors of treatment outcomes from immune checkpoint inhibitors (ICIs).

Objective

To establish a correlation between NLR and PLR and the potential of clinical benefit from ICIs.

Methods

The literature search was performed for studies that reported the association between NLR, PLR, and treatment outcomes among cancer patients treated with ICIs. The outcomes of interest were objective response rate (ORR), disease control rate (DCR), and progressive disease (PD). ORR was the summation of patients who achieved complete response and partial response. DCR included patients who achieved stable disease. PD was the proportion of patients who progressed, relapsed, or discontinued the treatment. Statistical analysis was performed using the STATA 12.0 package. Heterogeneity was determined by the I2 value. Quality assessment was performed using the Newcastle-Ottawa Scale. Egger's test was used to establish publication bias and sensitivity analysis.

Results

A total of 40 papers that met the inclusion criteria were included in the systematic review. However, only 17 studies were used in the meta-analysis to determine the correlation between NLR, PLR, and treatment response. We found that treatment with ICIs and monitoring of outcomes and adverse events using PLR and NLR parameters have been studied in different tumors. Our analysis showed that low NLR correlated with higher ORR (OR = 0.62 (95% CI 0.47-0.81, p = 0.001) and higher DCR (OR = 0.23, 95% CI 0.14-0.36, p < 0.001). Higher NLR predicted a higher probability of PD (OR = 3.12, 95% CI 1.44, 6.77, p = 0.004). Similarly, low PLR correlated with higher ORR (OR = 0.69, 95% CI 0.5, 0.95, p = 0.025). Generally, patients with low NLR and PLR were more likely to achieve clinical benefit and better response (p-value < 0.001). Meanwhile, patients with high ratios were more likely to progress (p-value < 0.005), although there was significant heterogeneity among studies. There was no significant publication bias observed.

Conclusion

The study showed that high NLR and PLR either at baseline or during treatment is associated with poorer treatment outcome. Therefore, these ratios can be utilized in clinical practice with other markers to determine treatment efficacy from immunotherapy.

CD39 and LDHA affects the prognostic role of NLR in metastatic melanoma patients treated with immunotherapy

BACKGROUND

Identifying response markers is highly needed to guide the treatment strategy in patients with metastatic melanoma.

METHODS

A retrospective study was carried out in patients with unresectable/metastatic melanoma (stage IIIb-IV), treated with anti-PD-1 in the first line setting, to better explore the role and the timing of neutrophil/lymphocyte ratio (NLR) as potential biomarker of response. The relationship of NLR with inflammation-immune mediators and the underlying negative effect of raising NLR during immunotherapy, have been investigated with transcriptomic gene analysis.

RESULTS

The results confirmed previous findings that a high baseline NLR is associated with a poorer prognosis and with higher serum level of lactate dehydrogenase (LDH), regardless of the presence of brain metastases. The transcriptomic analysis showed that high baseline NLR is associated with a characteristic gene signature CCNA1, LDHA and IL18R1, which correlates with inflammation and tumorigenesis. Conversely, low baseline NLR is associated with the signature CD3, SH2D1A, ZAP70 and CD45RA, linked to the immune-activation. The genes positively associated with NLR (CD39 (ENTPD1), PTEN, MYD88, MMP9 and LDH) are involved in processes of immunosuppression, inflammation and tumor-promoting activity. Increased expression of CD39 correlated with TGFβ2, a marker of the N2 neutrophils with immunosuppressive activity.

CONCLUSIONS

These results suggest that increasing NLR is associated with an increased neutrophil population, with polarization to the N2 phenotype, and this process may be the basis for the negatively prognostic role of NLR.

Features and Long-Term Outcomes of Stage IV Melanoma Patients Achieving Complete Response Under Anti-PD-1-Based Immunotherapy

BACKGROUND

Immune checkpoint inhibition (ICI) has changed the melanoma treatment spectrum. Few studies have examined the characteristics and long-term outcomes of patients achieving complete response (CR) under ICI.

MATERIALS AND METHODS

We evaluated patients with unresectable stage IV melanoma treated with first-line ICI. The characteristics of those achieving CR were compared with those not achieving CR. Progression-free survival (PFS) and overall survival (OS) were assessed. Late-onset toxicities, response to second-line treatment, the prognostic value of clinicopathologic features, and blood markers were examined.

RESULTS

A total of 265 patients were included; 41 (15.5%) achieved CR, while 224 (84.5%) had progressive disease, stable disease, or partial response. At the therapy start, those who had CR were more likely to be older than 65 years of age (p = 0.013), have a platelet-to-lymphocyte ratio below 213 (p = 0.036), and have lower lactate dehydrogenase levels (p = 0.008) than those not achieving a CR. For those who discontinued therapy after CR, the median follow-up time after CR was 56 months (interquartile range [IQR] 52-58) and the median time from CR to therapy end was 10 months (IQR 1-17). Five-year PFS after CR was 79% and 5-year OS was 83%. Most complete responders had a normalization of S100 at the time of CR (p < 0.001). In simple Cox regression analysis, age below 77 years at CR (p = 0.04) was associated with better prognosis after CR. Eight patients received second-line ICI; disease control was seen in 63%. Late immune-related toxicities occurred in 25% of patients, most being cutaneous immune-related toxicities.

CONCLUSIONS

Response, according to the Response Evaluation Criteria in Solid Tumors (RECIST) criteria, is, until now, the most important prognostic factor, and CR is a valid surrogate marker for long-term survival in patients treated with ICI. Our results highlight the importance of investigating the optimal therapy duration in complete responders.

Preoperative Neutrophil-to-Lymphocyte Ratio and a New Inflammatory Biomarkers Prognostic Index for Primary Retroperitoneal Sarcomas: Retrospective Monocentric Study

PURPOSE

Inflammatory biomarkers and neutrophil-to-lymphocyte ratio (NLR) are associated with prognosis in several tumors. Data on sarcomas are limited, and insufficient on retroperitoneal sarcoma (RPS).

EXPERIMENTAL DESIGN

Patients with primary RPS operated between 2002 and 2016 were included. Hemoglobin, monocytes, NLR, platelet-to-lymphocyte ratio (PLR) were retrieved and analyzed both individually and combined into a prognostic index (IBPI). Correlation with clinicopathologic variables was studied, as well as postoperative morbidity according to NLR and IBPI risk categories. The association between overall survival (OS) and biomarkers and, in addition, the 7-year Sarculator-predicted OS probability (pOS) was analyzed using univariable and multivariable Cox models.

RESULTS

423/463 patients had complete data. The median follow-up was 84 months. The median NLR was 3.3 (IQR, 2.4-4.7), with significant variation across histologies. NLR was the only biomarker that independently predicted OS (HR, 1.2; 95% CI, 1.03-1.40; P = 0.02). The IBPI showed good discrimination for subgroups at different OS (log-rank test P < 0.0001). The Cox model for pOS alone showed a 7-year index of prediction accuracy of 26.9, which increased to 29.5 when IBPI was added to pOS as a complementary prognostic tool. IBPI was also associated with the risk of serious infectious postoperative complications (P = 0.0094; noninfectious complications, P = 0.6463).

CONCLUSIONS

NLR was an independent prognostic factor for OS in RPS. When combined into a prognostic index with hemoglobin, monocytes, and PLR, it serves as a readily available prognostic tool addressing tumor-related inflammation and helps in classifying RPS risk in addition to the Sarculator nomogram.

Body mass index and baseline platelet count as predictive factors in Merkel cell carcinoma patients treated with avelumab

Background

Merkel cell carcinoma (MCC) is a rare and aggressive skin cancer, associated with a worse prognosis. The Immune Checkpoint Inhibitors (ICIs) avelumab and pembrolizumab have been recently approved as first-line treatment in metastatic MCC (mMCC). The clinical observation of improved outcomes in obese patients following treatment with ICIs, known as the "obesity paradox", has been studied across many types of tumors. Probably due to the rarity of this tumor, data on mMMC patients are lacking.

Patients and methods

This is an observational, hospital-based, study to investigate the role of Body Mass Index (BMI) as predictive biomarker of ICI response in mMCC patients treated with avelumab as first-line treatment. The study population included the patients treated from February 2019 to October 2022 in an Italian referral center for rare tumors. Clinico-pathological characteristics, BMI, laboratory parameters (NLR and platelet count), and response to avelumab were analyzed from a MCC System database prospectively collected.

Results

Thirty-two (32) patients were included. Notably, the presence of pre-treatment BMI ≥ 30 was significantly associated with longer PFS [BMI < 30 Group: median PFS, 4 months (95% CI: 2.5-5.4); BMI ≥ 30 Group: median PFS, not reached; p<0.001)[. Additionally, the median PFS was significantly higher in patients with higher PLT (median PFS: 10 months in the "low PLT" Group (95% CI: 4.9, 16.1) vs 33 months (95% CI: 24.3, 43.2) in the "high PLT" Group (p=0.006). The multivariable Cox regression model confirmed these results.

Conclusion

To our knowledge, this is the first study that investigates the predictive role of BMI in MCC patients. Our data were consistent with the clinical observation of improved outcomes in obese patients across other tumor types. Thus, advanced age, a weakened immune system, and the obesity-associated "inflammaging", are key factors that could impact the cancer immune responses of mMCC patients.

Baseline neutrophil-to- ratio combined with the change during treatment provides risk stratification for metastatic malignant melanoma patients treated with PD-1 inhibitors in a Chinese population

Background

Previous studies have suggested that an elevated baseline neutrophil-to-lymphocyte ratio (BLNLR) and elevated relative change of NLR (ΔNLR%) is associated with worse outcomes in patients with a variety of cancers. This study aims to investigate the value of BLNLR and ΔNLR% before the third cycle of treatment on the prognosis of patients with metastatic malignant melanoma treated with PD-1 inhibitors.

Methods

A total of 63 patients with metastatic malignant melanoma treated with PD-1 inhibitors in the First Affiliated Hospital of Zhengzhou University from January 2017 to December 2021 were retrospectively analyzed. BLNLR and ΔNLR% before the third cycle of treatment were collected. The Kaplan-Meier method was used to draw survival curves and Log-Rank test was used for survival analysis. Univariate and multivariate Cox regression analysis were used to analyze the relationship between BLNLR, ΔNLR% and clinical characteristics with progression-free survival (PFS) and overall survival (OS).

Results

Univariate analysis showed that PFS and OS were associated with BLNLR, ΔNLR%, BMI and number of metastatic organs (P < 0.05). Multivariate analysis showed that BLNLR, ΔNLR%, BMI and number of metastatic organs were independent predictors of OS and BLNLR and ΔNLR% were independent predictors of PFS. Patients were divided into four groups according to BLNLR (<3, ≥3) and ΔNLR% (< 30%, ≥30%): low-BLNLR + low-ΔNLR% group, low-BLNLR + high-ΔNLR% group, high-BLNLR + low-ΔNLR% group, high-BLNLR + high-ΔNLR% group. The median OS was 20 months, 8 months, 9 months, 5 months and the median PFS was 8 months, 3 months, 2 months, 2 months, respectively.

Conclusion

BLNLR combined with ΔNLR% can be used to predict the prognosis of PD-1 inhibitors in patients with metastatic malignant melanoma.

Granulocyte Apheresis: Can It Be Associated with Anti PD-1 Therapy for Melanoma?

In the field of advanced melanoma, there is an urgent need to investigate novel approaches targeting specific components of the cancer–immunity cycle beyond immune checkpoint inhibitors. The authors reviewed the basic understanding of the role of neutrophils in cancer biology, and the latest clinical evidence supporting the correlation between cancer-associated neutrophils and the prognosis and response to the immunotherapy of advanced melanoma. Finally, they propose that granulocyte and monocyte apheresis, an emerging non-pharmacological treatment in current dermatology, could become an investigative treatment targeting melanoma-associated neutrophils which could be potentially used in combination with the usual immune checkpoint inhibitors.

The Association between Early Changes in Neutrophil-Lymphocyte Ratio and Survival in Patients Treated with Immunotherapy

Dynamic changes in the blood-based biomarkers could be used as a prognostic biomarker in patients treated with immune checkpoint inhibitors (ICIs), although the data are limited. We evaluated the association between the neutrophil−lymphocyte ratio (NLR) and early NLR changes with survival in ICI-treated patients. We retrospectively evaluated the data of 231 patients with advanced-stage cancer. We recorded baseline clinical characteristics, baseline NLR and fourth-week NLR changes, and survival data. A compound prognostic score, the NLR2-CEL score, was developed with the following parameters: baseline NLR (<5 vs. ≥5), ECOG status (0 vs. ≥1), Charlson Comorbidity Index (CCI, <9 vs. ≥9), LDH (N vs. ≥ULN), and fourth-week NLR change (10% or over NLR increase). In the multivariable analyses, higher NLR (HR: 1.743, p = 0.002), 10% or over NLR increase in the fourth week of treatment (HR: 1.807, p = 0.001), higher ECOG performance score (HR: 1.552, p = 0.006), higher LDH levels (HR: 1.454, p = 0.017), and higher CCI (HR: 1.400, p = 0.041) were associated with decreased OS. Compared to patients with the lowest scores, patients in the highest score group had significantly lower OS (HR: 7.967, 95% CI: 3.531−17.979, p < 0.001) and PFS. The composite score had moderate success for survival prediction, with an AUC of 0.702 (95% CI: 0.626−0.779, p < 0.001). We observed significantly lower survival in patients with higher baseline NLR values and increased NLR values under treatment.