Prognostic value of the neutrophil‑to‑lymphocyte ratio in renal cell carcinoma: A systematic review and meta‑analysis
- Authors:
- Published online on: March 13, 2025 https://doi.org/10.3892/ol.2025.14977
- Article Number: 231
-
Copyright: © Lou et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
According to the American Cancer Society, Renal cell carcinoma (RCC) is the most common malignant kidney tumor type in the United States, ranking sixth among cancer types in men and tenth in women, accounting for 5 and 3% of all tumor diagnoses, respectively; its incidence is on the rise (1,2). Despite advances in diagnostic and therapeutic techniques in recent years, a significant proportion of patients are still diagnosed with locally advanced disease and 17% of patients present with distant metastases at diagnosis, leading to a poor prognosis (3). Although radical or partial nephrectomy is the standard surgical treatment for patients with non-metastatic RCC, the prognosis for patients remains poor, especially for those with regional or distant advanced disease (2,4). In addition, immune checkpoint inhibitors (ICIs) and combination therapies have notably changed the treatment landscape of advanced renal cancer, but there are still some limitations in their application, such as heterogeneity in efficacy, immune-related adverse events and drug resistance (5). Therefore, identifying a reliable prognostic marker is crucial for individualized risk assessment and adjustment of treatment strategies. In previous years, increasing evidence has suggested that blood-based inflammatory markers, particularly the neutrophil-to-lymphocyte ratio (NLR), can predict the prognosis of patients with RCC (6–9).
The relationship between inflammatory responses and cancer has garnered significant attention in recent years (10,11). Due to their low cost and easy accessibility, hematological inflammatory markers, such as the NLR, have been widely tested (12). NLR, a simple and readily available inflammatory marker, is closely related to systemic inflammation (13), and has been widely used in prognostic studies of various cancer types, such as colorectal (14), prostate (15), uroepithelial (16), penile (17), lung (18) and breast (19) cancer. NLR is linked to poorer outcomes in multiple cancer types, including penile, colorectal, bladder, lung, breast, throat and ovarian cancer (17,20–25), and high NLR levels often predict poorer survival. Several meta-analyses have already explored the prognostic value of NLR in patients with RCC, with existing research indicating that a high NLR is associated with a poor prognosis (8,26). Despite this, most studies suffer from several problems, such as small sample sizes or single-center studies, or being limited to a single hospital or region, limiting their external validity and wide applicability. There are also inconsistent conclusions, with some studies finding a significant correlation between NLR and RCC prognosis (27,28), while others failed to reach a clear conclusion (29–31).
The present study included the most recent articles, thus ensuring the timeliness and reliability of the conclusions. The role of NLR in the prognosis of RCC, especially its predictive value for patient survival, recurrence and disease progression, was further clarified in the present study to provide a more up-to-date and accurate prognostic assessment.
Materials and methods
Search strategy
Multiple databases, including PubMed (https://pubmed.ncbi.nlm.nih.gov/), Embase (https://www.embase.com/), Cochrane Library (https://www.cochranelibrary.com/) and Web of Science (http://webofscience.com) were searched for all relevant studies published from July 2021 to August 2024. The main terms used in the search strategy included the following: (‘renal’ or ‘kidney’) and (‘carcinoma’ or ‘neoplasms’ or ‘cancer’ or ‘tumor’) and (‘NLR’ or ‘neutrophil-lymphocyte ratio’ or ‘neutrophil-to-lymphocyte ratio’). No language restrictions were applied in the literature search to ensure the comprehensiveness of the included studies. Some studies [such as Asif et al (32)] have multiple sets of data; therefore, in some analyses, certain studies are included >1 in the analysis.
Inclusion and exclusion criteria
Studies were selected based on the following inclusion criteria: i) Prospective or retrospective cohort studies that evaluated the relationship between NLR and overall survival (OS), recurrence-free survival (RFS), progression-free survival (PFS) and cancer-specific survival (CSS) in patients with RCC. The NLR values were taken before, during and after treatment. Most studies collected NLR within the first 30 days of treatment, while the study by Asif et al (32) included preoperative, perioperative and postoperative NLR; ii) the included patients had not received any treatment other than tumor-specific therapy prior to sample collection; and iii) studies that directly provided hazard ratios (HRs) with 95% confidence intervals (CIs) or had sufficient data to calculate these statistics. If study data were duplicated, only the data from the most recent study were used. The following exclusion criteria were applied: i) Studies that did not provide sufficient survival data for further analysis; ii) duplicate studies or publications; and iii) expert opinions, conference abstracts, editorials, case reports, letters, reviews or meta-analyses.
Date extraction
For each eligible study, two authors independently extracted the following items: Study characteristics (first author's name, recruitment region, publication year, study type and sample size), patient information (sex, age and ethnicity), pathological characteristics [TNM stage and histological subtype (33)], disease type (localized or metastatic), NLR cut-off values (number and/or percentage of patients with high vs. low NLR), clinical characteristics (treatment strategy, patient survival outcomes and follow-up duration), and OS, RFS, PFS and CSS outcomes. In cases of disagreement, consensus was reached through discussion with a third researcher.
Quality assessment
The quality of each included study was assessed using the Newcastle-Ottawa Scale (NOS), which comprises three factors: Selection, comparability and exposure (34). The highest possible NOS score is 9, with studies scoring ≥7, 4–6 and <4 being considered to have a low, medium and high risk of bias, respectively. Disputes regarding the quality assessment were resolved through discussion with a third reviewer.
Statistical analysis
The primary endpoints of the present meta-analysis were OS, RFS, PFS and CSS for all patients with RCC. If the included studies directly reported survival analyses, HRs and 95% CIs were extracted to calculate the pooled HR; otherwise, these data were calculated and estimated from Kaplan-Meier survival curves using Engauge Digitizer software (version 4.1; http://engauge-digitizer.updatestar.com/en) (35,36). Cochran's Q test and the I2 statistic were used to assess heterogeneity among the included studies (37). The present systematic review followed the Cochrane Handbook for Evaluation of Intervention Systems, and all analyses used only the random-effects model. Sensitivity analysis was conducted by omitting each study one-by-one to evaluate the stability of the results. Subgroup analysis was also performed to explore the potential sources of heterogeneity. Additionally, funnel plots and Egger's test were used to assess the risk of publication bias. Egger's test and the trim-and-fill method were conducted using Stata 12.0 software (StataCorp LP). Other statistical analyses were performed using Review Manager 5.3 software (Cochrane Collaboration). All P-values were two-sided, and P<0.05 was considered to indicate a statistically significant difference.
Quality of evidence
The quality of evidence regarding the prognostic value of pre-treatment NLR for patients with RCC was evaluated using the Grading of Recommendations Assessment, Development and Evaluation system (38).
Results
Included literature
Based on the search strategy, 356 potentially relevant records were identified. After removing duplicates, the titles and abstracts of the remaining 288 records were reviewed. The full texts of 68 records that met the inclusion criteria were then assessed. Ultimately, 21 studies were included in the present meta-analysis (7,27–32,39–52). The study selection process is illustrated in a flow diagram presented in Fig. 1.
Study characteristics
A total of 4,459 patients with RCC were included in the present meta-analysis. Table I presents the main characteristics of the 21 included studies, which were published between 2021 and 2024. Among the 21 studies, 7 reported on localized/non-metastatic RCC, while 11 focused on metastatic RCC and 3 on mixed RCC. Additionally, of the 21 studies, 18 reported OS data, 6 reported RFS or PFS data and 6 reported CSS data. The histological types included clear cell RCC, papillary RCC, non-clear cell RCC and mixed types. The cut-off values for NLR ranged from 2.33 to 4.0. The HRs and 95% CIs for the 21 studies were derived from multivariate Cox regression analyses and Kaplan-Meier survival curves. The mean age of the patients ranged from 57 to 73 years and the mean follow-up period ranged from 15.3 to 93.5 months. The NOS scores were 7 or 8, indicating that the included studies were of a moderate to high quality (Table SI).
NLR and OS in RCC
In total, 18 studies involving 3,867 patients with RCC assessed the association between NLR and OS. The forest plot utilizing a random-effects model to investigate the association between NLR and OS demonstrated that in the overall population, a high NLR was significantly associated with a shorter OS time (HR, 2.00; 95% CI, 1.50-2.65; P<0.00001; Fig. 2A). To explore whether individual studies influenced the heterogeneity and conclusions, a sensitivity analysis was conducted by sequentially excluding each study. After excluding the study by Wang et al (45), the heterogeneity among the RCC studies decreased (I2=41%, P<0.00001; Fig. 2D). Overall, the sensitivity analysis results did not alter the above conclusions, confirming the robustness of the findings.
When evaluating the relationship between NLR and OS in non-metastatic RCC, 4 studies that included 1,761 patients were examined. In 11 studies involving 1,426 patients with metastatic RCC, a similar relationship between NLR and OS was observed. The meta-analysis showed that a high NLR was significantly associated with poorer OS in both patients with non-metastatic (HR, 2.98; 95% CI, 2.13–4.18; P<0.00001; I2=0%; Fig. 3C) and metastatic RCC (HR, 1.67; 95% CI, 1.11–2.50; P=0.001; I2=79%; Fig. 3A). Notably, heterogeneity remained significant in the metastatic RCC population (I2=79%, P=0.001; Fig. 3A). The results indicated that the studies by Wang et al (45), Tucker et al (29) and Aslan et al (51) (Fig. 3A) influenced the heterogeneity. Therefore, a sensitivity analysis was performed in patients with metastatic RCC. The results showed that excluding any single study, except for the study by Wang et al (45), did not significantly affect the heterogeneity. However, after removing the study by Wang et al (45), there was a significant effect on heterogeneity (Fig. 3E).
Due to the involvement of different study characteristics, subgroup analyses to explore the potential sources of heterogeneity in the metastatic RCC cohort were further performed after excluding the study by Wang et al (45) (Table II). In the subgroup analysis based on sample size, heterogeneity was higher in patients with clear cell RCC (HR, 1.63; 95% CI, 0.51–5.16; P=0.41; I2=86%) and Caucasian patients (HR, 2.29; 95% CI, 1.09–4.81; P=0.03; I2=76%). Therefore, the main sources of heterogeneity may be histological type (clear cell carcinoma) and ethnicity (Caucasian population), as these factors had the highest I2 values, indicating the greatest variability in study results under these conditions.
When evaluating the relationship between NLR and OS in patients with RCC who underwent only surgical treatment, there were 7 relevant studies but the study by Asif et al (32) contained 3 datasets with different patient cohorts (preoperative, intraoperative and postoperative) and these datasets were therefore included in the analysis separately. Thus, 9 studies/cohorts involving 2,043 surgically treated patients were examined. In 5 studies involving 893 patients with non-surgically treated RCC, a similar relationship between NLR and OS was observed. The meta-analysis showed that a high NLR was significantly associated with poorer OS in both patients with surgically (HR, 1.99; 95% CI, 1.40–2.85; P=0.0001; I2=62%; Fig. 4A) and non-surgically (HR, 2.07; 95% CI, 1.33–3.21; P=0.001; I2=47%; Fig. 4C) treated RCC. Notably, heterogeneity remained significant in the surgically treated RCC population (Fig. 4A). Therefore, a sensitivity analysis was conducted for studies analyzing patients with surgically treated RCC. The results indicated that the study by Tucker et al (29) influenced the heterogeneity, and after excluding this study, the heterogeneity among the studies decreased (I2=0%, P<0.00001; Fig. 4E). Overall, the sensitivity analysis results did not alter the aforementioned conclusions, confirming the robustness of the findings.
NLR and RFS/PFS in RCC
Due to the potential overlap in biological significance between RFS and PFS in specific clinical contexts (such as postoperative adjuvant therapy for solid tumors), and since some studies did not strictly distinguish between these endpoints, RFS and PFS were combined in this analysis. Additionally, merging the two endpoints improved statistical power and reduced bias from small sample sizes when individual analyses of RFS or PFS were infeasible. When examining the association between NLR and RFS/PFS, 11 studies involving 2,648 patients were selected. The forest plot of the meta-analysis showed that a high NLR was associated with poorer RFS/PFS in the overall population (HR, 1.70; 95% CI, 1.38–2.10; P<0.00001; I2=18%; Fig. 2B).
Upon further assessment of the relationship between NLR and PFS in patients with metastatic RCC, a meta-analysis based on 6 studies involving 826 patients indicated that a high NLR was significantly associated with poorer PFS (HR, 1.52; 95% CI, 1.22–1.89; P=0.0002; I2=10%; Fig. 3B). Regarding the relationship between NLR and RFS in patients with non-metastatic RCC, 5 studies involving 1,822 patients were examined. The forest plot showed that a high NLR was significantly associated with poorer RFS (HR, 2.14; 95% CI, 1.54–2.98; P<0.00001; I2=0%; Fig. 3D).
When the relationship between NLR and RFS/PFS in patients with RCC who underwent only surgical treatment was examined, 5 studies involving 1,515 patients were included. The forest plot showed that a high NLR was significantly associated with poorer RFS/PFS (HR, 1.83; 95% CI, 1.25–2.69; P=0.002; I2=44%; Fig. 4B). For the relationship between NLR and RFS/PFS in patients with RCC who did not undergo surgery, based on 5 studies involving 1,095 patients, the forest plot showed that a high NLR was significantly associated with poorer RFS/PFS (HR, 1.64; 95% CI, 1.28–2.10; P<0.0001; I2=0%; Fig. 4D).
NLR and CSS in RCC
In total, 6 studies involving 1,404 patients reported data on the association between NLR and CSS. The forest plot of the meta-analysis indicated that a high NLR was significantly associated with poorer CSS (HR, 3.81; 95% CI, 1.63–8.94; P=0.002; I2=75%; Fig. 2C). Of these 6 included studies, 3 studies involved non-metastatic RCC, 1 study involved metastatic RCC and 2 studies involved mixed type. Therefore, the association between NLR and CSS in patients with non-metastatic and metastatic RCC was not further investigated separately.
Additionally, a sensitivity analysis was conducted to explore whether any single study influenced heterogeneity and the overall conclusion. After excluding the preoperative cohort in the study by Asif et al (32), the heterogeneity among the non-metastatic RCC studies notably changed (I2=42%, P<0.0001; Fig. 2E). However, the recalculated HR did not alter the aforementioned conclusions, confirming the robustness of the results.
OS and RFS/PFS in patients treated with ICIs
The prognostic value of NLR in patients with RCC who were treated exclusively with ICIs was also examined. In examining the relationship between NLR and OS in patients with RCC treated with ICIs only, 4 studies involving 761 patients were included. The results of the meta-analysis showed that high NLR was associated with poorer OS (HR, 2.05; 95% CI, 1.05–3.99; P=0.04; I2=60%; Fig. 5A). In examining the relationship between NLR and RFS/PFS in patients with RCC treated with ICIs only, 5 studies involving 1,095 patients were included. The results of the meta-analysis showed that high NLR was associated with poorer RFS/PFS (HR, 1.64; 95% CI, 1.28–2.10; P=0.001; I2=0%; Fig. 5B).
Publication bias
The publication bias for OS, RFS/PFS and CSS was assessed without considering the staging of patients with RCC. For OS and CSS, the funnel plots were asymmetric (Fig. S1A and B). Egger's test also indicated the presence of publication bias (both P<0.001). Therefore, the trim-and-fill method was employed to test the asymmetry of the funnel plot by hypothesizing the existence of unpublished studies. The recalculated results demonstrated that a high NLR was significantly associated with OS and CSS, with statistical significance (P<0.05) after trimming and filling. Furthermore, the combined results before and after trimming had P<0.05, suggesting the stability of the results (Fig. S2A and B). For RFS/PFS, the funnel plot was relatively symmetric (Fig. S1C). Additionally, Egger's test showed no significant publication bias (P=0.667).
Discussion
Inflammatory factors in the human body have a crucial role in the occurrence, development and prognosis of tumors (53). The inflammatory response is a defense mechanism of the body against injury and infection, but chronic inflammation can induce abnormal cell proliferation, DNA damage and immune escape, thereby promoting the occurrence and development of tumors (53,54). Inflammatory factors in the tumor microenvironment, such as tumor necrosis factor-α, interleukins (such as IL-6 and IL-1β) and C-reactive protein (55–57), not only participate in the proliferation, invasion and metastasis of tumor cells but also affect the tumor's response to treatment. Therefore, the levels of inflammatory factors are often closely related to the prognosis of patients with cancer, with higher levels often indicating a poorer clinical prognosis (53,58). Investigating the mechanisms by which inflammatory factors affect tumors can help reveal the patterns of tumor occurrence and development, and provide new insights and targets for early diagnosis, personalized treatment and the prognosis assessment of tumors.
NLR is a simple and reliable marker that can be used to predict immune responses to infectious and non-infectious stimuli and serves as a reliable indicator of cancer-associated inflammation, as well as a predictor of tumor survival and treatment outcomes (59,60). NLR has an important role in the prognosis of RCC. This may be due to the fact that NLR reflects the inflammatory response of the body, which serves a notable role in tumor progression and metastasis (8). The present study systematically evaluated the impact of NLR on the prognosis of patients with RCC through a systematic review and meta-analysis of 4,459 patients. The results showed that a high NLR was significantly associated with a poor OS, RFS/PFS and CSS in patients with RCC. Additionally, the results of the present study indicated that a high NLR was significantly associated with a poor OS and RFS/PFS in patients with RCC, regardless of the metastasis status or treatment type. In the meta-analysis of metastatic RCC, the association between NLR and OS demonstrated significant heterogeneity (I2=79%). Despite sensitivity analyses, the heterogeneity remained high. To further investigate the source of heterogeneity, subgroup analyses based on the characteristics of the included studies were performed, which demonstrated the stability and reliability of the results. Overall, the results from the pooled data of the present systematic review and meta-analysis suggest that NLR may be used as a prognostic indicator for patients with RCC, aiding in clinical decision-making and the selection of individualized treatment strategies.
Neutrophils are a key component of the acute phase of inflammation and are associated with cancer development. Neutrophils can directly influence tumor cells, promoting cancer progression, and indirectly modify the tumor microenvironment to facilitate cancer metastasis (61). Moreover, neutrophils can release vascular endothelial growth factor, affecting tumor development (60,62). By contrast, lymphocytes have an important role in the antitumor immune response. Increased lymphocyte infiltration in the tumor region is associated with improved responsiveness to treatment and prognosis in patients with solid tumors (60). Additionally, lymphopenia (reduction in CD4+ T cells) can impair lymphocyte-mediated antitumor responses (63). Therefore, NLR not only reflects the patient's inflammatory response but also represents a decrease in antitumor immunity, with elevated NLR often indicating lower survival rates and more aggressive disease in patients with cancer.
The results of the present study align with several others (26,64–68), indicating that patients with high NLR typically have poorer outcomes, which further underscores the potential clinical value of NLR. This similarity may be attributed to the use of the same inclusion criteria and measurement tools in all studies, as well as the comparable sample sizes, which likely led to the consistency of the findings. Moreover, these similar results provide a solid evidence base for future research, as NLR, a simple and easily obtainable inflammatory marker, has been repeatedly validated in various studies as being closely associated with patient prognosis. Looking ahead, multicenter prospective studies are needed to further confirm the applicability and feasibility of NLR in different populations. For patients with high NLR, future clinical research could explore interventions such as anti-inflammatory treatments or immune modulation therapies to reduce NLR levels, thereby improving prognosis.
Although NLR demonstrates considerable predictive value for prognosis in various cancer types [such as colorectal (14), prostate (15), uroepithelial (16), penile (17), lung (18) and breast (19) cancer], the use of this single marker has its limitations. These limitations include non-specificity (interference by infection or coexisting disease), variability in measurement time points and methods, lack of consistent thresholds and confounding effects of therapeutic interventions on inflammatory signals. Future studies should focus on the combined use of NLR with other inflammatory markers, molecular biomarkers and clinical pathological features (such as TNM staging and tumor markers) to build more accurate prognostic models. This integrated approach could provide essential insights for personalized treatment strategies. In the context of personalized therapy, NLR, as a marker of immune-inflammatory response, could assist in predicting the response of patients to immunotherapy or targeted therapies. Future research may investigate the relationship between NLR and treatment response, exploring whether treatment plans can be tailored based on NLR levels, thereby improving therapeutic efficacy and minimizing unnecessary side effects.
Despite the notable potential of NLR as a prognostic indicator in clinical practice, its translation into routine clinical use faces several challenges. Future studies need to address issues such as standardizing NLR measurement methods and managing the heterogeneity arising from factors such as ethnicity, age, sex and histological type. Additionally, staging may influence NLR levels through systemic inflammatory responses and immunosuppressive status, which is particularly relevant in patients with advanced disease. Subgroup analyses based on staging were not performed in the present study, primarily due to sample size limitations that could have affected the statistical power. The present study was designed to initially evaluate the overall prognostic value of NLR. However, future research will aim to expand the cohort and conduct more targeted analyses to validate the staging-specific effects. Furthermore, large-scale multicenter prospective studies will be essential to provide a stronger evidence foundation for the widespread application of NLR.
The present analysis has several limitations warranting consideration. Primarily, the reliance on non-randomized observational designs with limited participant numbers may restrict generalizability. Although random-effects models were applied to address variability, residual heterogeneity persisted in stratified assessments, potentially reflecting unmeasured covariates or population diversity. While sensitivity analyses mitigated detection bias, residual selection bias or unmeasured confounders may persist despite analytical controls. Regarding methodological validity, statistical adjustments using the trim-and-fill method indicated that the core findings remained consistent; however, undetected publication bias in smaller cohorts could still influence effect estimates. Additionally, the absence of standardized NLR thresholds remains a critical gap. Current practices often adopt optimal thresholds derived from receiver operating characteristic curves or extrapolate values from prior cohorts, introducing comparability challenges across datasets. Prospective validation through multicenter collaborations is imperative to establish NLR criteria consistent with clinical endpoints (such as progression-free intervals) while accounting for treatment-era effects and biomarker-temporal dynamics.
In conclusion, the results of the present meta-analysis suggest that elevated NLR is a potential biomarker for the prognostic evaluation of patients with RCC. Clinically, for the treatment of RCC, NLR could be considered in the routine assessment of patients to more accurately predict the prognosis of this disease.
Supplementary Material
Supporting Data
Supporting Data
Acknowledgements
The authors would like to acknowledge the help provided by Dr Junjie Hu (Department of Urology, Lanxi People's Hospital) in analyzing the large number of samples.
Funding
Funding: No funding was received.
Availability of data and materials
All data generated in the present study are included in the figures and/or tables of this article.
Authors' contributions
KCL conceived the manuscript and performed data acquisition, data analysis and statistical analysis. XC assisted with data acquisition, data analysis and manuscript preparation. XC reviewed the manuscript and polished the grammar. KCL and XC confirm the authenticity of all the raw data. Both authors read and approved the final version of the manuscript.
Ethics approval and consent to participate
Not applicable.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
References
|
Siegel RL, Miller KD and Jemal A: Cancer statistics, 2018. CA Cancer J Clin. 68:7–30. 2018. View Article : Google Scholar : PubMed/NCBI | |
|
Siegel RL, Miller KD and Jemal A: Cancer statistics, 2019. CA Cancer J Clin. 69:7–34. 2019. View Article : Google Scholar : PubMed/NCBI | |
|
Capitanio U and Montorsi F: Renal cancer. Lancet. 387:894–906. 2016. View Article : Google Scholar : PubMed/NCBI | |
|
Motzer RJ, Jonasch E, Agarwal N, Bhayani S, Bro WP, Chang SS, Choueiri TK, Costello BA, Derweesh IH, Fishman M, et al: Kidney cancer, version 2.2017, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw. 15:804–834. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Yang JC and Childs R: Immunotherapy for renal cell cancer. J Clin Oncol. 24:5576–5583. 2006. View Article : Google Scholar : PubMed/NCBI | |
|
Simonaggio A, Elaidi R, Fournier L, Fabre E, Ferrari V, Borchiellini D, Thouvenin J, Barthelemy P, Thibault C, Tartour E, et al: Variation in neutrophil to lymphocyte ratio (NLR) as predictor of outcomes in metastatic renal cell carcinoma (mRCC) and non-small cell lung cancer (mNSCLC) patients treated with nivolumab. Cancer Immunol Immunother. 69:2513–2522. 2020. View Article : Google Scholar : PubMed/NCBI | |
|
Shang B, Guo L, Shen R, Cao C, Xie R, Jiang W, Wen L, Bi X, Shi H, Zheng S, et al: Prognostic significance of NLR about NETosis and lymphocytes perturbations in localized renal cell carcinoma with tumor thrombus. Front Oncol. 11:7715452021. View Article : Google Scholar : PubMed/NCBI | |
|
Boissier R, Campagna J, Branger N, Karsenty G and Lechevallier E: The prognostic value of the neutrophil-lymphocyte ratio in renal oncology: A review. Urol Oncol. 35:135–141. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Hu H, Yao X, Xie X, Wu X, Zheng C, Xia W and Ma S: Prognostic value of preoperative NLR, dNLR, PLR and CRP in surgical renal cell carcinoma patients. World J Urol. 35:261–270. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Rao Z, Zhu Y, Yang P, Chen Z, Xia Y, Qiao C, Liu W, Deng H, Li J, Ning P and Wang Z: Pyroptosis in inflammatory diseases and cancer. Theranostics. 12:4310–4329. 2022. View Article : Google Scholar : PubMed/NCBI | |
|
Lee HM, Lee HJ and Chang JE: Inflammatory cytokine: An attractive target for cancer treatment. Biomedicines. 10:21162022. View Article : Google Scholar : PubMed/NCBI | |
|
Sharma N and Jha S: NLR-regulated pathways in cancer: Opportunities and obstacles for therapeutic interventions. Cell Mol Life Sci. 73:1741–1764. 2016. View Article : Google Scholar : PubMed/NCBI | |
|
Li Y, Jia H, Yu W, Xu Y, Li X, Li Q and Cai S: Nomograms for predicting prognostic value of inflammatory biomarkers in colorectal cancer patients after radical resection. Int J Cancer. 139:220–231. 2016. View Article : Google Scholar : PubMed/NCBI | |
|
Li MX, Liu XM, Zhang XF, Zhang JF, Wang WL, Zhu Y, Dong J, Cheng JW, Liu ZW, Ma L and Lv Y: Prognostic role of neutrophil-to-lymphocyte ratio in colorectal cancer: A systematic review and meta-analysis. Int J Cancer. 134:2403–2413. 2014. View Article : Google Scholar : PubMed/NCBI | |
|
Gu X, Gao X, Li X, Qi X, Ma M, Qin S, Yu H, Sun S, Zhou D and Wang W: Prognostic significance of neutrophil-to-lymphocyte ratio in prostate cancer: Evidence from 16,266 patients. Sci Rep. 6:220892016. View Article : Google Scholar : PubMed/NCBI | |
|
Marchioni M, Primiceri G, Ingrosso M, Filograna R, Castellan P, De Francesco P and Schips L: The clinical use of the neutrophil to lymphocyte ratio (NLR) in urothelial cancer: A systematic review. Clin Genitourin Cancer. 14:473–484. 2016. View Article : Google Scholar : PubMed/NCBI | |
|
Saputra HM, Hidayatullah F, Kloping YP, Renaldo J, Chung E and Hakim L: Prognostic value of neutrophil-to-lymphocyte ratio (NLR) in penile cancer: A systematic review and meta-analysis. Ann Med Surg (Lond). 81:1043352022.PubMed/NCBI | |
|
Stares M, Ding TE, Stratton C, Thomson F, Baxter M, Cagney H, Cumming K, Swan A, Ross F, Barrie C, et al: Biomarkers of systemic inflammation predict survival with first-line immune checkpoint inhibitors in non-small-cell lung cancer. ESMO Open. 7:1004452022. View Article : Google Scholar : PubMed/NCBI | |
|
Tokumaru Y, Oshi M, Murthy V, Tian W, Yan L, Angarita FA, Nagahashi M, Matsuhashi N, Futamura M, Yoshida K, et al: Low intratumoral genetic neutrophil-to-lymphocyte ratio (NLR) is associated with favorable tumor immune microenvironment and with survival in triple negative breast cancer (TNBC). Am J Cancer Res. 11:5743–5755. 2021.PubMed/NCBI | |
|
Ouyang H, Xiao B, Huang Y and Wang Z: Baseline and early changes in the neutrophil-lymphocyte ratio (NLR) predict survival outcomes in advanced colorectal cancer patients treated with immunotherapy. Int Immunopharmacol. 123:1107032023. View Article : Google Scholar : PubMed/NCBI | |
|
Kobayashi T, Ito K, Kojima T, Maruyama S, Mukai S, Tsutsumi M, Miki J, Okuno T, Yoshio Y, Matsumoto H, et al: Pre-pembrolizumab neutrophil-to-lymphocyte ratio (NLR) predicts the efficacy of second-line pembrolizumab treatment in urothelial cancer regardless of the pre-chemo NLR. Cancer Immunol Immunother. 71:461–471. 2022. View Article : Google Scholar : PubMed/NCBI | |
|
Mandaliya H, Jones M, Oldmeadow C and Nordman II: Prognostic biomarkers in stage IV non-small cell lung cancer (NSCLC): Neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR), platelet to lymphocyte ratio (PLR) and advanced lung cancer inflammation index (ALI). Transl Lung Cancer Res. 8:886–894. 2019. View Article : Google Scholar : PubMed/NCBI | |
|
Grassadonia A, Graziano V, Iezzi L, Vici P, Barba M, Pizzuti L, Cicero G, Krasniqi E, Mazzotta M, Marinelli D, et al: Prognostic relevance of neutrophil to lymphocyte ratio (NLR) in luminal breast cancer: A retrospective analysis in the neoadjuvant setting. Cells. 10:16852021. View Article : Google Scholar : PubMed/NCBI | |
|
Hu X, Tian T, Zhang X, Sun Q, Chen Y and Jiang W: Neutrophil-to-lymphocyte and hypopharyngeal cancer prognosis: System review and meta-analysis. Head Neck. 45:492–502. 2023. View Article : Google Scholar : PubMed/NCBI | |
|
Chen S, Zhang L, Yan G, Cheng S, Fathy AH, Yan N and Zhao Y: Neutrophil-to-lymphocyte ratio is a potential prognostic biomarker in patients with ovarian cancer: A meta-analysis. Biomed Res Int. 2017:79434672017.PubMed/NCBI | |
|
Shao Y, Wu B, Jia W, Zhang Z, Chen Q and Wang D: Prognostic value of pretreatment neutrophil-to-lymphocyte ratio in renal cell carcinoma: A systematic review and meta-analysis. BMC Urol. 20:902020. View Article : Google Scholar : PubMed/NCBI | |
|
Allenet C, Klein C, Rouget B, Margue G, Capon G, Alezra E, Blanc P, Estrade V, Bladou F, Robert G and Bernhard JC: Can pre-operative neutrophil-to-lymphocyte ratio (NLR) help predict non-metastatic renal carcinoma recurrence after nephrectomy? (UroCCR-61 study). Cancers (Basel). 14:56922022. View Article : Google Scholar : PubMed/NCBI | |
|
Korkmaz M and Erylmaz MK: Systemic inflammatory markers predicting the overall survival of patients using tyrosine kinase inhibitors in the first-line treatment of metastatic renal cell carcinoma. J Coll Physicians Surg Pak. 33:653–658. 2023.PubMed/NCBI | |
|
Tucker MD, Brown LC, Chen YW, Kao C, Hirshman N, Kinsey EN, Ancell KK, Beckermann KE, Davis NB, McAlister R, et al: Association of baseline neutrophil-to-eosinophil ratio with response to nivolumab plus ipilimumab in patients with metastatic renal cell carcinoma. Biomark Res. 9:802021. View Article : Google Scholar : PubMed/NCBI | |
|
Cordeiro MD, Ilario EN, Abe DK, Carvalho PA, Muniz DQB, Sarkis AS, Coelho RF, Guimarães RM, Haddad MV and Nahas WC: Neutrophil-to-lymphocyte ratio predicts cancer outcome in locally advanced clear renal cell carcinoma. Clin Genitourin Cancer. 20:102–106. 2022. View Article : Google Scholar : PubMed/NCBI | |
|
Young M, Tapia JC, Szabados B, Jovaisaite A, Jackson-Spence F, Nally E and Powles T: NLR outperforms low hemoglobin and high platelet count as predictive and prognostic biomarker in metastatic renal cell carcinoma treated with immune checkpoint inhibitors. Clin Genitourin Cancer. 22:1020722024. View Article : Google Scholar : PubMed/NCBI | |
|
Asif A, Chan VWS, Osman FH, Koe JSE, Ng A, Burton OE, Cartledge J, Kimuli M, Vasudev N, Ralph C, et al: The prognostic value of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio for small renal cell carcinomas after image-guided cryoablation or radio-frequency ablation. Cancers (Basel). 15:21872023. View Article : Google Scholar : PubMed/NCBI | |
|
Edge SB and Compton CC: The American joint committee on cancer: The 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol. 17:1471–1474. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Lo CK, Mertz D and Loeb M: Newcastle-Ottawa Scale: Comparing reviewers' to authors' assessments. BMC Med Res Methodol. 14:452014. View Article : Google Scholar : PubMed/NCBI | |
|
Parmar MK, Torri V and Stewart L: Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Stat Med. 17:2815–2834. 1998. View Article : Google Scholar : PubMed/NCBI | |
|
Tierney JF, Stewart LA, Ghersi D, Burdett S and Sydes MR: Practical methods for incorporating summary time-to-event data into meta-analysis. Trials. 8:162007. View Article : Google Scholar : PubMed/NCBI | |
|
DerSimonian R and Laird N: Meta-analysis in clinical trials. Control Clin Trials. 7:177–188. 1986. View Article : Google Scholar : PubMed/NCBI | |
|
Guyatt G, Oxman AD, Akl EA, Kunz R, Vist G, Brozek J, Norris S, Falck-Ytter Y, Glasziou P, DeBeer H, et al: GRADE guidelines: 1. Introduction-GRADE evidence profiles and summary of findings tables. J Clin Epidemiol. 64:383–394. 2011. View Article : Google Scholar : PubMed/NCBI | |
|
Parosanu AI, Baston C, Stanciu IM, Parlog CF and Nitipir C: Second-line treatment of metastatic renal cell carcinoma in the era of predictive biomarkers. Diagnostics (Basel). 13:24302023. View Article : Google Scholar : PubMed/NCBI | |
|
Parosanu AI, Pirlog CF, Slavu CO, Stanciu IM, Cotan HT, Vrabie RC, Popa AM, Olaru M, Iaciu C, Bratu LI, et al: The prognostic value of neutrophil-to-lymphocyte ratio in patients with metastatic renal cell carcinoma. Curr Oncol. 30:2457–2464. 2023. View Article : Google Scholar : PubMed/NCBI | |
|
Nagamoto S, Urakami S, Oka S, Ogawa K, Kono K, Sakaguchi K, Kinowaki K, Yamada D and Kume H: Impact of the neutrophil-to-lymphocyte ratio as a surgical prognostic factor in renal cell carcinoma with inferior-vena-cava tumor thrombus. Asian J Surg. 46:192–200. 2023. View Article : Google Scholar : PubMed/NCBI | |
|
Ni J, Wang Y, Zhang H, Wang K, Song W, Luo M, Che J, Geng J, Xu Y, Yao X, et al: Combination of preoperative plasma fibrinogen and neutrophil-to-lymphocyte ratio to predict the prognosis for patients undergoing laparoscopic nephrectomy for renal cell carcinoma. Am J Cancer Res. 12:3713–3728. 2022.PubMed/NCBI | |
|
Chaker K, Ouanes Y, Dali KM, Bibi M, Messaoudi Y, Mosbehi B, Abid K, Sellami A, Ben Rhouma S and Nouira Y: The prognostic value of preoperative neutrophil-to-lymphocyte ratio in patients with non-metastatic renal cell carcinoma. Prog Urol. 32:585–592. 2022.(In French). View Article : Google Scholar : PubMed/NCBI | |
|
Wang J, Ye J, Zhao X, Li X and Ma X: Prognostic value and model construction of preoperative inflammatory markers in patients with metastatic renal cell carcinoma. World J Surg Oncol. 21:2112023. View Article : Google Scholar : PubMed/NCBI | |
|
Wang Z, Qin Y, Chai X, Lu L, Xue P, Lu R, Miao C, Ma H, Hu X and Yao J: Systemic inflammatory biomarkers predict survival of patients treated with tyrosine kinase inhibitors for metastatic renal cell carcinoma. Cancer Control. 30:107327482311975112023. View Article : Google Scholar : PubMed/NCBI | |
|
Khan AI, Psutka SP, Patil DH, Hong G, Williams MA, Bilen MA, Sekhar A, Kissick HT, Narayan VM, Joshi SS, et al: Sarcopenia and systemic inflammation are associated with decreased survival after cytoreductive nephrectomy for metastatic renal cell carcinoma. Cancer. 128:2073–2084. 2022. View Article : Google Scholar : PubMed/NCBI | |
|
Cheng Y, Kou W and Zhu Y: Preoperative inflammation-associated blood cell markers in patients with non-metastatic clear cell renal cell carcinoma: A retrospective study. Int J Gen Med. 16:3067–3080. 2023. View Article : Google Scholar : PubMed/NCBI | |
|
Zhang Q, Song HF, Ma BL, Zhang ZN, Zhou CH, Li AL, Liu J, Liang L, Zhu SY and Zhang Q: Pre-operative prognostic nutritional index as a predictive factor for prognosis in non-metastatic renal cell carcinoma treated with surgery. Beijing Da Xue Xue Bao Yi Xue Ban. 55:149–155. 2023.(In Chinese). PubMed/NCBI | |
|
Anpalakhan S, Signori A, Cortellini A, Verzoni E, Giusti R, Aprile G, Ermacora P, Catino A, Pipitone S, Di Napoli M, et al: Using peripheral immune-inflammatory blood markers in tumors treated with immune checkpoint inhibitors: An INVIDIa-2 study sub-analysis. iScience. 26:1079702023. View Article : Google Scholar : PubMed/NCBI | |
|
Rebuzzi SE, Signori A, Buti S, Banna GL, Murianni V, Damassi A, Maruzzo M, Giannarelli D, Tortora G, Galli L, et al: Validation of the Meet-URO score in patients with metastatic renal cell carcinoma receiving first-line nivolumab and ipilimumab in the Italian expanded access program. ESMO Open. 7:1006342022. View Article : Google Scholar : PubMed/NCBI | |
|
Aslan V, Kılıç ACK, Sütcüoğlu O, Eraslan E, Bayrak A, Öksüzoğlu B, Tahtacı G, Özdemir N, Üner A, Günel N, et al: Cachexia index in predicting outcomes among patients receiving immune checkpoint inhibitor treatment for metastatic renal cell carcinoma. Urol Oncol. 40:494.e1–e10. 2022. View Article : Google Scholar : PubMed/NCBI | |
|
Ueda K, Suekane S, Kurose H, Ogasawara N, Hiroshige T, Chikui K, Uemura K, Nakiri M, Nishihara K, Matsuo M and Igawa T: Absolute lymphocyte count is an independent predictor of survival in patients with metastatic renal cell carcinoma treated with nivolumab. Jpn J Clin Oncol. 52:179–186. 2022. View Article : Google Scholar : PubMed/NCBI | |
|
Singh N, Baby D, Rajguru JP, Patil PB, Thakkannavar SS and Pujari VB: Inflammation and cancer. Ann Afr Med. 18:121–126. 2019. View Article : Google Scholar : PubMed/NCBI | |
|
Mierke CT: The fundamental role of mechanical properties in the progression of cancer disease and inflammation. Rep Prog Phys. 77:0766022014. View Article : Google Scholar : PubMed/NCBI | |
|
Balkwill F: TNF-alpha in promotion and progression of cancer. Cancer Metastasis Rev. 25:409–416. 2006. View Article : Google Scholar : PubMed/NCBI | |
|
Orange ST, Leslie J, Ross M, Mann DA and Wackerhage H: The exercise IL-6 enigma in cancer. Trends Endocrinol Metab. 34:749–763. 2023. View Article : Google Scholar : PubMed/NCBI | |
|
Hart PC, Rajab IM, Alebraheem M and Potempa LA: C-reactive protein and cancer-diagnostic and therapeutic insights. Front Immunol. 11:5958352020. View Article : Google Scholar : PubMed/NCBI | |
|
Carnevale S, Ghasemi S, Rigatelli A and Jaillon S: The complexity of neutrophils in health and disease: Focus on cancer. Semin Immunol. 48:1014092020. View Article : Google Scholar : PubMed/NCBI | |
|
Zahorec R: Neutrophil-to-lymphocyte ratio, past, present and future perspectives. Bratisl Lek Listy. 122:474–488. 2021.PubMed/NCBI | |
|
Templeton AJ, McNamara MG, Šeruga B, Vera-Badillo FE, Aneja P, Ocaña A, Leibowitz-Amit R, Sonpavde G, Knox JJ, Tran B, et al: Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: A systematic review and meta-analysis. J Natl Cancer Inst. 106:dju1242014. View Article : Google Scholar : PubMed/NCBI | |
|
Shaul ME and Fridlender ZG: Tumour-associated neutrophils in patients with cancer. Nat Rev Clin Oncol. 16:601–620. 2019. View Article : Google Scholar : PubMed/NCBI | |
|
Masucci MT, Minopoli M and Carriero MV: Tumor associated neutrophils. Their role in tumorigenesis, metastasis, prognosis and therapy. Front Oncol. 9:11462019. View Article : Google Scholar : PubMed/NCBI | |
|
Wang B, Gu W, Wan F, Shi G and Ye D: Prognostic significance of the dynamic changes of systemic inflammatory response in metastatic renal cell carcinoma. Int Braz J Urol. 45:89–99. 2019. View Article : Google Scholar : PubMed/NCBI | |
|
Hu K, Lou L, Ye J and Zhang S: Prognostic role of the neutrophil-lymphocyte ratio in renal cell carcinoma: A meta-analysis. BMJ Open. 5:e0064042015. View Article : Google Scholar : PubMed/NCBI | |
|
Chandrasekaran D, Sundaram S, Maheshkumar K, Kathiresan N and Padmavathi R: Preoperative neutrophil-lymphocyte ratio/platelet-lymphocyte ratio: A potential and economical marker for renal cell carcinoma. J Cancer Res Ther. 18:1635–1639. 2022. View Article : Google Scholar : PubMed/NCBI | |
|
Ohno Y, Nakashima J, Ohori M, Gondo T, Hatano T and Tachibana M: Followup of neutrophil-to-lymphocyte ratio and recurrence of clear cell renal cell carcinoma. J Urol. 187:411–417. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Ito K, Masunaga A, Tanaka N, Mizuno R, Shirotake S, Yasumizu Y, Ito Y, Miyazaki Y, Hagiwara M, Kanao K, et al: Impact of inflammatory marker levels one month after the first-line targeted therapy initiation on progression-free survival prediction in patients with metastatic clear cell renal cell carcinoma. Jpn J Clin Oncol. 49:69–76. 2019. View Article : Google Scholar : PubMed/NCBI | |
|
Chen X, Meng F and Jiang R: Neutrophil-to-lymphocyte ratio as a prognostic biomarker for patients with metastatic renal cell carcinoma treated with immune checkpoint inhibitors: A systematic review and meta-analysis. Front Oncol. 11:7469762021. View Article : Google Scholar : PubMed/NCBI |
