Prognostic value of pretreatment lymphocyte-to-monocyte ratio in patients with urologic tumors: A PRISMA-compliant meta-analysis.

BACKGROUND: The prognostic value of pretreatment lymphocyte to monocyte ratio (LMR) in patients with urologic tumors remains controversial. Therefore, we herein conducted a meta-analysis to systematically assess the prognostic value of LMR in patients with urologic tumors.
METHODS: We comprehensively searched PubMed, EMBASE and Web of Science to identify eligible studies. Hazard ratios (HRs) and their 95% confidence intervals (CIs) were used to assess the prognostic value of LMR in patients with urologic tumors. This meta-analysis was registered in PROSPERO (CRD42018108959).
RESULTS: A total of 20 studies were included in this meta-analysis. Our synthesized analysis showed that low LMR was significantly correlated with poor overall survival (OS) and progression-free survival (PFS) in patients with upper tract urothelial cancer (UTUC). We also found that renal cell cancer (RCC) patients with low LMR had poor OS, PFS and cancer-specific survival (CSS). Besides, it was observed that low LMR predicted poor OS, RFS and CSS in patients with bladder cancer (BC).
CONCLUSION: This meta-analysis demonstrated that pretreatment LMR is associated with survival, and may be a useful prognostic parameter in urologic tumors. Nevertheless, more prospective and heterogeneous studies with large samples are required to further confirm our findings before it is applied for daily clinical decision making.

Introduction

Cancer remains one of the major causes of mortality and a huge economic burden worldwide.[ Urologic tumor, including upper tract urothelial cancer (UTUC), renal cell cancer (RCC), bladder cancer (BC) and prostate cancer, is a common type of malignancy. Although the comprehensively therapeutic strategy integrating surgery, immunotherapy, and molecular-targeted therapy has been improved largely in recent years, a subset of patients with urologic tumors still have unfavorable prognosis due to ineffective drug response, local relapse, and distant metastasis.[ A lack of effectively prognostic biomarkers might partly account for the poor prognosis in patients with urologic tumors. Hence, effective and reliable biomarkers that could provide additional prognostic information are imminently needed.[

Numerous studies have shown that systemic inflammatory response plays key roles in tumor initiation and progression.[ Several systemic inflammatory biomarkers such as platelet-to-lymphocyte ratio, albumin-to-globulin ratio, neutrophil-to-lymphocyte ratio and C-reactive protein-to-albumin ratio, have been reported to have potential as prognostic biomarkers in a wide variety of tumors.[ Recently, many studies indicated that a lower peripheral lymphocyte-to-monocyte ratio (LMR) was closely associated with worse prognosis in patients with various cancers and might be an easily available and reliable prognostic biomarker.[ In addition, because of the limitation of small sample from individual studies and the presence of conflicting conclusions, several meta-analyses have been performed to further validate the prognostic value of LMR in patients with various tumors.[ Nevertheless, to date there were no meta-analyses that specifically focus on investigating the association between LMR and patients with urologic tumors. Therefore, it is very imperative to perform a meta-analysis to thoroughly assess the prognostic value of LMR in patients with urologic tumors.

Methods

This meta-analysis was undertaken according to preferred reporting items for systematic reviews and meta-analyses statement[ and it was registered in PROSPERO (CRD42018108959). All analyses were based on previously published studies; thus, no patient consent and ethical approval are required.

Search strategy

A comprehensive search was performed in PubMed, EMBASE, and Web of Science for eligible studies that explored the prognostic role of LMR in patients with urologic tumors from inception to November, 2018. The search terms included: “lymphocyte and “monocyte or leukomonocyte” and ratio” and “upper tract urothelial carcinoma or UTUC or renal or kidney or bladder or prostate or urinary or urologic or urothelial or transitional”, and “tumor or cancer or carcinoma or adenocarcinoma or malignancy or malignant or neoplasm or neoplastic”. The detailed search strategy in PubMed database was presented in supplement.

Selection criteria

Study that met the following issues were included:

Cohort study or observational study;

Patients with urologic tumors were histopathologically confirmed

Hazard ratios (HR) and corresponding 95% confidence intervals (CIs) that assessed association between LMR and prognosis of patients with urologic tumor, including overall survival (OS), cancer-specific survival (CSS), recurrence-free survival (RFS), disease-free survival (DFS), and progression-free survival (PFS), could be extracted;

Full text should be accessible for extracting relevant data.

OS was defined as the interval from the date of surgery on the primary tumor to death. CSS was defined as the interval from the date of surgery on the primary tumor to death for urologic tumors. DFS was defined as the interval from the date of surgery on the primary tumor to local, regional, or distant recurrence or death from any cause. RFS was defined as the interval from the date of surgery on the primary tumor to local, regional, or distant recurrence. PFS was defined as the interval from the date of surgery on the primary tumor until disease progression (including local recurrence or distant metastasis) or death.

Exclusion criteria excluded:

The studies were editorials, letters, review articles, meeting abstracts or case reports;

The studies included overlapped patients;

The studies focused on investigating the relationship between LMR and non-urological tumors.

Only studies in English were considered in this meta-analysis.

Data extraction and quality evaluation

Two investigators extracted relevant data from the included studies independently (Jialin Li and Yusheng Cheng) and divergences in data extraction were resolved by the corresponding author. The extracted information included: first author, publication year, country, tumor type, tumor stage, case number, primary therapy, neoadjuvant therapy, sexual ratio, median age, median follow-up, cut off value for a low LMR, analysis type, and HRs (95% CIs) assessing the association between LMR and prognosis, including OS, DFS, RFS, PFS, and CSS. If the data form both univariable and multivariable analysis were available in the articles, the data from multivariable analysis was extracted for pooling analysis. If the survival data was reported as Kaplan-Meier curves, we used the Engauge Digitizer (version 4.1) and the Tierney methods to extract the HR and its 95% CIs.[ The quality of the included studies was assessed according to the Newcastle-Ottawa Scale (NOS),[ and studies with 6 or more were considered as high-quality ones.

Statistical analysis

Statistical analysis was performed using STATA version 12.0 (Stata Corporation, College Station, TX). HRs with 95% CIs were used to assess the association between LMR and prognosis. The concurrence of with the 95% CI not crossing 1, and HR > 1 indicates that patients with low LMR had a worse prognosis compared to a high LMR. In addition, the link between LMR and clinicopathological features of urologic tumors was assessed using ORs (odds ratios) with 95% CIs. Chi-square-based Q and I2 tests were conducted to assess the heterogeneity among the included studies. Random effects model was applied to combine data if there was significant heterogeneity among the included studies (P < .01 or I2 > 50%), otherwise fixed effects model was used. Sensitivity analysis was performed to further explore the potential sources of heterogeneity and meanwhile test the robustness of our pooled results by sequentially omitting individual studies step by step. Begg test and the Egger test were used to assess the publication bias.[ Duval nonparametric trim-and-fill method was used to evaluate the potential effect of publication bias.[

Results

Study search

A of total 163 studies were identified through literature search with 42 from PubMed, 74 from EMBASE, and 47 from Web of Science. After excluding 82 duplicated records, 81 studies were left for title and abstract screening and then 30 studies were excluded for irrelevant topics. The remaining 51 studies were further screened by full text, in which 31 studies were excluded for reviews, conference abstracts, lack of relevant data and overlapped patients. Finally, a total of 20 studies were included in our meta-analysis.[ The flow diagram of identifying eligible studies was presented in Figure 1.

Figure 1

Flow diagram of identifying eligible studies.

Characteristics of the included studies

A total of 20 studies were included in this meta-analysis. These studies were published between 2014 and 2018, 11 of which from China,[ 4 from Austria,[ 2 from Japan,[ 1 of each study from Turkey,[ Lebanon,[ and Poland.[ A total of 5 studies exploring the prognostic value of LMR in patients with UTUC were included in this meta-analysis.[ Among these studies, 3 studies with 706 patients referred to OS.[ Three studies involving 353 patients reported about DFS.[ Three studies with 677 patients referred to PFS.[ A total of 8 studies exploring the prognostic value of LMR in patients with RCC were included in this meta-analysis.[ Among these studies, 7 studies with 3608 patients referred to OS.[ Two studies involving 1505 patients reported about PFS.[ Two studies with 1094 patients referred to CSS.[ A total of 7 studies exploring the prognostic value of LMR in patients with BC were included in this meta-analysis.[ Among these studies, 6 studies with 4969 patients referred to OS.[ Two studies involving 324 patients reported about PFS.[ Two studies with 4479 patients referred to CSS.[ Two studies with 4542 patients reported about RFS.[ Across all included studies, the ratio of female patients ranged from 11.8% to 40.3%; The cut-off values for a low LMR were inconsistent, ranging from 2 to 4.44. More information about the main characteristics were summarized in Tables 1 and 2. The scores of quality of all the included studies ranged from 6 to 8, suggesting that all the included studies were eligible for synthesized analysis in this meta-analysis (Table 3).

Table 1

The main characteristics of the included studies.

Table 2

HRs (95% CIs) assessing the association between LMR and prognosis in patients with urologic tumor.

Table 3

The Newcastle-Ottawa Scale (NOS) quality assessment of the included studies.

The prognostic value of pretreatment LMR in patients with UTUC

A total of 5 studies exploring the prognostic value of LMR in patients with UTUC were included in this meta-analysis. Among these studies, 3 studies with 706 patients referred to OS. Three studies involving 353 patients reported about DFS. Three studies with 677 patients referred to PFS. The synthesized analyses showed that low LMR was significantly correlated with poor OS (fix-effect model, HR: 1.85, 95% CI: 1.34–2.56, P < .05) (Fig. 2A) and PFS (fix-effect model, HR: 2.20, 95% CI: 1.13–4.26, P < .05) (Fig. 2B), but not with DFS (random-effect model, HR: 1.53, 95% CI: 0.80–2.94, P > .05) (Fig. 2C) in patients with UTUC. Considering that the number of eligible studies was only limited, we did not perform sensitivity analysis and publication bias assessment for the pooling results about the prognostic value of LMR in patients with UTUC.

Figure 2

The synthesized HR assessing the prognostic value of pretreatment LMR for OS (A), PFS (B) and DFS (C) in upper tract urothelial cancer. DFS = disease-free survival, HR = hazard ratio, LMR = lymphocyte-to-monocyte ratio, OS = overall survival, PFS = progression-free survival.

The prognostic value of pretreatment LMR in patients with RCC

A total of 8 studies exploring the prognostic value of LMR in patients with RCC were included in this meta-analysis. Among these studies, 7 studies with 3608 patients referred to OS. Two studies involving 1505 patients reported about PFS. Two studies with 1094 patients referred to CSS. The synthesized analyses showed that RCC patients low LMR had poorer OS (fix-effect model, HR: 1.81, 95% CI: 1.37–2.40, P < .05) (Fig. 3A) and CSS (fix-effect model, HR: 2.63, 95% CI: 1.56–4.46, P < .05) (Fig. 3B), but equal PFS (random-effect model, HR: 1.75, 95% CI: 0.97–3.17, P < .05) (Fig. 3C). Additionally, we performed sensitivity analysis by sequentially omitting single study and publication bias assessment to further explore the stability and reliability of the pooled result about OS. From the results, we found that the pooled HR about OS was not significantly altered in sensitivity analysis (Fig. 4A), the funnel plot of assessing publication bias was symmetric (Fig. 4B) and the P values of Begg and Egger tests were more than .05, all of which suggested that our pooled result about OS were robust and dependable.

Figure 3

The synthesized HR assessing the prognostic value of pretreatment LMR for OS (A), CSS (B) and PFS (C) and in renal cell cancer. CSS = cancer-specific survival, HR = hazard ratio, LMR = lymphocyte-to-monocyte ratio, OS = overall survival, PFS = progression-free survival.

Figure 4

The sensitivity analysis of the synthesized HR assessing the prognostic value of pretreatment LMR for OS in renal cell cancer (A). The funnel plot of Begg test for the publication bias assessment of the synthesized HR assessing the prognostic value of pretreatment LMR for OS in renal cell cancer (B). HR = hazard ratio, LMR = lymphocyte-to-monocyte ratio, OS = overall survival.

The prognostic value of pretreatment LMR in patients with BC

A total of 7 studies exploring the prognostic value of LMR in patients with BC were included in this meta-analysis. Among these studies, 6 studies with 4969 patients referred to OS. Two studies involving 324 patients reported about PFS. Two studies with 4479 patients referred to CSS. Two studies with 4542 patients reported about RFS. The synthesized analyses showed that low LMR was related to poor OS (random-effect model, HR: 1.58, 95% CI: 1.24–2.03, P < .05) (Fig. 5), RFS (fix-effect model, HR: 1.39, 95% CI: 1.25–1.56, P < .05) (Fig. 6A) and CSS (fix-effect model, HR: 1.31, 95% CI: 1.19–1.44, P < .05) (Fig. 6B), but not to PFS (fix-effect model, HR: 1.18, 95% CI: 0.62–2.26, P > .05) (Fig. 6C) in patients with BC. Additionally, we performed sensitivity analysis by sequentially omitting single study and publication bias assessment to further explore the stability and reliability of the pooled result about OS of BC patients. From the results, we found that the pooled HR about OS was not significantly altered in sensitivity analysis (Fig. 7). The funnel plot of assessing publication bias was asymmetric (Fig. 8A) and the P values of Begg and Egger tests was less than .05, which indicated that there was significant publication bias for the pooled result about OS of BC patients. Thus, we performed trim-and-fill analysis determine whether the publication bias significantly affected the reliability of the pooled result about OS of BC patients. The result of trim-and-fill analysis showed that the adjusted HR for OS was still more than 1 (random -effect model, HR: 1.25, 95% CI: 1.14–1.36, P < .05), and the adjusted funnel plot of publication bias assessment became symmetric (Fig. 8B), suggesting that the publication bias did not significantly affect the reliability of the pooled result about OS of BC patients.

Figure 5

The synthesized HR assessing the prognostic value of pretreatment LMR for OS in bladder cancer. LMR = lymphocyte-to-monocyte ratio, OS = overall survival.

Figure 6

The synthesized HR assessing the prognostic value of pretreatment LMR for RFS (A), CSS (B) and PFS (C) in bladder cancer. CSS = cancer-specific survival, HR = hazard ratio, LMR = lymphocyte-to-monocyte ratio, OS = overall survival, PFS = progression-free survival, RFS = recurrence-free survival.

Figure 7

The sensitivity analysis of the synthesized HR assessing the prognostic value of pretreatment LMR for OS in bladder cancer. HR = hazard ratio, LMR = lymphocyte-to-monocyte ratio, OS = overall survival.

Figure 8

The funnel plot of Begg test for the publication bias assessment of the synthesized HR assessing the prognostic value of pretreatment LMR for OS in bladder cancer (A). The adjusted funnel plot of Begg test for the publication bias assessment of the synthesized HR assessing the prognostic value of pretreatment LMR for OS in bladder cancer (B). HR = hazard ratio, LMR = lymphocyte-to-monocyte ratio, OS = overall survival.

Discussion

To date there were no meta-analyses that specifically focus on investigating the prognostic value of pretreatment LMR in patients with urologic tumors. Therefore, we herein conducted a meta-analysis to systematically assess the prognostic value of LMR in patients with urologic tumors. Our synthesized analysis showed that low LMR was significantly correlated with poor OS and PFS in patients with UTUC. We also found that RCC patients with low LMR had poor OS, PFS, and CSS. Besides, it was observed that low LMR predicted poor OS, RFS, and CSS in patients with BC. Thus, pretreatment LMR may serve as a promising parameter for predicting the prognosis of patients with urologic tumors.

The inflammatory cell's response resulted from tumors could cause the production and release of various cytokines and inflammatory mediators, ultimately promoting tumor invasion, migration, metastasis and progression.[ Monocytes take up about 5% of the circulating leukocytes and play an essential role in innate immunity. Several studies reported that absolute monocyte count was related to survival in patients with colorectal cancer[ and the infiltrated monocytes in tumor tissue could promote tumor invasion and cell growth in large B-cell lymphoma. However, the exact mechanisms underlying the role of monocytes in tumor progression have not yet been well elucidated. One of mechanisms is the link between monocytes and tumor-associated macrophages (TAMs). That is, macrophages derives from monocytes circulating in peripheral blood, thereby which suggest that the circulating level of monocytes may mirror a surrogate for formation or presence of TAMs. TAMs are sensitive to the chemotactic effect of the tumor microenvironment-secreted cytokines and chemokines, such as monocyte chemoattractant protein-1, tumor necrosis factor-α and others. Furthermore, the interaction between TAMs and cancer cell were capable of promoting tumor angiogenesis, migration, invasion, and depressing antitumor immunity, ultimately leading to tumor progression and poor prognosis of tumor patients.[ Additionally, there is another hypothesis that may also explain the role of monocytes in tumor progression.[ The infiltrative monocytes in tumor could release many soluble factors, such as interleukin (IL)-1, IL-6, IL-10 and tumor growth factor-α, and it has been well studied that these factors play an important role in promoting neo-angiogenesis, invasion and migration, and correlate with unfavorable prognosis in various malignant tumors.[ Moreover, monocytes can restrain mitogen and antigen-induced lymphocytes proliferative response, which impair the lymphocyte-dependent anti-tumor defense, leading to suppression of anti-tumor immunity.[ In other words, LMR, as the combination of lymphocytes and monocytes, reflects the relative proportion of the 2 types of inflammatory cells, which may be more accurate to reflect the status of tumor-stimulated inflammatory response and predict prognosis in tumor patients than lymphocytes or monocytes. However, the reason why LMR is altered in cancers has not been fully identified so far. One possibility is that under cancer background there may be an inflammatory-immune imbalance, in which the induction of the inflammatory-immune cells, such as lymphocytes or monocytes, is influenced by tumor-associated factors. In addition, as mentioned above, monocytes can restrain mitogen and antigen-induced lymphocytes proliferative response, which may also partly contributes to the alteration of LMR. In light of the content above, we may speculate that LMR could reflect the status of antitumor immunity and predict the prognosis of patients with urological cancers due to its indication of the relative proportion between lymphocytes and monocytes. Therefore, it may be possible to integrate this inflammatory marker into predictive models of prognosis. For example, Zhang et al established a new prognostic model for UTUC by integrating LMR, pathological stage, subsequent bladder tumor, multifocality, and tumor necrosis, and demonstrated that this model could successfully divide UTUC patients into high, intermediate and low risk 3 groups in terms of overall survival time.[ Nonetheless, LMR has not been recommended in European Association of Urology (EAU) guidelines on BC,[ UTUC[ and RCC[ yet, since most of the evidence supporting the prognostic value of LMR in these tumors came from retrospective studies with small sample size.

Although our meta-analysis overcame the limitation of small sample size in a degree and provided more strong evidence of the prognostic value of LMR in urologic tumors, several limitations still should be seriously considered in our meta-analysis. First, all the included studies were retrospectively designed, which may lead to bias. Second, although we performed synthesized analysis of previous studies, the total sample sizes were not large enough, which still could lead us to make a biased conclusion. Third, in some of the included studies, HRs and 95% CIs were calculated from the survival curves, which might cause some statistical errors more or less. Fourth, HRs and 95% CIs were from univariable analysis, in which confounding factors were not adjusted. Thus, combining these data may introduce a degree of bias and heterogeneity. Fifth, the cut-off values for low LMR were inconsistent across the included studies, which might introduce heterogeneity into our meta-analysis and limit its application in clinical decision making. Additionally, there were several other inconsistencies in aspects of sex ratio, age, tumor stages, and follow-up across the included studies, which may result in bias and heterogeneity as well. Sixth, although this study was a systematic review with a meta-analysis about the prognostic value of LMR in urologic tumors, none of studies focusing on the prognostic value of LMR in prostate cancer. Therefore, it may imperative and interesting to explore the prognostic value of LMR in prostate cancer.

Conclusion

This meta-analysis demonstrated that pretreatment LMR is associated with survival, and may be a useful prognostic parameter in urologic tumors. Nevertheless, more prospective and heterogeneous studies with large samples are required to further confirm our findings before it is applied for daily clinical decision making.

Author contributions

Conceptualization: Zhigang Ji.

Data curation: Jialin Li.

Formal analysis: Jialin Li, Yusheng Cheng.

Methodology: Yusheng Cheng.

Software: Jialin Li, Yusheng Cheng.

Visualization: Jialin Li.

Writing – original draft: Jialin Li.

Writing – review & editing: Yusheng Cheng.