Introduction
Ovarian cancer is one of the most common gynecological malignant tumors with the highest mortality rate. Over 90% of ovarian cancer is of epithelial origin, and non-epithelial tumors are usually derived from the granulosa or germ cells [
1]. These differences in ovarian cancer etiology require different diagnostic approaches and result in distinct treatment regimens.
Despite advances in early diagnosis and targeted drug treatment, as well as improvements in drug cytotoxicity, most patients are still diagnosed at an advanced stage [
2,
3]. Furthermore, chemotherapy is frequently not effective in controlling the disease mainly due to the development of primary or secondary resistance to anticancer drugs. In addition, some chemotherapy regimens are also associated with increased relapse and mortality rates among patients with ovarian cancer [
4]. Therefore, better understanding of carcinogenic mechanisms is needed. The use of suitable and improved biomarkers could aid in both the diagnosis and prognosis of ovarian cancer.
It is well known that inflammatory and immune responses within the tumor microenvironment play important roles in tumorigenesis and cancer progression [
5,
6]. Several inflammatory-related prognostic factors, such as the platelet-to-lymphocyte (PLR), neutrophil-to-lymphocyte (NLR), lymphocyte-to-monocyte (LMR), and C-reactive protein/albumin (CAR) ratios have been recently evaluated for their ability to predict outcomes of patients with various solid cancers [
7‐
9]. In fact, PLR has been continuously reported as a novel inflammation-based prognostic index over the past years.
Similarly, LMR has been associated with a poor prognosis in several cancer types [
10‐
12]. However, its prognostic value in ovarian cancer has not yet been fully elucidated. With this in mind, we decided to carry out this meta-analysis to elucidate the relationship of LMR with the clinicopathology of ovarian cancer and to establish whether it might be useful in predicting patient outcome.
Materials and methods
Search strategy
We searched the MEDLINE, Embase, Cochrane Library, and WanFang databases to identify the relevant articles using the search terms “LMR”, “lymphocyte to monocyte ratio”, “lymphocyte monocyte ratio”, or “lymphocyte-to-monocyte ratio” combined with “ovarian cancer”, “ovarian carcinoma”, “ovarian adenocarcinoma”, “ovarian tumor”, or “ovarian neoplasms”. The literature search was performed up to November 20, 2018.
Inclusion and exclusion criteria
Published articles were selected for study based on the following inclusion criteria: (1) reported association between pretreatment LMR and prognosis in ovarian cancer; (2) patients grouped into “high LMR group” and “low LMR group” according to cut-off values of LMR; and (3) hazard ratios (HRs) with 95% confidence intervals (CIs) calculated for overall survival (OS), progression-free survival (PFS), or cancer-specific survival (CSS). The exclusion criteria were as follows: (1) lack of appropriate data; (2) duplicate publications; and (3) reviews, meta-analysis, letters, and conference abstracts.
Data extraction and quality assessment
Data extraction was conducted independently by two investigators. The following information (on study details and clinopathological features) was collected from the studies: first author, year and country of study, number of patients involved and distribution of age and gender, tumor histological type, grade, stage, and optimal debulking, presence of malignant ascites and lymph node metastases, type of treatment applied (including surgery and chemotherapy dosage and duration), cut-off values of LMR, patient’s survival outcome (assessed by OS and PFS), and duration of follow-up period.
The Newcastle–Ottawa Scale (NOS) [
13] was used to assess the methodological quality of the studies. According to this scale, the maximum score is 9; studies with NOS > 6 were considered high-quality studies.
Statistical analysis
We used Review Manager 5.3 (Cochrane Collaboration, Oxford, UK) to pool HRs for OS and PFS and to pool odd ratios (ORs) for clinicopathological parameters. The HRs and 95% CIs were directly obtained from studies that included survival analysis or, when necessary, they were determined from the Kaplan-Meier curve by using Engauge Digitizer 4.1 [
14,
15].
The heterogeneity across the eligible studies was assessed by the Cochran’s Q-test and I
2 statistic. If I
2 ≤ 50% or
p > 0.05, indicating low heterogeneity, we used a fixed-effect model with an inverse variance method. Otherwise, we used a random-effect model with the DerSimonian and Laird method, which considers both within-and between-study variations [
16]. A subgroup analysis was then performed to examine the potential source of heterogeneity. Sensitivity analysis was undertaken in order to test the robustness of the pooled results by removing each study. When more than eleven studies were included, Begg’s funnel plots and Egger’s linear regression tests were used to evaluate publication bias [
17,
18]. In all analyses, a
p value < 0.05 was considered statistically significant.
Discussion
The present study is, to our knowledge, the most comprehensive, up-to-date, and with the largest sample size meta-analysis undertaken to estimate the prognostic value of LMR in ovarian cancer. According to the pooled results confirmed by subgroup analysis, there was a significant association between low LMR and poor survival outcome, specifically poor OS and PFS, in ovarian cancer patients. Therefore, it can be concluded that LMR is an independent prognostic factor in ovarian cancer.
Additionally, in this study, the correlations between LMR and several clinicopathological parameters were evaluated. We found that a low LMR was highly correlated with tumor high G2/G3 histological grades and late III-IV FIGO stages, as well as with high serum CA-125 levels, and presence of malignant ascites and lymph node metastases, in agreement with the poor overall survival outcome associated with this ratio.
However, the potential mechanisms underlying the prognostic ability of LMR have not yet been clarified. It is known that lymphocytes play an important role in cell-mediated antitumor immune responses and in tumor immunological surveillance [
26,
27]. Cytotoxic lymphocytes, mainly cytotoxic T cells, are crucial to eliminate residual cancer cells and, as such, are applied in immunotherapy [
28,
29]. Monocytes seem to have an impact on tumorigenesis through differentiation into tumor-associated macrophages (TAMs). TAMs are major players in inflammation, being recruited to the tumor site in response to tumor-derived chemotactic factors [
30]. Therefore, TAM levels may reflect the tumor burden. Moreover, recent studies reported that an increased local infiltration of TAMs is associated with a poor prognosis in several cancer types [
31,
32]. In line with this, LMR may represent the balance between antitumor immune reaction and tumor promotion function. Thus, a low LMR would be associated with a favorable tumor progression, explaining at least in part our results.
Our study presents several limitations. First, all studies included were carried out in Asian countries, implying that more cohort studies from other regions are necessary. Second, our conclusions could have been influenced by the heterogeneity of the results of the studies included in this meta-analysis, as well as by unknown carcinogenesis mechanisms. Third, the cut-off value of LMR was not uniform across the studies analyzed. Finally, only retrospective studies were included, which might have introduced confounding variables; thus, control-test studies are missing. Nevertheless, the present meta-analysis, which is conceptually superior to individual investigations, included sufficient published studies with data from a large number of patients, allowing for adequate evaluation of the prognostic value of LMR in ovarian cancer.
Conclusions
The present study revealed that a low pretreatment (baseline) LMR is associated with a poor OS and PFS in ovarian cancer patients, as well as with severe clinicopathological features including advanced tumor characteristics. Therefore, as LMR is easily accessible, it may be a useful prognostic biomarker in ovarian cancer and thus, relevant in the management of the disease.
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