Pretreatment lymphocyte-to-monocyte ratio as a predictor of survival among patients with ovarian cancer: a meta-analysis

Figures & data

Figure 1 Flowchart of study selection in the current meta-analysis.

Abbreviations: CNKI, Chinese National Knowledge Infrastructure; LMR, lymphocyte-to-monocyte ratio; OC, ovarian cancer; OS, overall survival; PFS, progression-free survival.

Table 1 Characteristics of studies included in the meta-analysis

Study	Year	Country	Ethnicity	Duration of study conducted	Follow-up duration (months)	Age (years)a	Pathological type	Pathological subtypes, n (%)	No. of patientsb	No. of stage I/II	No. of stage III/IV	Outcome	Cutoff value	Method of obtaining cutoff	NOS score
Eo et al^Citation7	2016	Korea	Asian	2006.1– 2013.12	NA	54 (14–84)	EOC	Serous: 132 (56.4) Mucinous: 35 (15.0) Clear cell: 35 (15.0) Endometrioid: 21 (10.0) Mixed epithelial: 5 (2.1) Others: 6 (2.6)	234	97	137	OS and PFS	2.07	ROC curve	6
Sun and Song^Citation21	2016	China	Asian	2006.2– 2014.4	NA	55 (17–84)	EOC	Serous: 103 (54.5) Others: 86 (45.5)	189	78	111	OS and PFS	1.85	ROC curve	6
Wang et al^Citation24	2016	China	Asian	2000.1– 2013.12	NA	56.1±10.2	OC	Serous: 214 (89.2) Mucinous: 22 (9.2) Endometrioid: 2 (0.8) Clear cell: 2 (0.8)	240	59	181	OS	3.949	ROC curve	6
Kwon et al^Citation9	2017	Korea	Asian	2009.4– 2012.6 2000–2010	NA	70 (65–85)	EOC	Serous: 33 (78.6) Non-serous: 9 (21.4)	42	0	42	OS and PFS	3.63	ROC curve	6
Li et al^Citation10	2017	USA	Caucasian	2000–2010	49.5 (0.1–175.3)	63 (28–93)	EOC	High-grade serous: 525 (80.3) Low-grade serous: 4 (0.6) Endometrioid: 71 (10.9) Clear cell: 37 (5.7) Mucinous: 17 (2.6)	654	121	533	OS and PFS	2.22	ROC curve	8
Xiang et al^Citation11	2017	China	Asian	2011.1– 2016.3 2007.1– 2015.12	23.6 (0.77–69.4)	53.3±13.6 (20–82)	OC	Serous: 87 (65.4) Mucinous: 14 (10.5) Endometrioid: 10 (7.5) Clear cell: 5 (3.8) Others: 17 (12.8)	124	64	69	OS	4.35	ROC curve	6
Zhang et al^Citation5	2017	China	Asian	2007.1– 2015.12	NA	50 (24–76)	OC	Serous: 123 (51.9) Non-serous: 114 (36.3)	237	67	170	OS and PFS	3.82	NA	5
Zhu et al^Citation6	2017	China	Asian	2008.6– 2015.12	38 (5–103)	55 (30–70)	EOC	Serous: 484 (72.0) Non-serous: 188 (28.0)	672	0	672	OS and PFS	3.45	ROC curve	7
Tang et al^Citation22	2017	China	Asian	2005.1– 2015.1	46 (2–120)	52.2±12.0	EOC	Serous: 146 (68.2) Non-serous: 68 (31.8)	214	99	115	OS	3.85	ROC curve	7
Tian^Citation23	2017	China	Asian	2009.1– 2011.7	58 (2–60)	54 (14–76)	EOC	Serous: 166 (62.2) Mucinous: 21 (7.9) Endometrioid: 65 (24.3) Clear cell: 14 (5.2) Others: 1 (0.4)	267	86	181	OS and PFS	3.09 (OS) 2.07 (PFS)	ROC curve	7
Yang and Lo^Citation25	2017	China	Asian	2005.1–2011.5	37 (1–112)	54 (22–78)	EOC	Serous: 206 (56.6) Mucinous: 111 (30.5) Endometrioid: 23 (6.3) Others: 24 (6.6)	364	52	312	OS and PFS	3.84	ROC curve	7
Kwon et al^Citation8	2018	Korea	Asian	2005.1–2011.5	NA	50 (24–77)	OCCC	OCCC: 109 (100)	109	64	45	OS and PFS	4.2	ROC curve	6

Notes:

a Mean, median (range) of age at baseline.

b Number of patients at baseline.

Abbreviations: EOC, epithelial ovarian cancer; NA, not available; NOS, Newcastle–Ottawa Scale; OC, ovarian cancer; OCCC, ovarian clear cell carcinoma; OS, overall survival; PFS, progression-free survival; ROC, receiver-operator characteristic.

Table 2 Total, stratified, and sensitivity analyses of the associations between pretreatment LMR and survival among OC patients

Groups	OS					PFS
	Noa	RR (95% CIs)b	Pc	I^2 (%)	Pd	Noa	RR (95% CIs)b	Pc	I^2 (%)	Pd
Overall	12^Citation5^–^Citation11,Citation21^–^Citation25	1.85 (1.50–2.28)	<0.001	76.5	<0.001	8^Citation5^–^Citation9,Citation21,Citation23,Citation25	1.70 (1.49–1.94)	<0.001	24.4	0.234
Asian only	11^Citation5^–^Citation9,Citation11,Citation21^–^Citation25	1.97 (1.62–2.40)	<0.001	67.0	0.001	8^Citation5^–^Citation9,Citation21,Citation23,Citation25	1.70 (1.49–1.94)	<0.001	24.4	0.234
EOC only	8^Citation6,Citation7,Citation9,Citation10,Citation21^–^Citation23,Citation25	1.69 (1.34–2.13)	<0.001	79.4	<0.001	6^Citation6,Citation7,Citation9,Citation21,Citation23,Citation25	1.64 (1.48–1.82)	<0.001	0.0	0.483
Subgroup analyses
Age (years)
<55	7^Citation5,Citation7,Citation8,Citation11,Citation22,Citation23,Citation25	2.28 (1.72–3.01)	<0.001	61.9	0.015	5^Citation5,Citation7,Citation8,Citation23,Citation25	1.74 (1.37–2.20)	<0.001	54.7	0.065
≥55	5^Citation6,Citation9,Citation10,Citation21,Citation24	1.47 (1.17–1.85)	0.001	72.2	0.006	3^Citation6,Citation9,Citation21	1.70 (1.50–1.94)	<0.001	0.0	0.811
LMR cutoff values
≤3.0	3^Citation7,Citation10,Citation21	1.38 (1.06–1.80)	0.015	64.0	0.062	2^Citation7,Citation21	1.81 (1.11–2.97)	0.018	65.3	0.090
>3.0	9^Citation5,Citation6,Citation8,Citation9,Citation11,Citation22^–^Citation25	2.09 (1.63–2.67)	<0.001	70.1	0.001	6^Citation5,Citation6,Citation8,Citation9,Citation23,Citation25	1.72 (1.48–1.99)	<0.001	18.0	0.297
Sample size
≤200	4^Citation8,Citation9,Citation11,Citation21	1.59 (0.99–2.56)	0.057	37.8	0.186	3^Citation8,Citation9,Citation21	1.36 (0.83–2.20)	0.219	0.0	0.970
>200	8^Citation5^–^Citation7,Citation10,Citation22^–^Citation25	1.94 (1.50–2.50)	<0.001	83.1	<0.001	5^Citation5^–^Citation7,Citation23,Citation25	1.74 (1.48–2.06)	<0.001	52.0	0.080
NOS score
<7	7^Citation5,Citation7^–^Citation9,Citation11,Citation21,Citation24	1.94 (1.45–2.60)	<0.001	57.1	0.030	5^Citation5,Citation7^–^Citation9,Citation21	2.06 (1.65–2.59)	<0.001	0.0	0.429
≥7	5^Citation6,Citation10,Citation22,Citation23,Citation25	1.79 (1.31–2.46)	<0.001	86.7	<0.001	3^Citation6,Citation23,Citation25	1.63 (1.46–1.81)	<0.001	0.0	0.379
Influence analysese
Minimal	–	1.75 (1.43–2.13)	<0.001	72.9	<0.001	–	1.64 (1.48–1.81)	<0.001	0.0	0.560
Maximal	–	1.97 (1.62–2.40)	<0.001	67.0	0.001	–	1.76 (1.51–2.05)	<0.001	23.0	0.254

Notes:

a Number of studies.

b RRs and 95% CIs were pooled by using the random-effects model (the DerSimonian and Laird method).

c P-value of Z-test for the significance of pooled RRs and 95% CIs.

d P-value of Q-test for between-study heterogeneity test.

e Influence analysis was conducted by eliminating one study at a time; for OS, the excluded study was the study by Tang et al²² for minimal pooled RRs, and Li et al¹⁰ for the maximal pooled RRs; for PFS, the excluded study was the study by Zhang et al⁵ for minimal pooled RRs, and Tian²³ for the maximal pooled RR.

Abbreviations: EOC, epithelial ovarian cancer; LMR, lymphocyte-to-monocyte ratio; NOS, Newcastle–Ottawa Scale; OC, ovarian cancer; OS, overall survival; PFS, progression-free survival.

Figure 2 Forest plots of studies evaluating HRs of high pretreatment LMR among patients with OC for (A) OS and (B) PFS. Error bars indicate 95% CI.

Abbreviations: LMR, lymphocyte-to-monocyte ratio; OC, ovarian cancer; OS, overall survival; PFS, progression-free survival.

Figure 3 Funnel plots of studies evaluating HRs of high pretreatment LMR among patients with OC for (A) OS and (B) PFS.

Abbreviations: LMR, lymphocyte-to-monocyte ratio; OC, ovarian cancer; OS, overall survival; PFS, progression-free survival.

Table S1 PRISMA 2009 checklist

Section/topic	No.	Checklist item	Reported on page number
Title
Title	1	Identify the report as a systematic review, meta-analysis, or both	1
Abstract
Structured summary	2	Provide a structured summary including, as applicable: background; objectives; data sources; study eligibility criteria, participants, and interventions; study appraisal and synthesis methods; results; limitations; conclusions and implications of key findings; systematic review registration number	3
Introduction
Rationale	3	Describe the rationale for the review in the context of what is already known	4, 5
Objectives	4	Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS)	5
Methods
Protocol and registration	5	Indicate if a review protocol exists, if and where it can be accessed (eg, Web address), and, if available, provide registration information including registration number	NA
Eligibility criteria	6	Specify study characteristics (eg, PICOS and length of follow-up) and report characteristics (eg, years considered, language, and publication status) used as criteria for eligibility, giving rationale	6
Information sources	7	Describe all information sources (eg, databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched	5
Search	8	Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated	5, Supplementary materials, pages 1–2
Study selection	9	State the process for selecting studies (ie, screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis)	6
Data collection process	10	Describe method of data extraction from reports (eg, piloted forms, independently, and in duplicate) and any processes for obtaining and confirming data from investigators	6
Data items	11	List and define all variables for which data were sought (eg, PICOS and funding sources) and any assumptions and simplifications made	6
Risk of bias in individual studies	12	Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis	7, Table S2
Summary measures	13	State the principal summary measures (eg, risk ratio and difference in means)	7
Synthesis of results	14	Describe the methods of handling data and combining results of studies, if done, including measures of consistency (eg, I^2) for each meta-analysis	7
Risk of bias across studies	15	Specify any assessment of risk of bias that may affect the cumulative evidence (eg, publication bias and selective reporting within studies)	7, 8
Additional analyses	16	Describe methods of additional analyses (eg, sensitivity or subgroup analyses, meta- regression), if done, indicating which were prespecified	7
Results
Study selection	17	Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram	8, Figure 1
Study characteristics	18	For each study, present characteristics for which data were extracted (eg, study size, PICOS, and follow-up period) and provide the citations	8, Table 1
Risk of bias within studies	19	Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12)	10, Table S3
Results of individual studies	20	For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and CIs, ideally with a forest plot	Figure 2
Synthesis of results	21	Present results of each meta-analysis done, including CIs and measures of consistency	9, 10, Table 2, Figure 2
Risk of bias across studies	22	Present results of any assessment of risk of bias across studies (see item 15)	10, Table S3
Additional analysis	23	Give results of additional analyses, if done (eg, sensitivity or subgroup analyses, meta- regression [see item 16])	9, 10
Discussion
Summary of evidence	24	Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (eg, health care providers, users, and policy makers)	10
Limitations	25	Discuss limitations at study and outcome level (eg, risk of bias), and at review level (eg, incomplete retrieval of identified research and reporting bias)	12, 13
Conclusions	26	Provide a general interpretation of the results in the context of other evidence and implications for future research	13
Funding
Funding	27	Describe sources of funding for the systematic review and other support (eg, supply of data); role of funders for the systematic review	13

Note: Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JPA, et al. The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration. PLoS Med. 2009: 6(7): e1000100. https://doi.org/10.1371/journal.pmed.1000100. For more information, visit: www.prisma-statement.org.

Abbreviation: NA, not available.

Table S2 Methodological quality of all studies based on NOS for assessing the quality of each included study

Study	Representa- tiveness of exposed cohort	Selection of non- exposed cohort	Assessment of exposure	Outcome not present at the start of the study	Compara- bility based on the design or analysis	Assessment of outcome	Follow- up long enough for outcomes	Adequacy of follow-up	Total score
Eo et al^Citation1	1	1	1	1	2	0	0	0	6
Sun and Song^Citation2	1	1	1	1	2	0	0	0	6
Wang et al^Citation3	1	1	1	1	2	0	0	0	6
Kwon et al^Citation4	1	1	1	1	2	0	0	0	6
Li et al^Citation5	1	1	1	1	2	0	1	1	8
Xiang et al^Citation6	1	1	1	1	1	0	0	1	6
Zhang et al^Citation7	1	1	1	1	1	0	0	0	5
Zhu et al^Citation8	1	1	1	1	2	0	1	0	7
Tang et al^Citation9	1	1	1	1	2	0	1	0	7
Tian^Citation10	1	1	1	1	1	0	1	1	7
Yang and Lo^Citation11	1	1	1	1	2	0	1	0	7
Kwon et al^Citation12	1	1	1	1	2	0	0	0	6

Abbreviation: NOS, Newcastle–Ottawa Scale.

Table S3 Meta-regression analyses of the associations between pretreatment LMR and survival among OC patients

	Coefficient	Standard error	T-value	P-value	95% CI of intercept
OS
Year of publication	0.0820097	0.2491714	0.33	0.749	(–0.4731787, 0.6371981)
Age	−0.0738882	0.0200856	−3.68	0.004	(−0.1186417, −0.0291346)
Sample size	−0.0008594	0.0005413	−1.59	0.143	(−0.0020655, 0.0003466)
LMR cutoff value	0.2008357	0.129754	1.55	0.153	(−0.0882742, 0.4899455)
NOS score	−0.1728062	0.1330581	−1.30	0.223	(−0.4692782, 0.1236658)
PFS
Year of publication	−0.1952826	0.2098772	−0.93	0.388	(−0.7088336, 0.3182684)
Age	−0.0333006	0.0275148	−1.21	0.272	(−0.1006267, 0.0340256)
Sample size	−0.0000113	0.0004759	−0.02	0.982	(−0.0011757, 0.0011531)
LMR cutoff value	0.0189409	0.1054612	0.18	0.863	(−0.2391134, 0.2769952)
NOS score	−0.1618594	0.0787455	−2.06	0.086	(−0.3545426, 0.0308238)

Abbreviations: LMR, lymphocyte-to-monocyte ratio; NOS, Newcastle–Ottawa Scale; OC, ovarian cancer; OS, overall survival; PFS, progression-free survival.

EoWKChangHJKwonSHThe lymphocyte-monocyte ratio predicts patient survival and aggressiveness of ovarian cancerJ Cancer20167328929626918042

 PubMed Web of Science ®Google Scholar

SunLSongYEffects of lymphocyte and monocyte ratio on prognosis of epithelial ovarian cancerChinese Clin Oncol201610909912

 Google Scholar

WangXYuanZQiuHThe relationship between preoperative blood lymphocyte-to-monocyte ratio and the prognostic of epithelial ovarian cancerProg Obstet Gynecol20169654657

 Google Scholar

KwonBSLeeHJYangJSongYJSuhDSLeeDHKimKHPrognostic value of preoperative lymphocyte-monocyte ratio in elderly patients with advanced epithelial ovarian cancerObstet Gynecol Sci201760655856429184864

 PubMedGoogle Scholar

LiZHongNRobertsonMWangCJiangGPreoperative red cell distribution width and neutrophil-to-lymphocyte ratio predict survival in patients with epithelial ovarian cancerSci Rep201774300128223716

 PubMed Web of Science ®Google Scholar

XiangJZhouLLiXPreoperative monocyte-to-lymphocyte ratio in peripheral blood predicts stages, metastasis, and histological grades in patients with ovarian cancerTransl Oncol2017101333927888711

 PubMed Web of Science ®Google Scholar

ZhangWYeBLiangWRenYPreoperative prognostic nutritional index is a powerful predictor of prognosis in patients with stage III ovarian cancerSci Rep201771954828842710

 PubMedGoogle Scholar

ZhuJYLiuCCWangLZhongMTangHLWangHPeripheral blood lymphocyte-to-monocyte ratio as a prognostic factor in advanced epithelial ovarian cancer: a multicenter retrospective studyJ Cancer20178573774328382135

 PubMed Web of Science ®Google Scholar

TangYLiJXuFHuHAssociation between monocyte-to-lymphocyte ratio and prognosis of patients with epithelial ovarian cancerAm J Obstet Gynecol Pediat20175532538

 Google Scholar

TianYAnalysis of Prognostic Factors of Epithelial Ovarian CancerHe Bei, ChinaHebei Medical University2017

 Google Scholar

YangHMLouGThe relationship of preoperative lymphocyte-monocyte ratio and the clinicopathological characteristics and prognosis of patients with epithelial ovarian cancerZhonghua Zhong Liu Za Zhi201739967668028926896

 PubMedGoogle Scholar

KwonBSJeongDHByunJMPrognostic value of preoperative lymphocyte-monocyte ratio in patients with ovarian clear cell carcinomaJ Cancer2018971127113429675093

 PubMed Web of Science ®Google Scholar

EoWKChangHJKwonSHThe lymphocyte-monocyte ratio predicts patient survival and aggressiveness of ovarian cancerJ Cancer20167328929626918042

 PubMed Web of Science ®Google Scholar

SunLSongYEffects of lymphocyte and monocyte ratio on prognosis of epithelial ovarian cancerChinese Clinical Oncology201610909912

 Google Scholar

WangXYuanZQiuHThe relationship between preoperative blood lymphocyte-to-monocyte ratio and the prognostic of epithelial ovarian cancerProgi Obstet Gynecol20169654657

 Google Scholar

KwonBSLeeHJYangJSongYJSuhDSLeeDHKimKHPrognostic value of preoperative lymphocyte-monocyte ratio in elderly patients with advanced epithelial ovarian cancerObstet Gynecol Sci201760655856429184864

 PubMedGoogle Scholar

LiZHongNRobertsonMWangCJiangGPreoperative red cell distribution width and neutrophil-to-lymphocyte ratio predict survival in patients with epithelial ovarian cancerSci Rep201774300128223716

 PubMed Web of Science ®Google Scholar

XiangJZhouLLiXPreoperative Monocyte-to-lymphocyte ratio in peripheral blood predicts stages, metastasis, and histological grades in patients with ovarian cancerTransl Oncol2017101333927888711

 PubMed Web of Science ®Google Scholar

ZhangWYeBLiangWRenYPreoperative prognostic nutritional index is a powerful predictor of prognosis in patients with stage III ovarian cancerSci Rep201771954828842710

 PubMedGoogle Scholar

ZhuJYLiuCCWangLZhongMTangHLWangHPeripheral blood lymphocyte-to-monocyte ratio as a prognostic factor in advanced epithelial ovarian cancer: a multicenter retrospective studyJ Cancer20178573774328382135

 PubMed Web of Science ®Google Scholar

TangYLiJXuFHuHAssociation between monocyte-to-lymphocyte ratio and prognosis of patients with epithelial ovarian cancerAm J Obstet Gynecol Pediat20175532538

 Google Scholar

TianYAnalysis of Prognostic Factors of Epithelial Ovarian CancerHe Bei, ChinaHebei Medical University2017

 Google Scholar

YangHMLouGThe relationship of preoperative lymphocyte-monocyte ratio and the clinicopathological characteristics and prognosis of patients with epithelial ovarian cancerZhonghua Zhong Liu Za Zhi201739967668028926896

 PubMedGoogle Scholar

KwonBSJeongDHByunJMPrognostic value of preoperative lymphocyte-monocyte ratio in patients with ovarian clear cell carcinomaJ Cancer2018971127113429675093

 PubMed Web of Science ®Google Scholar