The prognostic value of preoperative inflammatory indexes in gallbladder carcinoma with hepatic involvement

Abstract

BACKGROUND:

Neutrophil-Lymphocyte Ratio (NLR) and Platelet-Lymphocyte Ratio (PLR) have been considered as indicators for prognosis in various cancers. However, the prognostic values of NLR and PLR have never been tested in gallbladder carcinoma (GBC) with hepatic involvement.

OBJECTIVE:

The aim of the current study was to assess the prognostic significance of NLR, PLR, and other candidate biomarkers in GBC with liver involvement.

METHODS:

Receiver operating characteristic (ROC) curve analyses were utilized to pinpoint the cut-off values for NLR, PLR, and Monocyte-Lymphocyte Ratio (MLR). Univariate analyses were employed to estimate the impact of NLR, PLR, MLR, and other inflammatory indexes on median survival. Multivariate analyses were used to verify the independent prognostic predictors.

RESULTS:

Eighty four patients were enrolled from 2009 to 2017. The cut-off values for NLR, PLR, and MLR were 3.20, 117.75, and 0.25, respectively. Univariate analyses revealed that TNM stage, NLR, PLR, MLR, lactate dehydrogenase, alkaline phosphatase, and carcinoembryonic antigen were significantly associated with decreased survival in GBC with hepatic involvement. Advanced TNM stage ( $P<$ 0.001) and elevated preoperative NLR ( $P=$ 0.002) were significantly associated with lower median survival periods, as revealed by multivariate analyses.

CONCLUSIONS:

These findings suggest that preoperative NLR may be an independent prognostic factor in evaluating prognosis in GBC with liver involvement.

Keywords

Gallbladder cancer immunologic markers overall survival prognostic factors serum markers

1. Introduction

Gallbladder cancer (GBC) is the predominant malignant tumor of the biliary system, with a poor overall 5-year survival rate, ranging from 5% to 10% [1, 2]. The sole potential curative treatment for GBC is to completely remove the gallbladder through surgery (cholecystectomy). Improvements in imaging technology including multi-slice spiral computed tomography (MSCT) and biliary magnetic-resonance imaging (MRI) have allowed moderately accurate preoperative staging of these diseases and have been helpful to surgeons for preoperative planning [3, 4]. Nonetheless, because GBC patients are often asymptomatic or initially describe nonspecific symptoms, detection of early-stage gallbladder cancer remains difficult [5, 6]. Patients are usually already at an advanced stage when diagnosed, thus complicating surgical management. As such, survival outcomes in GBC remain poor even in patients who undergo aggressive surgical treatment [7, 8]. Due to the anatomic position, GBC is likely to spread to the liver, either by direct invasion, hematogenous spread, and/or lymphatic spread. Previous studies have shown that liver involvement is a prognostic factor for decreased survival in GBC patients [9, 10, 11].

Inflammation is normally a protective reaction that aids in repairing tissue injury and in defending against pathogens. However, if inflammation becomes dysregulated, it can induce malignant transformation in the surrounding tissue [12, 13]. Indeed, the role of inflammation in cancer development is an important emerging area of study, and cancer-related inflammation has already been hailed as a hallmark of cancer [14]. Recent research has linked chronic inflammation to the development of GBC [15, 16], as well as other digestive system cancers, including stomach, intestine, and liver [17, 18, 19]. The relative abundance of immune-related cells, including neutrophils, lymphocytes, and platelets, can provide information about the state of a patient’s immune system and inflammatory state. Due to the low cost and ease of access, pretreatment Neutrophil-Lymphocyte Ratio (NLR) and Platelet-Lymphocyte Ratio (PLR) have been widely used as indicators of systemic inflammation in cancer patients. Neutrophils and platelets have been demonstrated to promote tumor development and protect cancer cells from the normal anti-cancer immune response mediated by lymphocytes, and thus elevated NLR and PLR ratios are thought to reflect a pro-cancer shifted inflammatory environment (see Discussion for more).

The prognostic significance of NLR and PLR has previously been demonstrated in non-small cell lung cancer (NSCLC), metastatic melanoma, and colorectal cancer [20, 21, 22]. Recently, NLR and PLR have also been examined as candidate biomarkers for GBC prognosis [23, 24]. However, there is still a need for further investigation of specific biomarkers associated with overall survival in GBC that involves the liver. The aim of the present study was to assess the merits of several inflammatory markers, including NLR, PLR, and Monocyte-Lymphocyte Ratio (MLR), as prognostic indicators of survival in patients with GBC with liver involvement.

2. Materials and methods

2.1 Patients

A retrospective review of all patients with histologically confirmed diagnosis of GBC in West China Hospital of Sichuan University from September 2009 to July 2017 was performed, excluding all those without hepatic involvement. Hepatic involvement was confirmed by radiological methods, including endoscopic ultrasonography, MRI and MSCT, and/or by pathological findings. Patients who were less than 18 years of age, had a recent infection, or had received any medication that might alter inflammatory markers, were excluded from further study. Approval for this retrospective study was obtained from the institution ethics commission of Sichuan University. Written informed consent was obtained from all included patients.

2.2 Data extraction and follow-up

Patients were regularly evaluated with radiological examinations and laboratory tests in West China Hospital of Sichuan University. The last follow up was June 30, 2017. All data were obtained from electronic medical records. Specifically, the following data were obtained: patient demographics, imaging results, pathology reports, aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin, lactate dehydrogenase (LDH), carcinoembryonic antigen (CEA), alkaline phosphatase (ALP), triglycerides, cholesterol, and peripheral blood cell counts including neutrophils, platelets, monocytes, and lymphocytes. The data were analyzed by both univariate and multivariate analyses to identify potential markers of prognosis in GBC patients with hepatic involvement.

2.3 Statistical analysis

The Pearson Chi squared test was performed to determine whether or not the differences between patients grouped by NLR, PLR, and MLR were significant. ROC curve analyses were used to determine the optimal cut-off values of pretreatment NLR, PLR, and MLR according to the maximum joint specificity and sensitivity. Survival curves were estimated by Kaplan-Meier univariate analyses and the differences between survival curves were compared with the log-rank test. Cox regression models were used to perform univariate analyses as well as multivariate analyses on potential prognostic factors. SPSS version 21.0 was used for data analysis. $P$ -values less than 0.05 were recognized as statistically significant.

Table 1
Clinicopathological demographic features stratified by NLR, PLR, and MLR

Variables	Cases	NLR		$P$ -value	PLR		$P$ -value	MLR		$P$ -value
		$<$ 3.20	$\geqslant$ 3.20		$<$ 117.75	$\geqslant$ 117.75		$<$ 0.25	$\geqslant$ 0.25
Gender
Male	28	6	22		7	21		5	23
Female	56	26	30	0.026	18	38	0.500	20	36	0.092
Age, years
$<$ 65	48	23	25		15	33		19	29
$\geqslant$ 65	36	9	27	0.032	10	26	0.731	6	30	0.023
TNM stage
III	35	21	14		14	21		15	20
IV	49	11	38	$<$ 0.001	11	38	0.083	10	39	0.027
LDH, IU/L
$<$ 195	30	21	9		14	16		14	16
$\geqslant$ 195	54	11	43	$<$ 0.001	11	43	0.012	11	43	0.012
ALP, IU/L
$<$ 90	18	13	5		10	8		13	5
$\geqslant$ 90	66	19	47	0.001	15	51	0.007	12	54	$<$ 0.001
CEA, ng/ml
$<$ 3.20	31	19	12		12	19		12	19
$\geqslant$ 3.20	53	13	40	0.001	13	40	0.170	13	40	0.170
Total bilirubin, umol/L
$<$ 30	57	24	33		20	37		23	34
$\geqslant$ 30	27	8	19	0.271	5	22	0.121	2	25	0.002
ALT, IU/L
$<$ 32	35	19	16		14	21		18	17
$\geqslant$ 32	49	13	36	0.010	11	38	0.083	7	42	$<$ 0.001
AST, IU/L
$<$ 35	33	18	15		14	19		16	17
$\geqslant$ 35	51	14	37	0.013	11	40	0.041	9	42	0.003
Triglyceride, mmol/L
$<$ 1.24	37	17	20		12	25		14	23
$\geqslant$ 1.24	47	15	32	0.189	13	34	0.635	11	36	0.151
Cholesterol, mmol/L
$<$ 2.82	9	1	8		1	8		2	7
$\geqslant$ 2.82	75	31	44	0.161	24	51	0.363	23	52	0.890
Postoperative chemotherapy
No	50	21	29		16	34		16	34
Yes	34	11	23	0.371	9	25	0.586	9	25	0.586

NLR $=$ Neutrophil-Lymphocyte Ratio, PLR $=$ Platelet-Lymphocyte Ratio, MLR $=$ Monocyte-Lymphocyte Ratio, LDH $=$ Lactate dehydrogenase, ALP $=$ Alkaline phosphatase, CEA $=$ Carcinoembryonic antigen, ALT $=$ Alanine aminotransferase, AST $=$ Aspartate aminotransferase. $P$ -values in bold were found to be significant ( $P<$ 0.05).

3. Results

From a total of 560 patients, 84 (15%) met the inclusion criteria for further study. The median (range) age was 62 (40–96) years and 56 (67%) patients were female. Following ROC analyses, the optimal cut-off values of NLR, PLR, and MLR were found to be 3.20, 117.75, 0.25 with a sensitivity of 0.813, 0.833, 0.896 and a specificity of 0.639, 0.472, 0.472 respectively. The corresponding areas under the curve for NLR, PLR, and MLR were, respectively, 0.683 (95% CI: 0.562–0.805, $P=$ 0.004), 0.630 (95% CI: 0.504–0.755, $P=$ 0.043) and 0.722 (95% CI: 0.611–0.833, $P=$ 0.001).

Table 2
Univariate and multivariate analyses of the prognostic utility of candidate biomarkers for survival in GBC with liver involvement

Variables	Univariate analyses						Multivariate analyses
	N	Median survival time	$P$ -value	HR	95% CI	$P$ -value	HR	95% CI	$P$ -value
		(Months)
Gender
Male	28	5
Female	56	8	0.068	0.649	0.396–1.062	0.085
Age, years
$<$ 65	48	7
$\geqslant$ 65	36	5	0.388	1.216	0.762–1.941	0.412
TNM stage
III	35	15
IV	49	4	$<$ 0.001	3.607	2.114–6.156	$<$ 0.001	3.175	1.809–5.573	$<$ 0.001
NLR
$<$ 3.20	32	17
$\geqslant$ 3.20	52	4	$<$ 0.001	2.811	1.678–4.710	$<$ 0.001	2.348	1.373–4.013	0.002
PLR
$<$ 117.75	25	14
$\geqslant$ 117.75	59	5	0.016	1.859	1.086–3.182	0.024
MLR
$<$ 0.25	25	15
$\geqslant$ 0.25	59	5	0.001	2.417	1.406–4.156	0.001
LDH, IU/L
$<$ 195	30	11
$\geqslant$ 195	54	5	0.022	1.736	1.050–2.869	0.031
ALP, IU/L
$<$ 90	18	13
$\geqslant$ 90	66	5	0.014	2.121	1.114–4.039	0.022
CEA, ng/ml
$<$ 3.20	31	12
$\geqslant$ 3.20	53	5	0.037	1.637	1.003–2.671	0.049
Total bilirubin, umol/L
$<$ 30	57	7
$\geqslant$ 30	27	5	0.437	1.203	0.736–1.967	0.460
ALT, IU/L
$<$ 32	35	8
$\geqslant$ 32	49	5	0.099	1.465	0.908–2.364	0.118
AST, IU/L
$<$ 35	33	8
$\geqslant$ 35	51	5	0.158	1.391	0.858–2.256	0.181
Triglyceride, mmol/L
$<$ 1.24	37	8
$\geqslant$ 1.24	47	5	0.606	1.124	0.705–1.792	0.624
Cholesterol, mmol/L
$<$ 2.82	9	9
$\geqslant$ 2.82	75	6	0.477	1.290	0.617–2.696	0.499
Postoperative chemotherapy
No	50	5
Yes	34	7	0.092	0.658	0.392–1.105	0.114

GBC $=$ Gallbladder carcinoma, NLR $=$ Neutrophil-Lymphocyte Ratio, PLR $=$ Platelet-Lymphocyte Ratio, MLR $=$ Monocyte-Lymphocyte Ratio, LDH $=$ Lactate dehydrogenase, ALP $=$ Alkaline phosphatase, CEA $=$ Carcinoembryonic antigen, ALT $=$ Alanine aminotransferase, AST $=$ Aspartate aminotransferase, HR $=$ Hazard Ratio, CI $=$ Confidential Interval. $P$ -values in bold were found to be significant ( $P<$ 0.05).

Figure 1.

The univariate survival analysis for the survival time of patients in the low ( $<$ 3.20) and high ( $\geqslant$ 3.20) Neutrophil-Lymphocyte Ratio (NLR) group by Kaplan-Meier.

Figure 2.

The univariate survival analysis for the survival time of patients in the low ( $<$ 117.75) and high ( $\geqslant$ 117.75) Platelet-Lymphocyte Ratio (PLR) group by Kaplan-Meier.

Figure 3.

The univariate survival analysis for the survival time of patients in the low ( $<$ 0.25) and high ( $\geqslant$ 0.25) Monocyte-Lymphocyte Ratio (MLR) group by Kaplan-Meier.

During follow-up, 72 (86%) patients died and 12 were censored at the last follow-up. The demographic baseline data and comparisons of clinicopathological parameters, stratified by NLR, PLR, and MLR threshold value, are listed in Table 1. All patients included in the current study were at TNM stages III or IV. Significant differences were found in LDH, ALP, and AST among all NLR, PLR, and MLR subgroups ( $P<$ 0.05). In addition, age, TNM stage, and ALT were found to be significant in the NLR and MLR subgroups, while CEA and gender were significant in the NLR subgroups, and total bilirubin was significant in the MLR subgroups.

TNM stage, NLR, PLR, MLR, LDH, ALP, and CEA were significantly associated with the survival outcomes of liver involvement GBC in the univariate analyses (Table 2). The median survival time of participants in the low NLR group was 17 months, compared with 4 months in the high NLR group ( $P<$ 0.001) (Fig. 1). High NLR was also associated with 2.811 times the odds of death (95% CI: 1.678–4.710, $P<$ 0.001). Patients assigned to the low PLR subgroup appeared to have had superior median survival time compared with those in the high PLR subgroup (14 months vs 5 months, $P=$ 0.016) (Fig. 2), and the hazard ratio was observed to be 1.859 (95% CI: 1.086–3.182, $P=$ 0.024). In addition, the median survival time for patients with high MLR was found to be 10 months less than for patients in the low MLR subgroup ( $P=$ 0.001) (Fig. 3), and high MLR was associated with more than double the odds of death compared with low MLR (HR $=$ 2.417, 95% CI: 1.406–4.156, $P=$ 0.001). Our multivariate analyses revealed that TNM stage ( $P<$ 0.001) and NLR ( $P=$ 0.002) were independent prognostic indexes for survival in GBC with liver involvement (Table 2), while PLR and MLR were not found to be independent prognostic markers for survival.

4. Discussion

Pathological TNM staging has been considered to be the most accurate index of long-term survival in cancer patients. Indeed, its utility as an independent prognostic index for survival in GBC with liver involvement has been confirmed here. However, a major limitation of TNM staging is that it can only be properly estimated after surgery. The aim of the present study was to explore the merits of several pretreatment inflammatory biomarkers as prognostic indicators of survival outcomes for GBC patients with hepatic involvement. Unlike TNM staging, these inflammatory indexes can be determined prior to performing surgery, and they may be valuable tools to supplement TNM staging for determining prognosis for patients with GBC with liver involvement.

Historically, NLR was employed as an indicator of systemic inflammation in critically ill patients (such as multiple trauma or major surgery) [25]. Subsequent studies found that reactive oxygen species generated by neutrophils are mutagenic, leading to premalignant lesions [26, 27]. Recent studies have demonstrated that tumor-associated neutrophils (TANs) can regulate the tumor microenvironment by producing various cytokines and/or chemokines that participate in immunosculpting and immunoediting [28, 29]. TANs, together with tumor-associated macrophages, encourage tumor cells to extravasate from the circulation and embed into a new tissue site [29]. In GBC, neutrophil-bound tumor cells engage integrins and induce ICAM-1 clustering on the tumor cell, stimulating a cellular migration towards the liver [30, 31].

In contrast to the reported pro-tumor functions of neutrophils, lymphocytes play an essential role in cancer immune surveillance, which suppresses the maturation of tumor cells [32]. Thus, the Neutrophil-Lymphocyte Ratio may be interpreted as reflecting the balance between deleterious inflammation and proper immune surveillance, with a high NLR suggesting a pro-cancer inflammatory environment, and a low NLR suggesting a protective, anti-tumor inflammatory environment. The present finding of increased NLR being associated with significantly decreased survival time is consistent with this interpretation of NLR, and supports the utility of NLR as a prognostic biomarker of survival in patients with GBC with liver involvement. Furthermore, NLR was the only independent prognostic biomarker, suggesting that it may be superior to PLR and MLR in the absence of other biomarkers.

There are several ways that platelets can promote tumor development. Platelets facilitate the arrest of tumor cells at the endothelium, which promotes the establishment of secondary lesions [33, 34]. In addition, the release of VEGF and other angiogenic factors by platelets during platelet-endothelium interaction modifies the angiogenic balance in the tumor microenvironment [35]. Platelets also protect tumor cells from the immune response through various mechanisms, including steric shielding from NK cells, inhibiting NK cell-mediated cytolysis, and altering MHC I expression [36]. Platelet-tumor cell interaction results in extensive membrane changes that suppress immune cytotoxicity and support the survival and spread of tumor cells [37]. The presence of tumor-infiltrating lymphocytes (TILs) is an important prognostic factor associated with superior clinical outcomes [38, 39], but platelets can shield tumor cells from being accessed by TILs [36]. The present finding that PLR is associated with decreased survival time in GBC with hepatic involvement is consistent with the previously described pro-cancer role of platelets, and we speculate that some of these mechanisms may be at play in the context of GBC with liver involvement.

Representing the relative levels of peripheral monocytes and lymphocytes, MLR was found to have an inverse relationship with survival in GBC with hepatic involvement. This finding is consistent with reports of various pro-cancer processes mediated by tumor-associated macrophages (TAMs), which are a major component of the infiltrate found within the stroma of many tumors. Derived from circulating monocytes, most TAMs are considered to have an M2 phenotype, meaning they can produce growth and angiogenic factors as well as proteases to degrade the extracellular matrix [40]. Thus, it has been speculated that TAMs can stimulate tumor cell proliferation, promote angiogenesis, and enhance invasion and metastasis [41].

Since our results showed that GBC patients with increased NLR tend to have a poorer prognostic outlook, these patients may benefit from more intensive postoperative care and careful follow-up.

A few limitations of the current study should be noted. First of all, although patients from 2009 to 2017 were analyzed, the sample size of available participants was still relatively small. Hence, larger prospective cohorts are still required to more completely investigate the values of NLR, PLR, and MLR as predictors of survival in GBC patients with liver involvement. Secondly, since the study was restricted to a Chinese population, the results may not apply to other ethnic populations.

References

Piehler

J.M.

and Crichlow

R.W.

, Primary carcinoma of the gallbladder, Surgery, Gynecology and Obstetrics 147(6) (1978), 929–942.

Cubertafond

Gainant

and Cucchiaro

, Surgical treatment of 724 carcinomas of the gallbladder. Results of the French surgical association survey, Annals of Surgery 219(3) (1994), 275–280.

Bai

R.J.

et al., Accuracy of multi-slice spiral computed tomography for preoperative tumor node metastasis (TNM) staging of colorectal carcinoma, Medical Science Monitor 23 (2017), 3470–3479.

Kim

S.J.

et al., Preoperative staging of gallbladder carcinoma using biliary MR imaging, Journal of Magnetic Resonance Imaging 41(2) (2015), 314–321.

Srinivasa

McEntee

and Koea

J.B.

, The role of PET scans in the management of cholangiocarcinoma and gallbladder cancer: A systematic review for surgeons, International Journal of Diagnostic Imaging 2(1) (2015), 1–9.

Corvera

C.U.

et al., 18F-fluorodeoxyglucose positron emission tomography influences management decisions in patients with biliary cancer, Journal of the American College of Surgeons 206(1) (2008), 57–65.

Puhalla

et al., Long-term follow-up of surgically treated gallbladder cancer patients, European Journal of Surgical Oncology 28(8) (2002), 857–863.

Shimizu

et al., Aggressive surgical approach for stage IV gallbladder carcinoma based on Japanese Society of Biliary Surgery classification, Journal of Hepato-Biliary-Pancreatic Surgery 14(4) (2007), 358–365.

Launoy

et al., Cancer of the gallbladder. Epidemiology diagnosis and prognostic factors, Annales De Chirurgie 47(1) (1993), 18–23.

10.

et al., Prognosis and management for gallbladder cancer with hepatic invasion: Long-term results of 139 patients from a single center in China, Asian Pacific Journal of Cancer Prevention 13(3) (2012), 1015–1018.

11.

Chen

et al., Long-term outcomes and prognostic factors in advanced gallbladder cancer: Focus on the advanced T stage, PLOS One 11(11) (2016), e0166361.

12.

Karin

and Greten

F.R.

, NF-kappaB: Linking inflammation and immunity to cancer development and progression, Nature Reviews. Immunology 5(10) (2005), 749–759.

13.

Karin

, Nuclear factor-kappaB in cancer development and progression, Nature 441(7092) (2006), 431–436.

14.

Colotta

et al., Cancer-related inflammation, the seventh hallmark of cancer: Links to genetic instability, Carcinogenesis 30(7) (2009), 1073–1081.

15.

Zhang

and Ma

, Chronic inflammation and gallbladder cancer, Cancer Letters 345(2) (2014), 242–248.

16.

Espinoza

J.A.

et al., The inflammatory inception of gallbladder cancer, Biochimica Et Biophysica Acta 1865(2) (2016), 245–254.

17.

Barash

et al., Accelerated carcinogenesis following liver regeneration is associated with chronic inflammation-induced double-strand DNA breaks, Proceedings of the National Academy of Sciences 107(5) (2010), 2207–2212.

18.

Watanabe

et al., Development of gastric cancer in nonatrophic stomach with highly active inflammation identified by serum levels of pepsinogen and Helicobacter pylori antibody together with endoscopic rugal hyperplastic gastritis, International Journal of Cancer 131(11) (2012), 2632–2642.

19.

Liang

et al., Sphingosine-1-phosphate links persistent STAT3 activation, chronic intestinal inflammation, and development of colitis-associated cancer, Cancer Cell 23(1) (2013), 107–120.

20.

Azab

et al., The value of the pretreatment neutrophil lymphocyte ratio vs. platelet lymphocyte ratio in predicting the long-term survival in colorectal cancer, Cancer Biomarkers 14(5) (2014), 303–312.

21.

Cananzi

F.C.

Dalgleish

and Mudan

, Surgical management of intraabdominal metastases from melanoma: Role of the neutrophil to lymphocyte ratio as a potential prognostic factor, World Journal of Surgery 38(6) (2014), 1542–1550.

22.

Zhang

et al., Clinical significance of preoperative neutrophil-lymphocyte vs platelet-lymphocyte ratio in primary operable patients with non-small cell lung cancer, The American Journal of Surgery 210(3) (2015), 526–535.

23.

Zhang

et al., Prognostic significance of preoperative neutrophil/lymphocyte ratio and platelet/lymphocyte ratio in patients with gallbladder carcinoma, Clinical and Translational Oncology 17(10) (2015), 810–818.

24.

Beal

E.W.

et al., Elevated NLR in gallbladder cancer and cholangiocarcinoma – making bad cancers even worse: Results from the US Extrahepatic Biliary Malignancy Consortium, HPB: The Official Journal of the International Hepato Pancreato Biliary Association 18(11) (2016), 950–957.

25.

Zahorec

, Ratio of neutrophil to lymphocyte counts – rapid and simple parameter of systemic inflammation and stress in critically ill, Bratislavské Lekárske Listy 102(1) (2001), 5–14

26.

Knaapen

A.M.

et al., Neutrophils and respiratory tract DNA damage and mutagenesis: A review, Mutagenesis 21(4) (2006), 225–236.

27.

Gungor

et al., Genotoxic effects of neutrophils and hypochlorous acid, Mutagenesis 25(2) (2010), 149–154.

28.

Queen

M.M.

et al., Breast cancer cells stimulate neutrophils to produce oncostatin M: Potential implications for tumor progression, Cancer Research 65(19) (2005), 8896–8904.

29.

Gregory

A.D.

and Houghton

A.M.

, Tumor-associated neutrophils: New targets for cancer therapy, Cancer Research 71(7) (2011), 2411–2416.

30.

Roland

C.L.

et al., ICAM-1 expression determines malignant potential of cancer, Surgery 141(6) (2007), 705–707.

31.

Spicer

J.D.

et al., Neutrophils promote liver metastasis via Mac-1-mediated interactions with circulating tumor cells, Cancer Research 72(16) (2012), 3919–3927.

32.

Dunn

G.P.

Old

L.J.

and Schreiber

R.D.

, The immunobiology of cancer immunosurveillance and immunoediting, Immunity 21(2) (2004), 137–148.

33.

Gay

L.J.

and Felding-Habermann

, Contribution of platelets to tumour metastasis, Nature Reviews. Cancer 11(2) (2011), 123–134.

34.

Takagi

et al., Platelets promote tumor growth and metastasis via direct interaction between aggrus/podoplanin and CLEC-2, PLOS One 8(8) (2013), e73609.

35.

Pinedo

H.M.

et al., Involvement of platelets in tumour angiogenesis? The Lancet 352(9142) (1998), 1775–1777.

36.

Meikle

C.K.

et al., Cancer and thrombosis: The platelet perspective, Frontiers in Cell and Developmental Biology 4 (2016), 147.

37.

Tesfamariam

, Involvement of platelets in tumor cell metastasis, Pharmacology and Therapeutics 157 (2016), 112–119.

38.

Wein

et al., Clinical validity and utility of tumor-infiltrating lymphocytes in routine clinical practice for breast cancer patients: Current and future directions, Frontiers in Oncology 7 (2017), 156.

39.

Zeng

D.Q.

et al., Prognostic and predictive value of tumor-infiltrating lymphocytes for clinical therapeutic research in patients with non-small cell lung cancer, Oncotarget 7(12) (2016), 13765–13781.

40.

Sica

Allavena

and Mantovani

, Cancer related inflammation: The macrophage connection, Cancer Letters 267(2) (2008), 204–215.

41.

Balkwill

and Mantovani

, Inflammation and cancer: Back to Virchow? The Lancet 357(9255) (2001), 539–545.

The prognostic value of preoperative inflammatory indexes in gallbladder carcinoma with hepatic involvement

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1. Introduction

2. Materials and methods

2.1 Patients

2.2 Data extraction and follow-up

2.3 Statistical analysis

Table 1 Clinicopathological demographic features stratified by NLR, PLR, and MLR

Table 2 Univariate and multivariate analyses of the prognostic utility of candidate biomarkers for survival in GBC with liver involvement

References

Table 1
Clinicopathological demographic features stratified by NLR, PLR, and MLR

Table 2
Univariate and multivariate analyses of the prognostic utility of candidate biomarkers for survival in GBC with liver involvement