Sage Journals: Discover world-class research

Abstract

BACKGROUND:

Esophageal cancer (EC) is the sixth most common cause of death from cancer. Altered mean platelet volume (MPV) levels were found in patients with malignancies.

OBJECTIVE:

The present study investigated whether MPV can predict the survival in EC patients.

MEHTODS:

The clinical data of 236 consecutive EC patients between January 2009 and December 2009 in our center were retrospectively analyzed. The overall survival rate was estimated using Kaplan-Meier method. Cox proportional hazards models were fitted to model the relationships between patient characteristics and prognosis.

RESULTS:

Decreased MPV was significantly correlated with tumor location and tumor differentiation ( $p<$ 0.001). Moreover, survival analysis revealed that the overall survival of patients with MPV $\leqslant$ 7.4 fL was significantly shorter than that of those with MPV $>$ 7.4 fL. Multivariate analysis identified MPV as an independent poor prognostic factor for overall survival.

CONCLUSIONS:

Reduced MPV is associated with worse survival outcome in EC.

Keywords

Esophageal cancer mean platelet volume prognosis

1. Introduction

Esophageal cancer (EC) is the sixth most common cause of death from cancer and the eighth most common cancer worldwide [1]. Prognosis of EC is poor with a 5-year survival rate of less than 20% even with multiple treatment modalities [2, 3]. Therefore, novel prognostic biomarkers could improve prognosis for EC patients.

Emerging evidence demonstrated that platelets contribute to circulating tumor cell growth, survival and invasiveness, and lead to tumor metastasis [4]. Thrombocytosis correlates with poor prognosis in patients with gastric, pancreatic, colorectal, ovarian, endometrial cancer [5, 6, 7, 8, 9]. Since platelet count is determined by the balance between the rate of production and consumption of platelets, in the presence of efficient compensatory mechanisms, a normal platelet count could conceal the presence of highly hypercoagulative and pro-inflammatory cancer phenotypes [10].

A most commonly used measurement of platelet size is mean platelet volume (MPV) in clinical practice. MPV is an indicator of platelet activation [11]. Alteration of MPV levels in breast, lung, gastric, colon, and ovarian, cancer has been reported [12, 13, 14, 15]. However, the significance of the change in these cancers remain elusive. The aim of this study was to assess the relationship between preoperative MPV and the long-term survival of EC patients.

2. Patients and methods

2.1 Study population

The study was comprised of 236 consecutive EC patients who underwent surgery between January 2011 and December 2011 at Harbin Medical University Cancer Hospital (Harbin, Heilongjiang, China). Clinical, demographic and pathological data were obtained from the patients’ medical records. Histopathological evaluation was carried out independently by two pathologists. None of the patients received preoperative chemotherapy or radiation therapy. Exclusion criteria included: hematological disorders, hypertension, diabetes mellitus, and medical treatment with anticoagulant, statins, and acetylic salicylic acid. Disease-free survival (DFS) time was calculated from the day of surgery to the day of definitive diagnosis of recurrent tumor. Overall survival (OS) time was measured from the date of surgery to the date of death or the date of the last clinical follow-up. The last clinical follow-up was completed on December 31, 2016. The median follow-up duration was 60 months.

The Institutional Ethics Review Board of Harbin Medical University Cancer Hospital approved this study prior to commencement of data collection and waived the informed consent requirement because it was a retrospective study. All methods were conducted according to guidelines (Declaration of Helsinki) for biomedical research.

2.2 Biochemical measurements

Fasting venous blood samples were collected in the morning after a 10-h fast within 1 week prior to surgery. White blood cell (WBC), haemoglobin, and platelet indices were measured by an autoanalyzer (Sysmex XE-2100, Kobe, Japan). The whole blood samples were collected in EDTA-containing tubes, and all samples were processed within 30 minutes after blood collection.

2.3 Statistical analysis

The descriptive statistics were presented as means $\pm$ SD for continuous variables and percentages of the number for categorical variables. Normally distributed continuous variables were compared with the Student’s t test. The Chi-square test was used for categorical variables. The Kaplan-Meier method was used to estimate survival times and distributions were compared using the log-rank test. The optimal cutoff value of MPV was determined by receiver operating characteristic (ROC) curve. Univariate Cox regression analyses were performed to determine the prognostic significance of individual clinicopathologic variables. The independent prognostic variables associated with OS were confirmed by multivariate analysis using Cox proportional hazards model. Variables in univariate analysis with $p<$ 0.10 were included in the multivariate analysis. The statistical tests were two-tailed and were performed using SPSS version 22.0 software (SPSS Inc., Chicago, IL, USA). Receiver operating characteristic (ROC) curves were constructed, and the area under the curve (AUC) was calculated to evaluate the specificity and sensitivity of MPV using MedCalc version 15.0. A nominal significance level of 0.05 was used in all tests.

3. Results

Of 236 enrolled primary EC patients, 94.5% ( $n=$ 223) were male, and 97.0% ( $n=$ 229) were with esophageal squamous cell carcinoma. The pathophysiological characteristics of the patients are reported in Table 1.

Table 1
The relation between clinico-pathological parameters and the pretreatment MPV levels in EC patients

Variables	Total		MPV $\leqslant$ 7.4		MPV $>$ 7.4		P value
	n (%)		n (%)		n (%)
Age (years)							0.835
$\leqslant$ 60	171	(72.5)	39	(73.6)	132	(72.1)
$>$ 60	65	(27.5)	14	(26.4)	51	(27.9)
Gender							0.046
Male	223	(94.5)	53	(100.0)	170	(92.9)
Female	13	(5.5)	0	(0)	13	(7.1)
Smoking history							0.359
Ever	190	(80.5)	45	(84.9)	145	(79.2)
Never	46	(19.5)	8	(15.1)	38	(20.8)
Drinking history							0.171
Ever	205	(86.9)	49	(92.5)	156	(85.2)
Never	31	(13.1)	4	(7.5)	27	(14.8)
Tumor location							$<$ 0.001
Upper	20	(8.5)	5	(9.4)	15	(8.2)
Middle	93	(39.4)	20	(37.7)	73	(39.9)
Lower	123	(52.1)	28	(52.8)	95	(51.9)
Tumor size							0.187
$<$ 3.5 cm	41	(17.4)	6	(11.3)	35	(19.1)
$\geqslant$ 3.5 cm	195	(82.6)	47	(88.7)	148	(80.9)
Differentiation							$<$ 0.001
Well	32	(13.5)	12	(22.6)	20	(10.9)
Moderate	155	(65.7)	27	(50.9)	128	(69.9)
Poor	49	(20.8)	14	(26.4)	35	(19.1)
Tumor invasion depth							0.100
T1 $+$ T2	108	(45.8)	19	(35.8)	89	(48.6)
T3 $+$ T4	128	(54.2)	34	(64.2)	94	(51.4)
Lymph node metastasis							0.123
Positive	116	(49.2)	31	(58.5)	85	(46.4)
Negative	120	(50.8)	22	(41.5)	98	(53.6)
TNM Stage							0.275
I $+$ II	100	(42.4)	19	(35.8)	81	(44.3)
III $+$ IV	136	(57.6)	34	(64.2)	102	(55.7)

Figure 1.

Optimized cut-off value was determined for MPV using standard ROC curve analysis.

Table 2

The relation between clinical parameters and the pretreatment MPV levels in EC patients

Variables	MPV $\leqslant$		MPV $>$		P value
	7.4 (fL)		7.4 (fL)
Age (years)	56.3	(8.9)	57.3	(7.7)	0.436
BMI (kg/m ${}^{2}$ )	21.4	(2.8)	22.3	(3.0)	0.043
Fibrinogen (g/L)	3.78	(1.19)	3.40	(0.87)	0.011
Hemoglobin (g/dl)	136.1	(13.0)	143.9	(13.9)	$<$ 0.001
WBC ( $\times$ 10 ${}^{9}$ /L)	7.1	(2.1)	6.9	(2.0)	0.511
Platelet count	278.3	(74.8)	228.1	(64.9)	$<$ 0.001
( $\times$ 10 ${}^{9}$ /L)

According to the ROC curve analysis, we identified that the optimal cut-off value of MPV was 7.4 fL, with a 28.2% sensitivity and 85.2% specificity for survival rate (AUC $=$ 0.559, 95% CI: 0.493–0.624, $p<$ 0.0001) (Fig. 1). The positive and negative likelihood ratios of model were 1.90 and 0.84, respectively. Then, patients were divided into 2 groups: patients with MPV $\leqslant$ 7.4 fL and patients with MPV $>$ 7.4 fL. There were 53 (22.5%) patients with MPV $\leqslant$ 7.4 fL and 183 (77.5%) patients with MPV $>$ 7.4 fL.

The relationship between MPV and clinical characteristics was shown in Tables 1 and 2. MPV was associated with differentiation tumor location. However, there were no significant differences between two groups in terms of age, tumor size, tumor invasion depth, lymph node metastasis, and clinical stage.

With a median follow up of 60 months, 135 (57.2%) patients had death events. The association between MPV and survival of EC patients was investigated by Kaplan-Meier analysis and log-rank test. We found that both the DFS and OS in the normal MPV group are significantly longer than those in the low MPV group (Fig. 2, 5-year DFS rates, 47.0% vs 11.3%, $p<$ 0.001 and Fig. 3, 5-years OS rates, 47.0% vs 28.3%, $p=$ 0.003, respectively).

Figure 2.

Kaplan-Meier analysis of disease-free survival in EC patients.

Figure 3.

Kaplan-Meier analysis of overall survival in EC patients.

We preformed Cox univariate and multivariate regression analyses for factors that could impact survival including tumor invasion depth, lymph node metastasis, TNM stage, and MPV. We found that MPV is significantly associated with survival in univariate analyses (Table 3). Next, we performed a multivariate analysis including all factors with a $p<$ 0.05 (Table 4) and found that reduction of MPV was an independent variable associated with survival. Patients with MPV $\leqslant$ 7.4 fL had a hazard ratio (HR) of 1.582 [95% confidence interval (CI): 1.077–2.323, $p=$ 0.019] for OS.

Table 3

The univariate analysis of overall survival in EC patients

	Hazard	95% CI	$P$ -value
	ratio
Age (years) ( $\leqslant$ 60 versus $>$ 60)	1.044	0.715–1.524	0.824
Gender (male versus female)	0.686	0.360–1.308	0.253
BMI (kg/m ${}^{2}$ )	0.981	0.927–1.038	0.507
Drinking history (ever versus never)	0.790	0.524–1.192	0.262
Smoking history (ever versus never)	0.719	0.451–1.145	0.165
Tumor location	1.083	0.831–1.411	0.554
Tumor Size (cm) ( $\geqslant$ 3.5 versus $<$ 3.5)	1.247	0.790–1.970	0.343
Differentiation	0.923	0.695–1.226	0.580
Tumor invasion depth (T3 $+$ T4 versus T1 $+$ T2)	1.693	1.196–2.395	0.003
Lymph node metastasis (positive versus absent)	2.026	1.435–2.859	$<$ 0.001
TNM Stage (III $+$ IV versus I $+$ II)	1.831	1.282–2.616	0.001
Fibrinogen (g/L)	1.058	0.879–1.275	0.549
Hemoglobin (g/dl)	0.995	0.983–1.007	0.397
WBC ( $\times$ 10 ${}^{9}$ /L)	1.024	0.943–1.111	0.574
Platelet count ( $\times$ 10 ${}^{9}$ /L)	1.001	0.999–1.004	0.261
MPV (fL) ( $\leqslant$ 7.4 versus $>$ 7.4)	1.754	1.205–2.554	0.003

Table 4

The multivariate analysis of overall survival in EC patients

	Hazard	95% CI	$P$ -value
	ratio
Tumor invasion depth (T3 $+$ T4 versus T1 $+$ T2)	0.895	0.383–2.093	0.798
Lymph node metastasis (positive versus absent)	1.739	1.209–2.500	0.003
TNM Stage (III $+$ IV versus I $+$ II)	1.693	0.699–4.096	0.243
MPV (fL) ( $\leqslant$ 7.4 versus $>$ 7.4)	1.582	1.077–2.323	0.019

Variables that showed a p-value $<$ 0.10 in univariate analysis were included in a multivariate Cox proportional hazards regression model.

4. Discussion

The main finding of this study is that reduced MPV is significantly associated with shorter survival in EC patients.

It was well recognized that platelets act as a key modulator in tumor cell growth, angiogenesis, and metastasis. In EC, platelets were associated with lymphangiogenesis and lymphovascular invasion [16]. High expression of platelet-derived growth factor-BB (PDGF-BB) predicts lymph node metastasis independently from platelet count [17]. Cyclooxygenase-2 expression in esophageal squamous cell carcinoma cells was significantly increased following treatment with platelet activating factor [18]. However, measurement of most parameters reflecting activated platelets was expensive and not commonly used in clinical practice. Whereas MPV is available in routine praxis and can be easily obtained prior to treatment.

The reasons for reduced MPV in EC are unclear. Chronic inflammation has been implicated in the development and progression of cancer including EC [19]. MPV is an early indicator of activated platelets. Reduced MPV could be regarded as an enhanced consumption of large platelets in inflammatory states [11]. Recent studies showed that MPV were reduced in high-grade inflammatory diseases, which could be reversed in the course of anti-inflammatory therapy [11].

In accord with our results, Hyder et al. showed that changes in neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios during chemoradiation predict survival in trimodality EC patients [20]. McLaren et al. found that neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios predict treatment response to neoadjuvant therapy in EC [21]. These data are also consistent with the current knowledge that anti-platelet is considered to be a part of cancer adjuvant therapy [22]. However, the association between MPV and the prognosis varies in different cancer types. Low MPV level in non-small-cell lung cancer (NSCLC) was associated with unfavorable survival [14, 23], whereas high MPV in blood tumor, renal cancer, hepatocellular carcinoma, and lung cancer is associated with advanced stage cancers (or unfavorable disease-like thrombotic state) [24, 25, 26, 27].

The present study is not without limitations. First, our study was single-center retrospective in nature. Larger prospective randomized studies are needed to validate and extend our findings. Second, the patients were composed of Chinese. The application to other ethnic groups still needs further investigation.

Taken together, MPV may serve as a promising biomarker for predicting prognosis of EC patients.

Footnotes

Acknowledgments

This work was supported financially by grants from the Harbin Medical University Cancer Hospital (JJZD 2017-05).

Conflict of interest

All authors declare no conflict of interest.

References

Ferlay

Soerjomataram

Dikshit

Eser

Mathers

Rebelo

Parkin

D.M.

Forman

and Bray

, Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012, Int. J. Cancer 136(5) (2015), E359–386.

Enzinger

P.C.

and Mayer

R.J.

, Esophageal cancer, N. Engl. J. Med. 349(23) (2003), 2241–2252.

Jemal

Center

M.M.

DeSantis

and Ward

E.M.

, Global patterns of cancer incidence and mortality rates and trends, Cancer Epidemiol. Biomarkers Prev. 19(8) (2010), 1893–1907.

Tesfamariam

, Involvement of platelets in tumor cell metastasis, Pharmacol. Ther. 157 (2016), 112–119.

Suzuki

Aiura

Kitagou

Hoshimoto

Takahashi

Ueda

and Kitajima

, Platelets counts closely correlate with the disease-free survival interval of pancreatic cancer patients, Hepatogastroenterology 51(57) (2004), 847–853.

Long

Wang

Gao

and Zhou

, Prognostic significance of pretreatment elevated platelet count in patients with colorectal cancer: a meta-analysis, Oncotarget (2016).

Pietrzyk

Plewa

Denisow-Pietrzyk

Zebrowski

and Torres

, Diagnostic Power of Blood Parameters as Screening Markers in Gastric Cancer Patients, Asian Pac. J. Cancer Prev. 17(9) (2016), 4433–4437.

Ekici

Malatyalioglu

Kokcu

Kurtoglu

Tosun

and Celik

, Do Leukocyte and Platelet Counts Have Benefit for \Preoperative Evaluation of Endometrial Cancer, Asian Pac. J. Cancer Prev. 16(13) (2015), 5305–5310.

Qiu

Xie

and Lu

, Preoperative plasma fibrinogen, platelet count and prognosis in epithelial ovarian cancer, J. Obstet. Gynaecol. Res. 38(4) (2012), 651–657.

10.

Seretis

Youssef

and Chapman

, Hypercoagulation in colorectal cancer: what can platelet indices tell us, Platelets 26(2) (2015), 114–118.

11.

Gasparyan

A.Y.

Ayvazyan

Mikhailidis

D.P.

and Kitas

G.D.

, Mean platelet volume: a link between thrombosis and inflammation, Curr. Pharm. Des. 17(1) (2011), 47–58.

12.

Shen

X.M.

Xia

Y.Y.

Lian

Zhou

X.L.

Han

S.G.

Zheng

Gong

F.R.

Tao

Mao

Z.Q.

and Li

, Mean platelet volume provides beneficial diagnostic and prognostic information for patients with resectable gastric cancer, Oncol Lett 12(4) (2016), 2501–2506.

13.

Tanriverdi

Menekse

Teker

Oktay

Nur

P.K.

Gunaldi

Kocar

Kacan

Bahceci

Avci

Akman

Cokmert

Yesil-Cinkir

and Teoman

Y.M.

, The mean platelet volume may predict the development of isolated bone metastases in patients with breast cancer: a retrospective study of the Young Researchers Committee of the Turkish Oncology Group (TOG), J BUON 21(4) (2016), 840–850.

14.

Kumagai

Tokuno

Ueda

Marumo

Shoji

Nishimura

Fukui

and Huang

C.L.

, Prognostic significance of preoperative mean platelet volume in resected non-small-cell lung cancer, Mol Clin Oncol 3(1) (2015), 197–201.

15.

Kemal

Demirağ

Ekiz

and Yücel

, Mean platelet volume could be a useful biomarker for monitoring epithelial ovarian cancer, J Obstet Gynaecol 34(6) (2014), 515–518.

16.

Schoppmann

S.F.

Alidzanovic

Schultheis

Perkmann

Brostjan

and Birner

, Thrombocytes Correlate with Lymphangiogenesis in Human Esophageal Cancer and Mediate Growth of Lymphatic Endothelial Cells In Vitro, PLoS ONE 8(6) (2013), e66941.

17.

Krzystek-Korpacka

Diakowska

Gamian

and Matusiewicz

, Increase in serum platelet-derived growth factor (PDGF)-BB reflects lymph node involvement in esophageal cancer patients independently from platelet count, Exp. Oncol. 33(3) (2011), 140–144.

18.

Wang

L.S.

Chow

K.C.

and Wu

Y.C.

, Effects of platelet activating factor, butyrate and interleukin-6 on cyclooxygenase-2 expression in human esophageal cancer cells, Scand. J. Gastroenterol. 37(4) (2002), 467–475.

19.

Mantovani

Allavena

Sica

and Balkwill

, Cancer-related inflammation, Nature 454(7203) (2008), 436–444.

20.

Hyder

Boggs

D.H.

Hanna

Suntharalingam

and Chuong

M.D.

, Changes in neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios during chemoradiation predict for survival and pathologic complete response in trimodality esophageal cancer patients, J Gastrointest Oncol 7(2) (2016), 189–195.

21.

McLaren

P.J.

Bronson

N.W.

Hart

K.D.

Vaccaro

G.M.

Gatter

K.M.

Thomas

C.R.

Hunter

J.G.

and Dolan

J.P.

, Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratios can Predict Treatment Response to Neoadjuvant Therapy in Esophageal Cancer, J. Gastrointest. Surg. 21(4) (2017), 607–613.

22.

Mezouar

Frere

Darbousset

Mege

Crescence

Dignat-George

Panicot-Dubois

and Dubois

, Role of platelets in cancer and cancer-associated thrombosis: Experimental and clinical evidences, Thromb. Res. 139 (2016), 65–76.

23.

Inagaki

Kibata

Tamaki

Shimizu

and Nomura

, Prognostic impact of the mean platelet volume/platelet count ratio in terms of survival in advanced non-small cell lung cancer, Lung Cancer 83(1) (2014), 97–101.

24.

Kissova

Bulikova

Ovesna

Bourkova

and Penka

, Increased mean platelet volume and immature platelet fraction as potential predictors of thrombotic complications in BCR/ABL-negative myeloproliferative neoplasms, Int. J. Hematol. 100(5) (2014), 429–436.

25.

Gunduz

Mutlu

Uysal

Coskun

H.S.

and Bozcuk

, Elucidating the correlation between treatment with tyrosine kinase inhibitors and mean platelet volume in patients with metastatic renal cell cancer, Oncol Lett 8(5) (2014), 2249–2252.

26.

Cho

S.Y.

Yang

J.J.

You

Kim

B.H.

Shim

Lee

H.J.

Lee

W.I.

Suh

J.T.

and Park

T.S.

, Mean platelet volume/platelet count ratio in hepatocellular carcinoma, Platelets 24(5) (2013), 375–377.

27.

Omar

Tanriverdi

Cokmert

Oktay

Yersal

Pilancı

K.N.