Combination of preoperative D-dimer and mean platelet volume predicts postoperative deep venous thrombosis in breast cancer patients

Abstract

BACKGROUND:

Deep venous thrombosis (DVT) is associated with severe morbidity and mortality in cancer. Mean platelet volume (MPV) is an indicator of activated platelets.

OBJECTIVE:

We aimed to investigate whether the combination of D-dimer and MPV could have a better performance in predicting deep venous thrombosis (DVT) in patients with breast cancer.

MEHTODS:

In 342 consecutive breast cancer patients without preoperative DVT, we measured the preoperative D-dimer and MPV levels. Compression ultrasonography was performed in all breast cancer patients before surgery, as well as one month, three months, six months, and twelve months.

RESULTS:

During a median period of twelve months, 15 of the 234 patients (6.4%) developed DVT. MPV was reduced and D-dimer was increased in patients with DVT events compared to those without DVT. Multivariate Cox analysis revealed that both MPV and D-dimer were independent predictors for DVT events. The area under the ROC curve was 0.619 (95% CI: 0.553 to 0.681) when D-dimer was used alone, whereas it increased to 0.790 (95% CI 0.732 to 0.840, $p<$ 0.001) with the addition of MPV.

CONCLUSIONS:

The combination of preoperative D-Dimer and MPV improves the predictive power of postoperative DVT risk in breast cancer patients.

Keywords

Breast cancer D-dimer mean platelet volume risk prediction

1. Introduction

Deep venous thrombosis (DVT) is associated with severe morbidity and mortality in cancer. 50% of DVTs are asymptomatic and 30% will have additional complications [1]. Therefore, accurate prediction for DVT is of utmost clinical importance. D-dimer, a fibrin degradation product, is the most well established biomarker and used to assesss for DVT in clinical practice. However, there are nonspecific D-dimer elevations in cancer patients.

Platelets play a key role in atherogenesis, inflammation, and atherothrombosis [2]. Mean platelet volume (MPV) is a measure of platelet size and is clinically used as an indicator of activated platelet [3]. Previous studies have stated that increased MPV is associated with diabetes mellitus, hypertension, cardiovascular disease, and DVT event [4, 5, 6, 7]. However, accumulating evidence recently demonstrated that MPV is reduced in cancer patients that developed thrombosis [8]. In addition, decreased MPV is associated with increased venous thromboembolism risk and shorter survival in cancer patients [9].

In the current study, we sought to investigate whether a combination of MPV and D-dimer prior to surgery could better predict the postoperative DVT in breast cancer.

2. Methods

2.1 Study population

Consecutive breast cancer cases were admitted to Harbin Medical University Cancer Hospital between January 2014 and December 2014. All patients undergone complete surgical resection. The pathologic diagnoses of breast cancer were evaluated by pathologists from biopsy reports. None of the patients received preoperative chemotherapy or radiation therapy. Patients were excluded if they had hematological disorders, hypertension, diabetes mellitus, and medical treatment with anticoagulant, and acetylic salicylic acid.

Our study is a prospective study. A total of 338 patients enrolled in this study. Seventeen patients were excluded because they refused to give informed consent. Forty-six patients with hypertension, and 41 patients with diabetes mellitus were also excluded. The final analysis included 234 patients. All subjects were followed-up for twelve months. Informed consent was obtained from every subject. The study protocol was approved by the Ethics Committee of Harbin Medical University Cancer Hospital.

2.2 Biochemical parameters

All participants completed a standardized questionnaire including medical history, lifestyle factors and smoking habits. After a 10-hour overnight fast, blood samples were collected from participants. Platelet-poor plasma was then assayed using second-generation latex immunoassay kit that provides quantitative measure of D-dimer. It was analysed on Sysmex CS-5100 (Siemens Diagnostics, Erlangen, Germany). The standard cut-off level of D-dimer in our hospital is 0.55 mg/L. Platelet count and MPV were determined with 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 in order to prevent in vitro platelet activation.

2.3 Diagnosis of deep venous thrombosis

An experienced ultrasonographist performed the compression ultrasonography according to standard procedures (grey scale, B-mode, color Doppler) with a high-end ultrasound scanner (DC-8 EXP, Mindray, Shenzhen, China) prior to the surgery, as well as one month, three months, six months, and twelve months. If the patients were in cases of clinical signs of DVT, an additional compression ultrasonography was performed.

2.4 Statistical analysis

Continuous variables were presented as means $\pm$ SD or median (inter-quartile range). Categorical variables were presented as percentages. Student $t$ test was used for the continuous variables, while the Chi-square statistical test was used for the categorical variables. Survival curves and analysis were performed using the Kaplan-Meier method and log-rank test. To determine the independent prognostic factor, multivariate analysis was carried out using the Cox proportional hazard model, hazard ratios (HRs) and 95% confidence intervals (95% CIs). To examine the predictive value, we constructed receiver operating characteristic (ROC) curves with DVT as outcome. The area under the ROC curve (AUC) was calculated for the D-Dimer model and for the combination of D-Dimer plus MPV. The differences in AUC were detected by using MedCalc version 15.0. A two tailed $p<$ 0.05 indicated statistical significance. All statistical analyses were performed using SPSS Statistics version 22.0 (SPSS Inc., Chicago, IL, USA).

3. Results

During a median follow-up time of twelve months, 15 (6.4%) patients had DVT events. The baseline characteristics of the patients with DVT or without DVT events were summarized in Table 1. Compared to the patients without DVT, those with DVT were older, and with a higher frequency of venous thrombo-embolism. In addition, MPV was lower and D-dimer was higher in DVT patients.

Table 1
Baseline characteristics of patients according to the postoperative DVT status

Variables	With DVT		Without DVT		p value
Age (years)	55.3	$\pm$ 8.8	49.6	$\pm$ 9.2	0.022
BMI (kg/m ${}^{2}$ )	24.5	$\pm$ 3.2	23.4	$\pm$ 3.4	0.255
Smoker ( $n$ , %)	1 (6.7)		6 (2.7)		0.388
WBC ( $\times$ 10 ${}^{9}$ /L)	5.73	$\pm$ 1.42	6.09	$\pm$ 1.78	0.443
Hemoglobin (g/dl)	131.6	$\pm$ 16.2	134.5	$\pm$ 12.5	0.407
Platelet count	256.3	$\pm$ 63.4	237.1	$\pm$ 51.6	0.172
( $\times$ 10 ${}^{9}$ /L)
MPV (fL)	8.0	$\pm$ 1.0	9.1	$\pm$ 1.5	0.003
PDW (%)	16.5	$\pm$ 2.1	16.7	$\pm$ 1.5	0.595
D-dimer ( $\mu$ g/mL)	1.24	$\pm$ 1.77	0.48	$\pm$ 0.15	$<$ 0.001
Differentiation					0.542
Well/moderate	4 (26.7)		44 (20.1)
Poor	11 (73.3)		175 (79.9)
Molecular subtype					$<$ 0.001
Luminal-A	5 (33.3)		92 (42.0)
Luminal-B	4 (26.7)		63 (28.8)
HER 2+	5 (33.3)		31 (14.2)
TNBC	1 (6.7)		33 (15.1)
Clinical stage ( $n$ , %)					0.390
I/II	12 (80.0)		192 (87.7)
III/IV	3 (20.0)		27 (12.3)
Past history of	1 (6.7)		1 (0.5)		0.011
VTE ( $n$ , %)

Data are expressed as means (SD) or percentage. BMI, body mass index; WBC, white blood cell; MPV, mean platelet volume; PDW, platelet distribution width; DVT, deep venous thrombosis; VTE, venous thrombo-embolism.

A ROC curve for DVT prediction was plotted to verify the optimal cut-off value for MPV, which was 9.0 fL (Fig. 1). It demonstrated that MPV predicts DVT with a sensitivity of 93.3% and a specificity of 45.7% (AUC $=$ 0.763, 95% CI: 0.703–0.816, $p<$ 0.001).

Figure 1.

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

To correct for significant prognostic factors, variables were first examined in cancer patients with the univariate Cox regression model (Table 2). MPV, D-dimer, and past history of venous thrombo-embolism showed significant associations with a higher risk of DVT. The independent prognostic values were further tested in multivariate analysis. MPV remained as an independent predictor for poor prognosis in patients with breast cancer (HR, 9.446; 95% CI, 1.232–72.442; $p=$ 0.031) (Table 3).

Table 2

Univariate Cox analysis

	Hazard	95% CI		$P$ -value
	ratio
Age (years)
( $\leqslant$ 50 versus $>$ 50)	2.379	0.813	–6.960	0.114
Smoker (yes versus no)	2.546	0.335	–19.365	0.367
BMI (kg/m ${}^{2}$ )	1.078	0.952	–1.221	0.237
WBC ( $\times$ 10 ${}^{9}$ /L)	0.880	0.634	–1.222	0.447
Hemoglobin (g/dl)	0.984	0.947	–1.021	0.386
Platelet count ( $\times$ 10 ${}^{9}$ /L)	1.006	0.997	–1.015	0.185
MPV (fL)
( $>$ 9.0 versus $\leqslant$ 9.0)	5.192	1.172	–23.010	0.030
PDW (%)	0.933	0.709	–1.228	0.621
D-dimer (mg/L)
( $>$ 0.58 versus $\leqslant$ 0.58)	17.970	5.635	–57.307	$<$ 0.001
Differentiation
(Poor versus Well/
moderate)	0.714	0.227	–2.242	0.564
Molecular subtype	1.094	0.693	–1.727	0.699
Past history of VTE ( $n$ , %)	13.580	1.775	–103.901	0.012
Clinical stage
(III/IV versus I/II)	1.773	0.500	–6.285	0.375

Abbreviations: see to Table 1.

Table 3

Multivariate Cox proportional hazards analysis

	Hazard	95% CI	$P$ -value
	ratio
MPV (fL) ( $>$ 9.0 versus $\leqslant$ 9.0)	9.446	1.232–72.442	0.031
D-dimer (mg/L)
( $>$ 0.58 versus $\leqslant$ 0.58)	2.904	1.046–8.060	0.041
Past history of VTE ( $n$ , %)	9.338	1.178–74.047	0.034

Variables that showed a p-value $<$ 0.10 in univariate analysis were included in a multivariate Cox proportional hazards regression model. CI, confidence interval. Abbreviations: see to Table 1.

The estimated cumulative incidence of DVT events by the Kaplan-Meier curve was shown in Fig. 2. With a median follow up of twelve months, 15 (6.4%) patients had DVT events. The prevalence of DVT was significantly higher in low MPV group than normal MPV group (10.5% vs. 1.0%, $p=$ 0.003).

Figure 2.

Kaplan-Meier analysis of the cumulative incidence of deep venous thrombosis according to preoperative MPV levels.

Figure 3.

Receiver-Operator Characteristics (ROC) curve analysis. The combination of MPV and D-dimer could improve the predictive power of postoperative DVT.

As shown in Table 3, D-dimer could independently predict future DVT events in breast cancer patients. To assess whether the addition of MPV to D-dimer could improve the prediction of DVT, ROC analysis was performed (Fig. 3). The area under the ROC curve was 0.619 (95% CI: 0.553 to 0.681, $p=$ 0.191) when D-dimer was used alone, whereas it increased to 0.790 (95% CI 0.732 to 0.840, $p<$ 0.001) when the combination of MPV with D-dimer was used.

4. Discussion

In this study, we found that preoperative MPV is an independent prognostic factor for postoperative DVT. Moreover, D-dimer plus MPV enhanced the prediction of DVT risk.

A positive preoperative D-dimer was associated with a higher cumulated incidence of postoperative deep venous thrombosis in patients with colorectal cancer [10]. However, the nonspecific elevations of D-dimer in cancer patients limit its wider applicability [11]. We showed that MPV confers an important additive effect to D-dimer. One possible explanation is that increased MPV indicates platelet activation which exerts extensive effects on atherogenesis, inflammation, and atherothrombosis [2]. Increased MPV is not only associated with myocardial infarction and heart failure, but also with peripheral artery disease and stroke [12, 13, 14]. We previously reported that elevated MPV is positively correlated to arterial stiffness measured by the brachial-ankle pulse wave velocity [15].

There is a complex interplay between platelet-induced tumor growth and tumor cell-induced platelet activation [16]. In breast cancer, platelet-derived growth factor (PDGF) expression is associated with biological aggressiveness via NFkappaB signaling pathway [17, 18]. Moreover, platelet-derived lysophosphatidic acid accelerates osteolytic bone metastases [19]. A study confirmed increased levels of NFkappaB-dependent markers in cancer-associated DVT [20]. These discoveries make the PDGFR/PDGF system an attractive oncologic therapeutic target. A recent report demonstrated that combinations of anti-platelet drugs inhibit breast cancer cell-induced platelet aggregation [21]. In agreement with the studies above, our study indirectly confirmed the findings using a simple platelet index. In addition, our results indicate that evaluation of preoperative D-dimer and MPV levels will improve risk prediction and help more physicians to better make therapeutic decisions.

Our study has several limitations. First, this was a single-center study and additional larger multicenter studies are needed to confirm our results. Second, the sample size is relatively small. Third, the patients in our study are limited to Chinese patients, so that the conclusions should be drawn cautiously to other ethnic group.

In conclusion, the combined use of preoperative MPV and D-dimer may be useful in predicting postoperative DVT events in breast cancer patients.

Footnotes

Acknowledgments

This work was supported financially by grants from Open Foundation of Key Laboratory of Myocardial Ischemia, Chinese Ministry of Education, Harbin, China, grant No. KF201404.

Conflict of interest

None declared.

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Combination of preoperative D-dimer and mean platelet volume predicts postoperative deep venous thrombosis in breast cancer patients

Abstract

BACKGROUND:

OBJECTIVE:

MEHTODS:

RESULTS:

CONCLUSIONS:

Keywords

1. Introduction

2. Methods

2.1 Study population

2.2 Biochemical parameters

2.3 Diagnosis of deep venous thrombosis

2.4 Statistical analysis

3. Results

Table 1 Baseline characteristics of patients according to the postoperative DVT status

Footnotes

Acknowledgments

Conflict of interest

References

Table 1
Baseline characteristics of patients according to the postoperative DVT status