Incidence and potential predictors of thromboembolic events in epithelial ovarian carcinoma patients during perioperative period

Journal Pre-proof Incidence and potential predictors of thromboembolic events in epithelial ovarian carcinoma patients during perioperative period Qingqing Zhou, Chenchen Zhu, Zhen Shen, Tianjiao Zhang, Min Li, Jing Zhu, Jiwei Qin, Yanhu Xie, Wei Zhang, Rongzhu Chen, Guihong Wang, Lili Qian, Dabao Wu, Björn Nashan, Ying Zhou PII:

S0748-7983(20)30045-7

DOI:

https://doi.org/10.1016/j.ejso.2020.01.026

Reference:

YEJSO 5619

To appear in:

European Journal of Surgical Oncology

Received Date: 25 November 2019 Revised Date:

6 January 2020

Accepted Date: 17 January 2020

Please cite this article as: Zhou Q, Zhu C, Shen Z, Zhang T, Li M, Zhu J, Qin J, Xie Y, Zhang W, Chen R, Wang G, Qian L, Wu D, Nashan Bjö, Zhou Y, Incidence and potential predictors of thromboembolic events in epithelial ovarian carcinoma patients during perioperative period, European Journal of Surgical Oncology (2020), doi: https://doi.org/10.1016/j.ejso.2020.01.026. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Ltd.

Incidence and potential predictors of thromboembolic events in

epithelial

ovarian

perioperative period

1 / 24

carcinoma

patients

during

Qingqing Zhou#1, Chenchen Zhu#1, Zhen Shen2, Tianjiao Zhang2, Min Li2, Jing Zhu2, Jiwei Qin3, Yanhu Xie4, Wei Zhang4, Rongzhu Chen5, Guihong Wang5， ，Lili Qian2， ，Dabao Wu2*, Björn Nashan3*, Ying Zhou1,2*

1. Anhui Medical University, Anhui Provincial Hospital, Hefei, 230001, China; 2. Department of Obstetrics and Gynecology, The First Affiliated Hospital of University of Science & Technology of China, Anhui Provincial Hospital, Hefei, Anhui Province 230001, and China. 3.Organ Transplantation Center, The First Affiliated Hospital of University of Science & Technology of China, Anhui Provincial Hospital, Hefei, Anhui Province 230001, China; 4. Department of Anesthesiology, the First Affiliated Hospital of University of Science & Technology of China, Anhui Provincial Hospital, Hefei, Anhui Province 230001, and China; 5. Operation room, the First Affiliated Hospital of University of Science & Technology of China, Anhui Provincial Hospital, Hefei, Anhui Province 230001, and China;

# Qingqing Zhou and Chenchen Zhu are co-first author

2 / 24

*Corresponding Author

Dabao Wu, Department of Obstetrics and Gynecology, The First Affiliated Hospital of University of Science & Technology of China, Anhui Provincial Hospital, Hefei, Anhui Province 230001, China. E-mail: [email protected] Björn Nashan: Organ Transplantation Center, The First Affiliated Hospital of University of Science & Technology of China, Anhui Provincial Hospital,

Hefei,

Anhui

Province

230001,

China.;

E-mail:

[email protected] Ying Zhou, Department of Obstetrics and Gynecology, The First Affiliated Hospital of University of Science & Technology of China, Anhui Provincial Hospital, Hefei, Anhui Province 230001, China. E-mail: [email protected]

3 / 24

Abstract Objective: To assess the incidence and the risk factors of venous thromboembolism (VTE) in patients with epithelial ovarian carcinoma (EOC) during the perioperative period. Methods: A retrospective analysis was conducted on the patients with epithelial ovarian cancer treated in our hospital, between January 2017 and July 2019, and a comprehensive review of the medical documentation was performed to collect relevant data. We then analyzed the related factors of the thrombosis in the EOC patients, using univariate and multivariate analysis to identify significant risk factors for VTE, and bootstrap resampling method was used to verify the multivariate analysis results. The ROC curve methods were conducted to evaluate the diagnostic value for the prediction of VTE. Results: We analyzed 233 cases of patients with EOC, of whom the incidence of VTE was 11.16%. According to multivariate and 5000 bootstrap samples analysis, preoperative D-dimer levels (>4.215µg/ml， p=0.041 and p=0.032) and comorbid of cerebral infarction (p<0.001 and p<0.001) had statistical significance in predicting VTE events; bootstrap analysis also found the Alb, CA125, OCCC had statistical significance. While According to multivariate and 5000 bootstrap samples analysis, age (>50.5 years old, p=0.019 and p=0.002) and nonoptimal debulking surgery (p=0.007 and p=0.002) showed significance in predicting VTE after surgery; bootstrap analysis also found the D-dimer levels (>4.215µg/ml) and tuberculosis had statistical significance. Conclusion: More effective thromboprophylaxis and pre-test assessment is necessary for EOC patients. For prediction VTE events, D-dimer levels (>4.215µg/ml) were the independent predictors before operation. Age and debulking surgery were the independent predictors post operation. 4 / 24

Keywords: Epithelial ovarian cancer (EOC), Venous thromboembolism (VTE), Perioperative, D-dimer, Optimal debulking surgery

5 / 24

1

1.Introduction

2

Epithelial ovarian cancer (EOC) accounts for 90% of ovarian

3

carcinoma and is the most lethal malignant tumor in gynecology (1).

4

Venous thromboembolism, which comprised by deep vein thrombosis

5

(DVT) and pulmonary embolism (PE), is a multifactorial disease and one

6

of the leading causes of death in active cancer patients (2, 3). It has been

7

estimated that 14% of deaths in hospitalized patients with malignancy due

8

to PE and 8.33% of patients with cancer die of VTE within 30 days of

9

their surgery (4).

10

Women with gynecologic cancer are at a higher risk of VTE

11

compared with other cancers, particularly in epithelial ovarian cancer, due

12

to their advanced age, advanced stages, larger pelvic tumors, massive

13

ascites, hyper viscosity syndrome, chemotherapy and prolonged

14

abdominal and pelvic surgeries (4, 5). VTE increases the difficulty in the

15

treatment of ovarian cancer and affects the prognosis of ovarian cancer

16

patients with cytoreduction surgery. Moreover, it as a significant impact

17

on hospital mortality and costs (6, 7). Many clinical risk factors have

18

been reported to be associated with VTE, which are essentially classified

19

into patient-related (age, comorbidities, etc.), cancer-related (primary site,

20

stage, histological type, etc.), and treatment-related factors (operation and

21

chemotherapy) (8). However, so far, there has been no evidence that any

22

of these factors can truly identify the risk of developing venous

23

thrombosis complications in patients with ovarian cancer. As we all know,

24

the perioperative period ― the days or weeks following tumor

25

excision ― is an essential period to improve the survival of patients (9).

26

This being the case, the present study aims to describe the incidence of

27

VTE in patients with epithelial ovarian carcinoma during perioperative

28

period and to investigate the risk factors associated with VTE.

29

6 / 24

30

2.Materials and methods

31

2.1 Patients

32

The 314 cases of patients collected in this retrospective study were

33

treated at the First Affiliated Hospital of the University of Science &

34

Technology of China (USTC) from January 2017 to July 2019.

35

Eighty-one patients were excluded because of inadequate clinical data

36

collected during the perioperative period. Patients who underwent

37

cytoreductions and were histologically diagnosed as having ovarian

38

cancer after surgery were enrolled. We collected patients with a history of

39

VTE before cytoreduction in the perioperative period or when VTE

40

occurred within 30 days after their operations.

41

All patients had standard pre-admission testing, and additional

42

preoperative medical examinations were requested at the surgeon's

43

discretion. Pharmacologic prophylaxis and VTE treatment, such as

44

heparin or low-molecular-weight heparins, were administered to patients.

45

Women with DVT systematically underwent an enhanced CT of lungs to

46

search for a PE. Patients without macroscopic residual disease or with

47

residual disease less than 1 cm were defined as having received optimal

48

debulking surgery.

49

The diagnosis of deep venous thrombosis was based on clinical signs

50

and confirmed by color Doppler ultrasound; pulmonary embolism was

51

diagnosed by spiral computerized tomography (CT).

52

2.3 Data collection

53

The data were obtained retrospectively, include age, body mass

54

index (BMI), Federation International of Gynecology and Obstetrics

55

stage

56

chemotherapy and intermediate cytoreduction), duration of hospital stay,

57

postoperative hospital stay, postoperative initial chemotherapy interval, 7 / 24

(FIGO,

2014)

(excluding

patients

receiving

neoadjuvant

58

diagnosed time of thrombosis, type and site of thrombosis, laboratory

59

tests (usually a week before surgery and 3 days after surgery), example

60

platelet (Plt) count, albumin (Alb) level, preoperative cancer antigen

61

(CA)125 level and coagulation function test (including Dimerized

62

plasmin fragment D (D-dimer), activated partial thromboplastin time

63

(APTT), thrombin time (TT), prothrombin time (PT), fibrinogen (Fg) ),

64

postoperative pathological, operative procedures, surgical complexity

65

scores (SCS) (10), and so on. BMI was categorized as less than 27kg/m2

66

or equal to or more than 27kg/m2, according to China’s standard of

67

obesity.

68

2.4 Statistical analysis

69

Statistical analysis was performed using SPSS v.20.0 (IBM Corp.,

70

Armonk, NY, USA). . For each variable, mean ± standard deviation or

71

medians and interquartile range, range and counts (expressed as

72

percentages), were computed to describe the continuous and categorical

73

variables, respectively. For categorical variables, differences in variables

74

between the VTE and non-VTE groups before or after surgery were

75

assessed using the chi-square test or Fisher exact test, as appropriate. For

76

continuous variables Student’s t-test or the Mann–Whitney test was used,

77

as appropriate. ROC (receiver operating characteristic) curve methods

78

were conducted to evaluate the diagnostic value for the prediction of VTE.

79

Odds ratio (OR) and 95% confidence intervals (95%CI) were calculated

80

using a conventional univariate analysis or multivariate logistic

81

regression analysis to determine the association between different risk 8 / 24

82

factors and the occurrence of VTE. We also did the multivariate logistic

83

regression analysis with bootstrapping in SPSS. The value of p<0.05 was

84

considered statistically significant and all p-values reported were

85

two-sided. A bootstrap with 5000 permutated samples containing 233

86

patients each was performed. The study was approved for retrospective

87

data analysis by the First Affiliated Hospital of USTC Expert

88

Commission for Physician Confidentiality, and by the institutional ethical

89

review board.

90 91

9 / 24

92

3.Results

93

3.1 Patients characteristics

94

Two hundred and thirty-three patients were finally analyzed in

95

our study, among them 26 (11.16%) had VTE, and nine of the 26

96

were diagnosed with VTE before surgery, while 16 were diagnosed

97

after surgery, and one patient had VTE both before and after surgery.

98

We analyzed characteristics of patients in the VTE group and

99

non-VTE group both before and after their operations (Table 1 and

100

Table 2).

101

Past medical history or comorbidities were shown in Table1-2, and

102

the relationship between the comorbidities and VTE were presented.

103

Hypertension (p=0.005) and cerebral infarction (p<0.001) were related

104

with VTE events before operation; and obsolete pulmonary tuberculosis

105

(p=0.028) was related with VTE events after operation.

106

The mean level of albumin in the VTE group was 38.0g/ml

107

contrasted with 42.2g/ml in the non-VTE group. The mean level of

108

D-dimer and CA125 in the VTE before surgery group was 7.5 µg/ml and

109

3401.8U/ml respectively; while the mean level of D-dimer and CA125 in

110

the non-VTE before surgery group was 2.5 µg/ml and 1054.1U/ml

111

respectively . Albumin (<38g/L), D-dimer (>7.5 μ g/mL), CA125

112

(>3401.8U/ml) were significantly related with the VTE event before

113

operation.

114

The mean level of age in the VTE group was 65 years contrasted with

115

53 years in the non-VTE group. SCS (p=0.027) and residue tumors (p=

116

0.006) were related with the VTE events after operation. Both

117

pre-operation

118

g/mL, p=0.046) of D-dimer in the patients were relate with the VTE 10 / 24

(>3.3 μ g/mL, p=0.011) and post-operation

(>6.2 μ

119

events after operation. Also, the occurrence of VTE has longer hospital

120

stay days (18 days v 12 days) in the VTE group than the non-VTE group

121

(p=0.006).

122 123

3.2 Characteristics of patients with VTE

124

We analyzed the distribution of VTE by pathological types and FIGO

125

stage (Supplement Tables 1 and 2). The ovarian clear cell carcinoma

126

(OCCC) had the highest incidence of VTE which was 26.32%, almost

127

two times of endometroid carcinoma and more than two times of serous

128

carcinoma. Also, OCCC patients tended to have DVT and its

129

complication, PE, while serous cancer prone to develop distal sites

130

(below the knee level) tended to have DVT alone. The incidence of VTE

131

in different stages was stage Ⅰ 7.32%, Ⅰ 4.55%, Ⅰ 12.24%, Ⅰ 18.75%.

132

Compared to early stages (Ⅰand Ⅰ), VTE occurred twice as often in

133

advanced stages (Ⅰ and Ⅰ). Half of the patients with VTE in Stage Ⅰ had

134

DVT alone in distal sites. Patients in Stage Ⅰ were more likely to develop

135

PE.

136

Additionally, we analyzed the effect of different cytoreduction surgery

137

in postoperative VTE (Supplement Table 3). The incidence of VTE in

138

primary cytoreductive surgery, intermediate cytoreductive surgery, and

139

re-cytoreductive surgery was 8.44% (n=13), 7.5% (n=3) and 2.56%

140

(n=1), respectively. Pairwise comparison in the three-groups used the

141

Chi-square test (p=1, p=0.358, p=0.615), and we received the result that

142

suggests there is no correlation between the 3 surgery methods with

143

VTE events.

144

Moreover, the detailed information of VTE patients is listed in

145

Supplement Table 4. Patients with confirmed VTE were treated

146

immediately with standard anticoagulation therapy, with five of them also 11 / 24

147

having filter implants in the inferior vena cava (IVC). Of these women,

148

one had thrombolysis before her operation. Eleven patients had VTE in

149

their left leg and five patients had it in their right leg. There were five

150

patients with VTE in both legs, with half of them also having pulmonary

151

embolism. Eleven patients had pulmonary embolism, including one

152

patient who also had VTE in her brain. One patient treated with NACT

153

developed VTE before surgery and another patient after her first adjuvant

154

chemotherapy after surgery.

155

3.3 Conventional Univariate and multivariate analysis

156

According to the results of correlation analysis in Tables 1 and 2, we

157

conducted the ROC curves (Figure 1) to evaluate the diagnostic value of

158

different factors in preoperative and postoperative VTE and received their

159

cut-off values (Table 3 and 4). Through a univariate analysis (Table 3),

160

we found that the pathology type of OCCC, hypertension, cerebral

161

infraction, preoperative levels of albumin, D-dimer and CA125 were

162

associated with VTE before operations. Both D-dimer and cerebral

163

infarction were still statistically significantly associated with preoperative

164

VTE in multivariate analysis.

165

In Table 4, many factors were found to be related to postoperative

166

VTE, including age >50.5 years old, postoperative level of albumin <

167

34.65g/L and D-dimer >4.71µg/L, an SCS of 3, nonoptimal debulking

168

surgery and postoperative hospital stay >16.5 days, also, comorbid of

169

tuberculosis. Among them older age and nonoptimal debulking surgery

170

were significantly associated with post-operative VTE in multivariate

171

analysis.

172

3.4 Bootstrap Analysis 12 / 24

173

The multiple regression results with bootstrap performing 5,000

174

times selection procedure in permutated samples from the original data

175

with 233 patients each is shown in Table 3,4. According to the

176

conventional multivariate analysis, we have validated that both D-dimer

177

and cerebral infarction were significantly associated with preoperative

178

VTE in multivariate analysis; both older age and nonoptimal debulking

179

surgery were also significantly associated with post-operative VTE in

180

multivariate analysis. Furthermore, in bootstrap analysis, we have found

181

that

182

CA125 >1474U/ml (p<0.001) and the pathology type of OCCC (p=0.011)

183

were also related with the VTE event before operation; while

184

D-dimer >4.71µg/L and comorbid of tuberculosis were also related with

185

the VTE event after operation.

186 187

13 / 24

preoperative

level

of

albumin

<

39.85g/L

(p=0.032),

188

4. Discussion

189

When compared with other solid cancers, epithelial ovarian cancer

190

patients are more likely to have VTE (11, 12). According to a previous

191

study, the incidence of VTE in ovarian cancer ranged from 14.5% to 34%

192

(13-18). Most of the data were shown in 6-24 months of cumulative

193

incidence of VTE(12, 18-20),while the incidence of VTE in perioperative

194

patients in our study was 11.16% (n=26) lower than the previous study

195

mentioned above, it maybe because of the different analysis standards we

196

used or because of the possibility that we may have missed silent VTE.

197

The complete cytoreduction rate of ovarian cancer depends greatly on

198

physician/surgeon-related factors including surgical training offered at the

199

center, experience, and risk tolerance; patient-related factors like

200

performance status and comorbidity; and disease-related factors like

201

tumor biological aggressive behavior and extension of disease. The

202

proportion of patients who undergo optimal cytoreduction for advanced

203

disease in different centers varies considerably in the literature from 15–

204

85%(21). Therefore, the VTE events were analyzed in our center

205

according to our cytoreduction levels and managements of peri-operation

206

to guide us how to management the patients before and after operation in

207

hospital. We analyzed VTE in perioperative EOC patients, which means

208

that the risk factors for preoperative and postoperative VTE were

209

different. As for VTE before surgery, it was more closely related with

210

tumor characteristics and the patients’ comorbid conditions. As for VTE

211

after surgery, there were many additional risk factors, particularly due to

212

the damage that is often caused by large pelvic surgery and the poor

213

condition of patients after operation.

214

Among the six variables predicted as risk factors for VTE before

215

surgery, the preoperative level of D-dimer, and cerebral infraction were 14 / 24

216

most significant. This finding is partially in agreement with previous

217

studies (17, 18, 22). Patients with OCCC were found to more frequently

218

have VTE (23, 24). Although the number of this pathology type was

219

small, the incidence of VTE was the highest (26.32%) in our study. So,

220

we should pay more attention to patients with this pathology type for

221

preventing VTE. But as opposed to the research of Abu Saadeh et al. (24),

222

the advanced stage of OC was not an independent factor before operation

223

in our analysis, SCS was also not related with the VTE occurrence after

224

operation in multivariate analysis. High plasma D-dimer level was a

225

common characteristic of patients with advanced cancer and was relative

226

to both the risk of VTE and the risk of tumor progression (25, 26). It was,

227

moreover, useful for screening out preoperative VTE, particularly silent

228

VTE. The cut-off value of D-dimer for predictive VTE is still

229

controversial. Ebina et al.(17) have suggested that the cut-off value of

230

D-dimer was 10.9µg/ml, while Kawaguchi et al. (27) have recommended

231

that the cut-off value should be greater than 1.5µg/ml in ovarian cancer;

232

the mean D-dimer level was 4.1 µg/ml in their research. However,

233

according to the cut-off value in our study, we suggest that if the D-dimer

234

value

235

post-operation, then doctors should be alert for VTE development.

is

more

than

4.215µg/ml

pre-operation

and

4.71µg/ml

236

With regard to the postoperative factors in our study, age, and

237

nonoptimal debulking surgery were found to be independent risk factor

238

for VTE after operation in our multivariate and bootstrap analysis.As is

239

well known, postoperative VTE formation is multifactorial and

240

complicated in its etiology. The importance of D-dimer levels has already

241

been showed above, that a higher D-dimer is associated with a higher risk

242

of developing VTE. And albumin levels as a marker of functional reserve,

243

the lower the level was, the poorer condition and tolerance capacity for 15 / 24

244

surgery of patients would experience (28). It is likewise well known that

245

radical pelvic surgery holds the possibility of causing a high incidence of

246

VTE. In our study, it was not the kind of surgery but the SCS that was

247

associated with the occurrence of VTE. Abu Saadeh et al. (24) have

248

reported the same results as us. The higher scores represented more

249

complex and difficult surgeries, which tends to signify a higher

250

possibility of losing balance in the coagulation system. We define optimal

251

debulk surgery as one with residual disease that is less than 1cm.

252

Takasaki et al. showed that (6) suboptimal surgery was a risk factor for

253

VTE in ovarian carcinoma patients, a similar result as we found. This

254

may because that patient with a worse condition is unable to receive

255

optimal debulking surgery, which increases the risk of VTE.

256

Surprisingly, age was not an independent factor in VTE before

257

surgery, but it did show significance in the analysis of VTE

258

post-operation in our study. Moreover, it is reported in some studies that

259

age is not a relative risk factor for the development of VTE in ovarian

260

cancer (6, 13, 17, 18). But patients with VTE do tend to be older, in both

261

before- and after-surgery VTE groups, as they were in our study. Thus,

262

this result may be due to the fact that patients with advanced age have a

263

lessened ability to tolerate an operation which induces a high risk of VTE.

264

Additionally, we found that there was no correlation between

265

BMI≥27kg/m2 and VTE. Mokri et al. (4) showed that patient age, BMI,

266

FIGO stage, and estimated operative blood loss were not univariately

267

associated with postoperative VTE, a result which agrees with ours.

268

Obesity was reported to predict higher rates of venous thromboembolism

269

(24, 29, 30), but perhaps this is due to the different definition of obesity

270

in Chinese and its foreign standard (BMI≥27kg/m2 and BMI≥30kg/m2),

271

as well as the time points in which body weight was quantified. Still there 16 / 24

272

are no studies that we could locate that confirm that weight loss prevents

273

a secondary occurrence of thromboembolism (29).

274

We did not find any correlation between platelet and VTE in ovarian

275

cancer. Although one-third of women diagnosed with ovarian cancer have

276

thrombocytosis and are therefore at increased risk for VTE (31, 32). This

277

may be related to the point in time in which the platelet count was tested

278

or to the effect of different treatments. Among EOC patients who

279

developed VTE, bilateral DVT occurred in 23.08% (n=6) of the patients,

280

and left-side thrombus was the most common location. This might be due

281

to the fact that the left common iliac vein is crossed over by the entire

282

accompanying artery (33). DVT history and obesity were reported with

283

the incidence of VTE.(19, 29) Past medica history comorbidities have

284

shown that cerebral infarction and hypertension is related with

285

preoperative VTE; while tuberculosis is associated with postoperative

286

VTE.

287

Early VTE events were related with chemotherapy and surgery, while

288

latter VTE events were related with older age, DVT history, advanced

289

stages and resident tumor loads et al(34, 35). Ferroni P et al has shown

290

that the clinical use of antiangiogenetics drugs such as bevacizumab have

291

increased risk of thromboembolism, comparable to that of patients treated

292

with standard chemotherapy alone(36, 37). In our study, none of the

293

patients have used antiangiogenetics drugs before operation and peri

294

operation. Therefore, we

295

antiangiogenetics drugs with VTE during perioperation for the EOC

296

patients.

have

not shown the

association

of

297

As a retrospective study we have limitations and potential bias. First,

298

the number of samples were limited. Second, VTE events may have been

299

missed because we only included VTE case recorded in Electronic 17 / 24

300

Discharge Database and in peri operation periods. Moreover, we did not

301

conduct any information regarding the prognostic, just a descriptive

302

analysis of the clinical character of VTE occurrence.

303

In conclusion, we demonstrated that EOC patients had an incidence

304

of

305

thromboprophylaxis and pretest assessment is necessary. It is also worth

306

noting that D-dimer is a predictor for both preoperative and postoperative

307

patients in identifying VTE and optimal debulking surgery is essential for

308

EOC patients.

309

Acknowledgments

310

This work was supported by the National Key Research and

311

Development Program (2018YFC1003900), National Natural Science

312

Foundation of China (81872110, 81902632), Anhui Provincial Key

313

Research and Development Program (1704a0802151),. Anhui provincial

314

innovative program for organ transplantation (S20183400001). The

315

funders had no role in the study design, data collection and analysis,

316

decision to publish, or preparation of the manuscript.

11.16%

18 / 24

for

VTE,

which

suggests

that

more

effective

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Table 1 Clinical characteristics of ovarian cancer patients before operation Table 2 Clinical characteristics of ovarian cancer patients after operation Table 3 Univariate and multivariate analysis of factors associated with preoperative VTE Table 4 Univariate and multivariate analysis of factors associated with postoperative VTE Supplement Table1 Distribution of ovarian cancer patients with VTE by pathological types Supplement Table2 Distribution of ovarian cancer patients with VTE by FIGO stage Supplement Table3 Effect of cytoreduction surgery in ovarian cancer patients with VTE after surgery Supplement Table4 Characteristics of patients with VTE.

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Figure1.ROC curve of potential predictors of VTE (a-e for VTE before surgery; f-j for VTE after surgery)

Table 1 Clinical characteristics of ovarian cancer patients before operation Preoperative risk factors VTE group Number 10(4.3%) a Age (y) 57.5(IQR19)(40-69) BMI (kg/m2)a 22.86(IQR2.53)(20.03-24.44) <27 9(90%) ≥27 0 Stay in bed 1(10%) Ascites ≥500ml 6(60%) <500ml 4(40%) Past medical history/comorbidities Hypertension(n=50) 4(40%) Diabetes (n=18) 0 Heart disease(n=12) 0 c Personal history of non-ovarian cancer (n=13) 1(10%) Hepatitis(n=10) 0 Nervous system disease(n=6) 0 Cerebral infarction(n=12) 5(50%) Obsolete Pulmonary Tuberculosis(n=4) Rheumatic disease(n=3) Hyperthyroidism/hypothyroidism(n=3) Chronic obstructive pulmonary disease (n=2) Nephrotic syndrome(n=2) Histology

1(10%) 1(10%) 0 0 0

Non VTE group 223(95.7%) 54(IQR17)(15-77) 23.42(IQR4.03)(16.89-37.25) 192(86.1%) 29(13%) 2(0.9%)

P value 0.956 0.29 0.099

0.349 89(39.91%) 134(60.08%) 46(20.63%) 18(8.07%) 12(5.38%) 12(5.38%) 10(4.48%) 6(2.69%) 7(3.14%） 3(1.35%) 2(0.9%) 3(1.35%) 2(0.9%) 2(0.9%)

0.005 / / 1 / / <0.001 0.162 0.124 / / / 0.066

Serous carcinoma Mucinous carcinoma Clear cell carcinoma Endometroid carcinoma Mixed carcinoma FIGO stage Ⅰ Ⅰ Ⅰ Ⅰ Plateletb(10*9/L) Albuminb(g/L) PTb(s) APTTb(s) TTb(s) D-dimerb(µg/ml) Fgb(g/L) CA125b(U/ml) a. Median, interquartile range (IQR), range b. Mean ± standard deviation, range

6(60%) 0 3(30%) 1(10%) 0 9 1(11.11%) 0 6(66.67%) 2(22.22%) 255.5±105.5(118-443) 38.0±3.5(34-44.8) 11.7±1.3(9.2-13.6) 31.61±7.0(22.2-43.3) 17.3±2.1(13.8-21.1) 7.5±7.5(0.51-22.49) 3.6±1.3(2.41-6.18) 3401.8±5884.3(12.62-18848)

183(82.06%) 12(5.38%) 16(7.17%) 6(2.69%) 6(2.69%) 184 40(21.7%) 22(12%) 92(50%) 30(16.3%) 266.9±116.2(65-935) 42.2±5.2(24.9-64.6) 11.1±1.4(8-16.7) 28.6±6.7(16.3-54.3) 17.7±1..7(12.4-25.2) 2.5±2.9(0.1-18.92) 3.6±1.2(1.58-8.15) 1054,1±2268.5(6.48-17810)

0.693

0.701 0.004 0.085 0.154 0.466 0.021 0.901 0.031

c.breast cancer(n=8),cervical cancer(n=1),nasopharynx cancer(n=1),lung cancer(n=1),brain tumor (n=2)Abbreviation ： VTE ： Venous thromboembolism; BMI: Body mass index; PT: Prothrombin time; APTT: Activated partial thromboplastin time; TT: Thrombin time; Fg: Fibrinogen; CA125: Cancer antigen 125; FIGO: Federation International of Gynecology and Obstetrics;

Table 2 Clinical characteristics of ovarian cancer patients after operation Postoperative risk factors VTE group Number 17(7.3%) a Age (y) 65(IQR15) (51-76) BMI (kg/m2)a 24.16(IQR3.33) (20.96-30.8) <27 14(82.35%) ≥27 3(17.65%) Stay in bed 0 a Postoperative hospital stay (days) 18(IQR12) (8-48) a Surgery time (min) 268(IQR165) (122-490) a intraoperative blood loss (ml) 600(IQR1100) (100-6000) Past medical history/comorbidities Hypertension(n=50) 6(35.29%) Diabetes (n=18) 1(5.88%) Heart disease(n=12) 2(11.76%) c Personal history of non-ovarian cancer (n=13) 0 Hepatitis(n=10) 1(5.88%) Nervous system disease(n=6) 0 Cerebral infarction(n=12) 1(5.88%) Obsolete Pulmonary Tuberculosis(n=4) 2（11.76%） Rheumatic disease(n=3) Hyperthyroidism/hypothyroidism(n=3) Chronic obstructive pulmonary disease(n=2) Nephrotic syndrome(n=2) 30-day postoperative complications

1(5.88%) 0 0 0

Non VTE group 216(92.7%) 53(IQR16) (15-77) 23.23(IQR3.92) (16.89-37.25) 187(86.57%) 26(12.04%) 3(1.39%) 12(IQR7) (5-55) 250(IQR140) (50-682) 800(IQR900) (0-10000)

P value

0.006 0.291 0.709

44(20.37%) 17(7.87%) 10(4.63%) 13(6.02%) 9(4.17%) 6(2.78%) 11(5.1%)

0.256 1 0.477 / 1 / 1

2(0.93%)

0.028

2(0.93%) 3(1.34%) 2(0.93%) 2(0.93%)

0.204 / / /

0.001 0.068 0.568

Anastomotic fistula Pulmonary infection Incision poor healing Abdominal/pelvic infections Bowel obstruction Cardiac event Urinary tract infection Incision infection Other fistulad Surgery methods Primary cytoreductive surgery Intermediate cytoreductive surgery Re-cytoreductive surgery FIGO Stage

1(5.88%) 2(11.76%) 2(11.76%) 1(5.88%) 0 0 0 0 0

4(1.85%) 11(5.09%) 8(3.70%) 5(2.31%) 4(1.85%) 1(0.46%) 4(1.85%) 4(1.85%) 6c(2.78%)

13(76.5%) 3(17.6%) 1(5.9%) 14

141(65.3%) 37(17.1%) 38(17.6%) 179

Ⅰ

2(14.29%)

39(21.79%)

Ⅱ

1(7.14%)

21(11.73%)

Ⅲ

7(50%)

91(50.84%)

Ⅳ

4(28.57%)

28(15.64%)

SCS Low Intermediate High Residual disease 0

0.318 0.545 0.338 0.921 / / / / / 0.560

0.695

0.027 3(17.6%) 7(41.2%) 7(41.2%)

97(44.9%) 80(37%) 39(18.1%) 0.006

13(76.5%)

173(80.1%)

<1cm 0 33(15.3%) >2cm 4(23.5%) 10(4.6%) b Plt (10*9/L) Pre-operation 279.8±103.3(103-449) 265.4±116.7(65-935) Post-operation 194.4±76.7(92-347) 199.4±78.1(29-476) b Alb (g/L) Pre-operation 40.7±4.3(33.8-48.4) 42.1±5.2(24.9-64.6) Post-operation 29.2±5.11(16.7-34.6) 31.7±7.2(10-69) b PT (s) Pre-operation 10.9±1.1(9.4-13.6) 11.1±1.4(8-16.7) Post-operation 13.4±1.7(9.1-15.8) 13.3±2.0(8.5-19.9) APTTb(s) Pre-operation 26.7±6.2(20.1-43.6) 28.9±6.8(16.3-54.3) Post-operation 35.4±4.5(25.0-45.1) 36.2±6.3(18.9-60.9) b TT (s) Pre-operation 17.7±1.6(14.7-19.9) 17.7±1.7(12.4-25.2) Post-operation 15.6±1.5(13.5-19.6) 15.8±2.6(3.17-42.8) b D-dimer (µg/ml) Pre-operation 3.3±1.7(0.2-5.79) 2.7±3.5(0.1-22.49) Post-operation 6.2±3.9(1.68-14.69) 4.5±3.4(0.22-20) b Fg (g/L) Pre-operation 3.9±1.1(2.56-7.04) 3.6±1.2(1.58-8.15) Post-operation 3.2±1.5(0-6.65) 3.4±1.1(1.05-7.2) a. Median, interquartile range (IQR), range b. Mean ± standard deviation, range c. Breast cancer(n=8), cervical cancer(n=1), nasopharynx cancer(n=1), lung cancer(n=1), brain tumor (n=2)

0.496 0.801 0.179 0.157 0.589 0.808 0.096 0.569 0.981 0.934 0.011 0.046 0.145 0.868

d. duodenal fistula(n=1), rectovaginal fistula(n=2), ureteral fistula(n=1), 2 case of pancreatic fistula and one of them also had gastric fistula result from pancreatic fistula. Abbreviation：VTE：Venous thromboembolism; BMI: Body mass index; SCS: Surgical complexity scores; Plt: Platelet; Alb: Albumin; PT: Prothrombin time; APTT: Activated partial thromboplastin time; TT: Thrombin time; Fg: Fibrinogen; d. Duodenal fistula(n=1), rectovaginal fistula(n=2), ureteral fistula(n=1), 2 case of pancreatic fistula and one of them also had gastric fistula result from pancreatic fistula. Abbreviation：VTE：Venous thromboembolism; BMI: Body mass index; SCS: Surgical complexity scores; Plt: Platelet; Alb: Albumin; PT: Prothrombin time; APTT: Activated partial thromboplastin time; TT: Thrombin time; Fg: Fibrinogen;

Table 3 Univariate and multivariate analysis of factors associated with preoperative VTE Univariate analysis OR (95% CI) P value OR (95% CI) Age (>59.5 years old) Plt (<244.5*109/L) Alb (<39.85g/L) D-dimer (>4.215µg/ml) CA125(>1474U/ml) FIGO stage (Ⅲ+Ⅲ vs I+Ⅲ) OCCC NACT vs Non-NACT Comorbid vs non-comorbid Multiple comorbid vs Non- Multiple comorbid Hypertension vs Non- Hypertension Cerebral infarction vs Non- Cerebral infarction

1.429(0.750-2.725)

0.527

1.459(0.951-2.240) 2.695(1.860-3.906) 3.263(1.833-5.809) 3.190(1.793-5.677)

0.298

1.341(1.041-1.726) 4.181(1.452-12.044) 0.572(0.087-1.353) 1.385 (0.716-2.681) 1.715(0.472-6.239) 2.77(1.644-4.667) 15.929(6.118-41.473)

Multivariate analysis P value P value (5000 bootstrap samples)

1.157(0.966-1.381) 1.182(1.006-1.387) 1(1-1)

0.113 0.041 0.051

0.039 0.032

0.047 0.853 0.402 0.767

6.872(0.588-80.28)

0.124

0.011

0.005 <0.001

1.298(0.218-7.721) 43.292(5.94-315.536)

0.774 <0.001

0.749 <0.001

0.003 0.005 0.006 0.295

<0.001

Abbreviation：VTE：Venous thromboembolism; OR: Odds ratio; 95%CI: 95% Confidence intervals; Plt: Platelet; Alb: Albumin; CA125: Cancer antigen 125; FIGO: Federation International of Gynecology and Obstetrics; OCCC: Ovarian clear cell carcinoma; NACT: New adjuvant chemotherapy treatment

Table 4 Univariate and multivariate analysis of factors associated with postoperative VTE Univariate analysis OR (95% CI) P value OR (95% CI) Age (>50.5 years old)

1.612(1.452-1.789)

Multivariate analysis P value P value (5000 bootstrap samples) 1.071(1.011-1.1350 0.019 0.002

Plt (<198*10 /L)

1.331(0.913-1.940)

0.002 0.201

Alb(<34.65g/L) D-dimer (>4.71µg/ml)

1.394(1.282-1.515) 1.841(1.183-2.867)

0.024 0.024

1.006(0.928-1.089) 1.146(0.997-1.318)

0.890 0.055

0.855 0.036

Postoperative hospital stay (>16.5 days)

2.386(1.504-3.785)

1.01(0.954-1.069)

0.745

0.750

FIGO stage (Ⅲ Ⅲ+Ⅳ Ⅳ vs I+Ⅱ Ⅱ)

1.849(0.497-6.878)

0.006 0.527

SCS (3 vs 1+2)

2.281(1.208-4.304)

0.047

3.496(0.935-13.072)

0.063

0.109

Optimal debulking surgery (yes vs no) 30-day postoperative complications vs Non-30-day postoperative complications Comorbid vs Non-Comorbid Multiple comorbid vs Non- Multiple comorbid Tuberculosis vs Non-Tuberculosis

0.802(0.615-1.045) 1.538(0.474-4.989)

0.009 0.698

0.123(0.027-0.568)

0.007

0.002

1.117(0.659-1.894) 2.118(0.83-5.401)

0.692 0.259

12.706(1.907-84.676)

0.028

11.667(0.911-149.42 5)

0.059

0.015

9

Abbreviation：VTE：Venous thromboembolism; OR: Odds ratio; 95%CI: 95% confidence intervals; Plt: Platelet; Alb: Albumin; SCS: Surgical complexity scores

Declarations of interest: The authors declare no potential conflicts of interest.