Literature DB >> 22792477

Prognostic significance of vascular endothelial growth factor serum determination in women with ovarian cancer.

Elisabetta Bandiera1, Roberta Franceschini, Claudia Specchia, Eliana Bignotti, Chiara Trevisiol, Massimo Gion, Sergio Pecorelli, Alessandro Davide Santin, Antonella Ravaggi.   

Abstract

Introduction. We performed a review of the literature to elucidate the potential prognostic significance of serum vascular endothelial growth factor (sVEGF) levels in ovarian cancer. Methods. Eligible studies in English and Italian were identified in MEDLINE/PubMed from VEGF discovery to October 2011. All studies evaluating: (i) sVEGF levels before any surgical and chemotherapeutic treatment; (ii) the association between sVEGF levels and the established prognostic variables; (iii) the value of sVEGF levels in predicting patients' outcomes, were selected for this review. Results. The search resulted in 758 titles. Nine studies met the inclusion criteria. A statistically significant association between the level of sVEGF and FIGO stage, tumour grade, residual tumour size, lymph node involvement, and presence of ascites was found in at least one study. sVEGF, in comparison with the established prognostic factors, appears to be the best prognostic marker for overall survival, since it stands out as an independent prognostic factor in most of the studies considered. Moreover, sVEGF levels were shown to be independent prognostic factors by 2 out of the 3 studies that considered DFS as an end point. Conclusion. High levels of sVEGF identify a subgroup of patients with higher risk of death and/or recurrence. These patients should be eligible for individually tailored therapeutic interventions.

Entities:  

Year:  2012        PMID: 22792477      PMCID: PMC3390037          DOI: 10.5402/2012/245756

Source DB:  PubMed          Journal:  ISRN Obstet Gynecol        ISSN: 2090-4436


1. Introduction

Ovarian cancer is the most frequent cause of death from gynaecological cancer and the fourth most frequent cause of cancer-related death in women in Europe and the United States [1]. It has the highest fatality-to-case ratio of all gynaecological malignancies, mainly due to the fact that it is characterized by early widespread metastasis and high-grade malignancy at diagnosis. The five-year survival proportion is about 80–90% for patients with stage I disease and only 15–20% for patients with stage III or IV disease. Although survival has improved with the use of maximal cytoreduction surgery along with platinum- and taxane-based chemotherapy, nearly 80% of ovarian cancers relapse and patients inevitably succumb to the development of chemotherapy-resistant disease [2]. Clinicopathological features known to be prognostic variables for ovarian cancer are surgical stage (FIGO stage), histological grade, lymph node involvement, residual tumour size after cytoreductive surgery, histological subtype, ascites, and age. According to the three-year analysis of the FIGO Annual Report on the Results of Treatment in Gynaecological Cancer, stage, grade, and residual tumour size have the greatest prognostic value [3]. However, these factors provide an insufficient picture of the biology of ovarian cancer and they are frequently interrelated. The identification of new serological biological markers that predict the outcome of the disease would be extremely useful for developing individually tailored and possibly more effective treatments. Serum analysis is a noninvasive technique feasible in cases where no tissue is available and it can also be performed during followup. It is well established that angiogenesis, the formation of new blood vessels, is necessary for the growth and metastatic spread of solid tumours [4-7]. A high degree of tumour angiogenesis has been shown to correlate with poor survival in women with ovarian cancer [7-10]. Vascular endothelial growth factor (VEGF) plays an essential role in angiogenesis in many tumour types [11-15]. It is a heparin-binding dimeric glycoprotein involved in angiogenic, mitotic, and microvascular permeability-inducing activities, leading to extravasation of plasma proteins and proangiogenic stromal changes [16]. Several studies have found VEGF levels to be significantly higher in the tissues and biological fluids of women with ovarian cancer compared with healthy controls [17-20], whereas its association with tumour progression and/or patient survival is still controversial. We performed a review of the literature to elucidate the prognostic role of serum VEGF (sVEGF) levels in ovarian cancer, both alone and in comparison with established clinicopathological factors.

2. Methods

Eligible studies in English and Italian were identified in MEDLINE (PubMed version) from VEGF discovery to October 2011 using the terms VEGF, “vascular endothelial growth factor” and synonyms, “ovarian cancer,” “ovary cancer,” and synonyms. We searched studies that used these terms in title and abstract and that was indexed by bibliographic database with the Mesh term “ovarian neoplasms.” We searched the database using these terms separately and also in combination. Relevant papers were independently selected by two of the reviewers (E. Bandiera and R. Franceschini) based on the following inclusion criteria: studies that evaluated (i) sVEGF levels before any surgical and chemotherapeutic treatment; (ii) the association of sVEGF levels with the established clinicopathological prognostic factors (FIGO stage, tumour grade, residual tumour size, lymph node involvement, histological type, ascites, age); (iii) the value of sVEGF levels in predicting patients' outcomes (overall survival (OS), disease-free survival (DFS), progression free survival (PFS)). Any disagreement in the inclusion of one study between two reviewers was solved by discussion.

2.1. Data Extraction

Two of the reviewers (E. Bandiera and R. Franceschini) independently reviewed each study and abstracted data on first author, country of study, study characteristics (study design, followup duration, therapy), clinical and pathological variables, and study outcomes.

3. Results

3.1. Included Studies

Our search strategy identified 758 journal abstracts. From these, we retrieved for further evaluation 15 full-text articles focused on the relationship between circulating preoperative VEGF and prognosis in ovarian cancer. Of these 15 articles, nine [21-29] studies met the inclusion criteria and were used for this review. Hefler et al. [28] gathered together some cases from trials by Tempfer et al. [21], Gadducci et al. [22], Chen et al. [23], and Cooper et al. [25]. Because Hefler et al. [28] added a series of new patients, we reported these five [21–23, 25, 28] studies independently.

3.2. Excluded Studies

Six studies were excluded. The paper by Manenti et al. [30] was excluded because these authors analysed plasma VEGF levels. Since VEGF is secreted also by platelets, Manenti et al.'s study was unsuitable for comparison with studies focusing on sVEGF. Boss et al. [31], Bamias et al. [32], Yamamoto et al. [33], and Rudlowski et al. [34] were excluded because they did not directly evaluate the prognosis of patients with abnormal sVEGF levels and/or the association between sVEGF levels and clinicopathological characteristics. Finally, Dirix et al. [35] evaluated patients with different cancer types and did not report independent results for ovarian cancer.

3.3. Characteristics of the Selected Studies

The nine selected studies were published between 1996 and 2010 and included 529 patients from seven countries. All but one [28] study were retrospective. Six of these nine studies reported details on the duration of followup (median: 42 months [21], 34 months [23], 29 months [29] or mean: 39 months [28], or length: 60 months [25], 24 months [22]). All studies analysed the association between sVEGF levels and the established prognostic variables and evaluated the association between sVEGF levels and OS. Three studies [21, 23, 27] analysed the association between sVEGF and DFS whereas only one [29] analysed the association between sVEGF and PFS.

3.4. Characteristics of Study Populations

All studies enrolled women with newly diagnosed and histopathologically confirmed ovarian cancer except the one by Cooper et al. [25], which included also a small group of women with peritoneal and fallopian tube malignancies (Table 1). The mean (or median) ages of the studied women ranged from 52.5 to 64 years. Most cancers (>95%) were epithelial and the predominant histological type was serous carcinoma. Most patients were diagnosed with poorly differentiated ovarian cancer, advanced FIGO stage, and ascites. With the exception of Gadducci et al. [22], who followed only 27 patients with advanced disease receiving chemotherapy, all other studies monitored all patients enrolled.
Table 1

Clinical and demographic characteristics of patients.

                                         Author, year
Tempfer et al., 1998 [21]Gadducci et al., 1999 [22]Chen et al., 1999 [23]Oehler and Caffier, 2000 [24]Cooper et al., 2002 [25]Li et al., 2004 [26]Harloziňska et al., 2004 [27]Hefler et al., 2006 [28]Mahner et al., 2010 [29]
Origin and Dates 1990–1995Austria1990–1997Italy1992–1998TaiwanGermany1995–2000Iowa1999–2001China1997–2002Poland1990–2003Austria, Iowa, Italy, Taiwan1996–2004Germany

Number of cases 60535641101$ 508631437

Age, mean or median* (range), years 55.6*(36–71)59* (23–81)52.5* (21–88)62 (32–83)64 (20–78)NANA59.958.61* (26–78)

FlGO stageI719145 20 1714561
II121629271
III27223230 81 333717729
IV14114426466

GradeG1211721NA 39 1319600
G2 3912 35NA41889
G324NA 61302615027

Epithelial ovarian cancerSerous28333032 81154916631
Mucinous2364294410
Undifferentiated36801913154
Endometrioid37107020391
Clear cell204000091
Others1100000440

Nonepithelial ovarian cancer 000007000

Ascites>500 mL/presence**NA21**NANA67**2264**NA21
<500 mL/absence**NA12**NANA34**2822**NA15

Residual disease<2 or 1*** cm389401168***4432164***22
>2 or 1*** cm2224163033***65464***14

Lymph node involvementyes23NANANANA12NA3810
no37NANANANA38NA6311

$: Cooper study contains a small group of peritoneal and fallopian tube malignant cancers; NA: not available data; *: Median values; **: Numbers of patients with presence/absence of ascites; ***: Numbers of patients with residual disease < or >1 cm.

Surgery for optimal tumour debulking included hysterectomy, bilateral salpingo-oophorectomy, omentectomy [21, 23, 28, 29], pelvic and para-aortic lymphadenectomy [21, 23, 28, 29], and appendectomy [23, 28, 29]. Five studies [22, 24–27] did not describe the surgical approach, but according to the reported data (residual tumour size [22, 24–27], omental metastasis [26], lymph node involvement [26]), we may presume that maximal cytoreductive surgery was performed. Surgery was followed by chemotherapy consisting of platinum analogues alone [21–24, 28] or in combination with taxane [25, 29]. Early stages of disease were treated according to the standards established by the respective institutions: patients with stage IA-IB [21], I-II [22], IA [25], and IA-IB excluding clear cell histology [28] did not receive any chemotherapy or were treated like patients with advanced disease [23, 24, 29]. Although postoperative chemotherapy is the accepted standard treatment, two studies [26, 27] omitted any information about it.

3.5. sVEGF Assay

The sVEGF assay method was similar across studies. Venous blood was taken preoperatively from all patients. All sera were separated and stored at ≤20°C. Seven studies [21–25, 27, 28] used the same Quantikine sandwich ELISA kit (R&D Systems Minneapolis, USA). Li et al.'s study used a home-made indirect ELISA kit, whereas Mahner et al.'s study used VEGF-165 ELISA KIT (Siemens Healthcare Diagnostic, Tarrytown, USA). Data on the precision of sVEGF assays were reported in three studies [21, 24, 28], and in all studies, the intra/inter-assay coefficient of variation was <10%. Median values of sVEGF reported by authors were: 466 pg/mL [21], 229 pg/mL [22], 458 pg/mL [23], 440 pg/mL [24], 379 pg/mL [25], 387 pg/mL [27], 407 pg/mL [28], and 171 pg/mL [29]. Li et al. [26] showed a mean value of 765 pg/mL.

3.6. Relationship between sVEGF Levels and the Other Prognostic Factors

The association between sVEGF concentrations and FIGO stage, tumour grade, residual tumour size, lymph node involvement, histological type, ascites, and age was analysed by 89%, 89%, 89%, 44%, 67%, 56%, and 78% of studies respectively (Table 2).
Table 2

Association between sVEGF and clinicopathological characteristics of patients.

VariableAuthor, yearNo. casesReported statistics for VEGFVariable typeStatistical significance of association
StageTempfer et al., 1998 [21]60mdI/II versus III/IVNO
Gadducci et al., 1999 [22]53mdI versus II and III versus IVNO
Chen et al., 1999 [23]56mdI/II versus III/IVNO
Oehler and Caffier, 2000 [24]41mcategoricalNO
Cooper et al., 2002 [25]101mdI/II versus III/IVNO
Li et al., 2004 [26]50mI/II versus III/IVYES
Harloziňska et al., 2004 [27]86NAI/II versus III/IVNO
Hefler et al., 2006 [28]314mcategoricalNO

GradeTempfer et al., 1998 [21]60mdG1 versus G2/G3YES
Gadducci et al., 1999 [22]53mdG1-G2 versus G3NO
Chen et al., 1999 [23]56mdG1 versus G2/G3YES
Cooper et al., 2002 [25]101mdG1-G2 versus G3NO
Li et al., 2004 [26]50mG1-G2 versus G3YES
Harloziňska et al., 2004 [27]86NAG1 versus G2/G3NO
Hefler et al., 2006 [28]314mcategoricalNO
Mahner et al., 2010 [29]37mdG2 versus G3NO

Residual tumour size (cm)Tempfer et al., 1998 [21]60md≥2 versus <2NO
Gadducci et al., 1999 [22]53md≥2 versus <2NO
Chen et al., 1999 [23]56md≥2 versus <2NO
Oehler and Caffier, 2000 [24]41m≥2 versus <2NO
Cooper et al., 2002 [25]101md≥1 versus <1NO
Li et al., 2004 [26]50m≥2 versus <2YES
Hefler et al., 2006 [28]314m≥1 versus <1YES
Mahner et al., 2010 [29]37md≥0 versus <0NO

Lymph node involvementTempfer et al., 1998 [21]60mdyes versus noNO
Li et al., 2004 [26]50myes versus noYES
Hefler et al., 2006 [28]314myes versus noNO
Mahner et al., 2010 [29]37mdyes versus noNO

Histological typeTempfer et al., 1998 [21]60mdserous or mucinous versus othersNO
Gadducci et al., 1999 [22]53mdserous versus othersNO
Chen et al., 1999 [23]56mdserous or mucinous versus othersNO
Oehler and Caffier, 2000 [24]41mcategoricalNO
Li et al., 2004 [26]50mcategoricalNO
Harloziňska et al., 2004 [27]86NAcategoricalNO

Ascites (mL)Gadducci et al., 1999 [22]53mdpresence versus absenceYES
Cooper et al., 2002 [25]101mdpresence versus absenceYES
Li et al., 2004 [26]50m≥500 versus <500YES
Harloziňska et al., 2004 [27]86NApresence versus absenceNO
Mahner et al., 2010 [29]37md≥500 versus <500NO

Age (years)Tempfer et al., 1998 [21]60md≥50 versus <50NO
Gadducci et al., 1999 [22]53NANANO
Chen et al., 1999 [23]56md≥50 versus <50NO
Oehler and Caffier, 2000 [24]41m≥60 versus <60NO
Cooper et al., 2002 [25]101md≥64 versus <64NO
Hefler et al., 2006 [28]314mcontinuous variableNO
Mahner et al., 2010 [29]37md≥61 versus <61NO

Md: median, m: media, NA: not available data.

When the median (or mean) of sVEGF values was evaluated in relation to clinicopathological features, a statistically significant association between the level of sVEGF and FIGO stage, tumour grade, residual tumour size, lymph node involvement, and presence of ascites was found in at least one study. By contrast, no statistically significant association was found between sVEGF levels and histological type or age. Tempfer et al. [21], Chen et al. [23], and Li et al. [26] demonstrated that elevated sVEGF levels were associated with a high malignant potential of tumours (G1 versus G2-G3 [21, 23], G1-G2 versus G3 [26]). Gadducci et al. [22], Cooper et al. [25], and Li et al. [26] reported a positive association between sVEGF concentrations and ascites volume (Gadducci et al. [22] selected patients with stages III-IV). Li et al. [26] and Hefler et al. [28] found that patients with suboptimally debulked cancer had higher sVEGF values than patient in whom tumour debulking was optimal. Finally, only the study by Li et al. [26] showed that sVEGF values were higher in patients with advanced FIGO stages and lymph node involvement.

3.7. sVEGF Evaluation

In evaluating its association with outcome variables, the levels of sVEGF were dichotomised using different cut-offs: 75th percentile [21, 23] or median [24, 29] in ovarian cancer patients, mean [26] in healthy subjects, and 95th percentile [27] in patients with benign disease. In one study, the authors used the value maximizing the hazard ratio [25]. Cut-offs ranged from 100 to 826 pg/mL. Finally, only Hefler and coworkers [28] considered sVEGF as a continuous variable.

3.8. Statistical Analyses

In the univariate analyses, seven [21, 23, 24, 26–29] studies used the Kaplan-Meier product-limit method to estimate how sVEGF and other clinicopathological variables might predict OS and DFS. Gadducci et al. [22] and Cooper et al. [25] did not explicitly report the method of univariate analysis. In the multivariate analyses, all studies claim to have used the Cox proportional hazards regression model to assess the independent role of different, simultaneously evaluated prognostic factors in determining outcomes. Estimates are reported in terms of relative risk (RR) and hazard ratio (HR). The results of univariate and multivariate analyses were considered statistically significant when the P  values were <0.05.

3.9. Univariate and Multivariate OS Analysis

Univariate and multivariate analyses for survival were reported in Table 3. All studies analysed the association between sVEGF levels and OS. With the exception of Gadducci et al. [22] and Mahner et al. [29], all authors found that elevated sVEGF was associated with shorter OS. Moreover, five [21, 23, 25, 27, 28] of these seven studies found sVEGF to be an independent prognostic factor.
Table 3

Univariate and multivariate analyses for overall survival.

VariableAuthor, yearNo. casesCut-offUnivariate analysis RR or HR, P-valueMultivariate analysis RR or HR, P-value
VEGF (pg/mL)Tempfer et al., 1998 [21]60≥826 versus <826RR = 2.7, P = 0.007RR = 2.7, P = 0.008
Gadducci et al., 1999 [22]53NA P = NSNA
Chen et al., 1999 [23]56NA P < 0.001/P = 0.006*RR = 4.47, P ≤ 0.001; RR = 5.37*, P < 0.001*
Oehler and Caffier, 2000 [24]41≥440 versus <440HR = 3.56, P = 0.026 P = NS
Cooper et al., 2002 [25]101≥380 versus <380HR = 2.13, P = 0.009HR = 2.08, P = 0.02
Li et al., 2004 [26]50≥100 versus <100 P = 0.0085; P = 0.4§; P = 0.02 P = 0.0750
Harloziňska et al., 2004 [27]86≥750 versus <750 P = 0.0169RR = 2.35; P = 0.02
Hefler et al., 2006 [28]314continuous variable P < 0.001; P < 0.001°HR = 1.8, P = 0.03; HR = 1.1°, P = 0.001°
Mahner et al., 2010 [29]37171 P = 0.302NA

StageTempfer et al., 1998 [21]60I/II versus III/IVRR = 3.2, P = 0.007RR = 3.2, P = 0.001
Chen et al., 1999 [23]56I/II versus III/IVNARR = 2.08, P = 0.11; RR = 3.84*, P = 0.01*
Oehler and Caffier, 2000 [24]41I/II versus III/IVHR = 2.24, P = 0.043 P = NS
Cooper et al., 2002 [25]101I/II versus III/IVHR = 10.15, P < 0.001HR = 9.24, P < 0.001
Li et al., 2004 [26]50NANA P = NS
Harloziňska et al., 2004 [27]86I/II versus III/IV P = 0.0006RR = 4.08, P = 0.008
Hefler et al., 2006 [28]314NA P < 0.001HR = 1.7, P < 0.001

GradeTempfer et al., 1998 [21]60G1 versus G2/3RR = 1.4, P = 0.005RR = 1.4, P = 0.01
Chen et al., 1999 [23]56G1 versus G2/3NARR = 2.38, P = 0.034; RR = 2.44*, P = 0.045*
Cooper et al., 2002 [25]101G1/2 versus G3HR = 1.36, P = 0.29HR = 0.86; P = 0.63
Li et al., 2004 [26]50NANA P = NS
Harloziňska et al., 2004 [27]86G1 versus G2/3 P = 0.00079 P = NS
Hefler et al., 2006 [28]314NA P < 0.001; P = 0.2°HR = 1.2, P = 0.3; HR = 3.4°, P = 0.02°

Residual tumor size (cm)Chen et al., 1999 [23]56≥2 versus <2NARR = 1.34, P = 0.46
Oehler and Caffier, 2000 [24]410 versus 1 + 2HR = 11.68, P = 0.018HR = 11.68, P = 0.018
Cooper et al., 2002 [25]1010 versus 1 + 2HR = 2.2, P = 0.007HR = 1.29, P = 0.42
Li et al., 2004 [26]50NANA P = 0.019
Harloziňska et al., 2004 [27]86≥2 versus <2 P = 0.00637 P = NS
Hefler et al., 2006 [28]314≥1 versus <1 P < 0.001HR = 1.8, P = 0.006

Lymph node involvementTempfer et al., 1998 [21]60Yes versus NoRR = 2.8, P = 0.0007RR = 2.8, P = 0.006
Li et al., 2004 [26]50NANA P = NS

Histological typeChen et al., 1999 [23]56serous/mucinous versus othersNARR = 0.99, P = 0.92; RR = 1.14*, P = 0.21*
Li et al., 2004 [26]50NANA P = NS
Harloziňska et al., 2004 [27]86serous versus others P = NS P = NS
Hefler et al., 2006 [28]314serous versus others P = 0.3; P = 0.6°HR = 1.1, P = 0.6; HR = 1°, P = 0.9°

AscitesCooper et al., 2002 [25]101presence versus absenceHR = 2.5, P = 0.004HR = 1.28, P = 0.54

Age (years)Oehler and Caffier 2000 [24]41≥60 versus <60 P = NS P = NS
Cooper et al., 2002 [25]101NAHR = 1.34, P = 0.30HR = 1.16, P = 0.63
Harloziňska et al., 2004 [27]86≥62 versus <62 P = 0.0478RR = 2.20, P = 0.0272
Hefler et al., 2006 [28]314continuous variable P = 0.01, P = 0.8°HR = 1, P = 0.9; HR = 1°, P = 0.6°

*:Subset of 40 patients with residual tumour size ≤2 cm; °:Subset of 56 patients with stage I; §:Subset of patients with stages I-II; :Subset of patients with stages III-IV; NA: not available data; NS: non-significant statistical analysis.

As expected, clinicopathological features known to be prognostic variables for EOC such as FIGO stage, tumour grade, residual tumour size after cytoreductive surgery, lymph node involvement, and age have been shown as independent prognostic factors in at least one study. Notably, sVEGF, in comparison with others prognostic variables, was reported as independent prognostic factors by the majority of studies. Chen et al. [23], Li et al. [26], and Hefler et al. [28] chose subgroups of patients for further analyses. Chen et al. [23] selected a subset of 40 patients with residual tumour size less than 2 cm. Univariate analysis, performed only for sVEGF, showed that elevated sVEGF was associated with shorter OS. Multivariate analysis identified sVEGF, FIGO stage, and grade as independent prognostic factors. Li et al. [26] demonstrated that there was no significant difference in cumulative survival probability between stage I/II patients with high values of sVEGF and stage I/II patients with low levels of sVEGF. By contrast, the cumulative survival probability of stage III/IV patients with high values of sVEGF was lower than that of stage III/IV patients with low levels of sVEGF. A planned subgroup analysis was performed for 56 patients with FIGO stage I in the study by Hefler et al. [28]. In univariate analysis, only sVEGF was associated with OS. In multivariate analysis, sVEGF and tumour grade were independent prognostic factors for OS.

3.10. Univariate and Multivariate DFS and PFS Analysis

Only three [21, 23, 27] of the nine included studies considered DFS as an end point. In univariate analysis, a significant association between DFS and sVEGF level was found by 2 [21, 23] out of 3 [21, 23, 27] studies. In multivariate analysis, sVEGF levels were shown to be independent prognostic factors by 2 [21, 23] out of 3 [21, 23, 27] studies. The associations between DFS and other prognostic factors were shown in Table 4.
Table 4

Univariate and multivariate analyses for disease free survival.

VariableAuthor, yearNo. casesCut-offUnivariate analisys RR, P-valueMultivariate analisys RR, P-value
Tempfer et al., 1998 [21]60≥826 versus <826RR = 1.8, P = 0.003RR = 1.8, P = 0.02
VEGF (pg/mL)Chen et al., 1999 [23]56NA P = 0.001, P = 0.001*RR = 3.34, P = 0.002; RR = 5.62*, P < 0.001*
Harloziňska et al., 2004 [27]314≥750 versus <750 P = NS P = NS

StageTempfer et al., 1998 [21]60I/II versus III/IVRR = 1.3, P = 0.01RR = 1.3, P = 0.02
Chen et al., 1999 [23]56I/II versus III/IVNARR = 2.09, P = 0.10; RR = 3.28*, P = 0.027*
Harloziňska et al., 2004 [27]314I/II versus III/IV P = 0.000RR = 4.66, P = 0.00018

GradeTempfer et al., 1998 [21]60G1 versus G2/G3RR = 1.9, P = 0.03RR = 1.9, P = 0.04
Chen et al., 1999 [23]56G1 versus G2/G3NARR = 2.24, P = 0.042; RR = 2.55*, P = 0.037*
Harloziňska et al., 2004 [27]314G1 versus G2/G3 P = 0.0001 P = NS

Residual tumour sizeChen et al., 1999 [23]56≥2 versus <2NARR = 0.96, P = 0.93
Harloziňska et al., 2004 [27]314≥2 versus <2 P = 0.0001 P = NS

Lymph node involvementTempfer et al., 1998 [21]60Yes versus NoRR = 2.8, P = 0.009RR = 2.8, P = 0.009

Histological typeChen et al., 1999 [23]56serous/mucinous versus othersNARR = 0.97, P = 0.73; RR = 1.04*, P = 0.7*
Harloziňska et al., 2004 [27]314serous versus others P = NS P = NS

Age (years)Harloziňska et al., 2004 [27]314≥62 versus <62 P = NS P = NS

*:Subset of 40 patients with residual tumour size ≤2 cm; NA: not available data; NS: non-significant statistical analysis.

Chen et al. [23] further evaluated DFS for 40 ovarian carcinoma patients with residual tumour size less than 2 cm, and they found that elevated sVEGF levels were significantly associated with lower DFS in univariate analysis and sVEGF levels, FIGO stage and grade were independent prognostic factors for DFS in multivariate analysis. Finally, only Mahner et al. [29] considered PFS as an end point and he did not find a significant association between PFS and sVEGF level.

4. Discussion

The management of patients with ovarian cancer is based on established prognostic factors such as tumour stage, histological grade, and residual tumour size after cytoreductive surgery. Recently, the concept of standard chemotherapeutic treatment with platinum/taxane combination, the necessity of adjuvant chemotherapy in early stages of disease, the use of neoadjuvant chemotherapy for patients expected not to be optimally debulked at primary cytoreductive surgery and the use of consolidation chemotherapy for patients at high risk of recurrence have all been questioned. The need for additional prognostic data to calibrate therapeutic tools on an individual basis in women with ovarian cancer seems obvious. In contrast to other malignancies, no serological prognostic parameter other than CA125 has been shown to have clinical value in ovarian cancer, even though CA125 serum levels at diagnosis are not associated with OS and DFS [36, 37]. From VEGF discovery till 2011, nine studies that directly correlated preoperative sVEGF with ovarian cancer outcome were published. Structured data extraction was performed on the articles to compare study populations, sVEGF assays, associations between sVEGF and clinicopathological characteristics, patient management, and outcome evaluation. Unfortunately, because of the heterogeneity of the studies and missing or incomplete information, it is not possible to pool data and to perform a meta-analysis in order to obtain univocal indications about sVEGF's prognostic value. The data reported in Tables 1, 3, and 4 show evident differences among studies. All studies included only epithelial ovarian carcinoma patients except those by Cooper et al. [25] and Li et al. [26], where other ovarian, peritoneal, and tubal malignancies were included. Patients underwent different chemotherapy regimens based on platinum analogues alone [21–24, 28] or in combination with taxane [25, 29]. Patients with early-stage disease were treated differently or were not treated, depending on the standards of the respective institutions. None of the studies exhaustively described followup (time, lost patients, events). Although seven [21–25, 27, 28] out of nine studies used the same sVEGF assay, one [22] of these measured significantly lower sVEGF values in ovarian cancer patients. Finally, widely differing sVEGF cut-off values (ranging from 100 to 826 pg/mL) were chosen for univariate and multivariate analysis, depending on the statistical methods chosen for the analysis. In order to find out how sVEGF influences ovarian cancer biology, all studies analysed the association between sVEGF and the clinicopathological characteristics of the patients. The results seem to confirm that VEGF plays an important biological role in the pathogenesis of ascites [38, 39]. VEGF increases vessel permeability for circulating macromolecules, thus facilitating extravasation of a plasma-rich exudate into the peritoneal cavity. Moreover, seven out of eight studies, concerning the relationship between sVEGF and FIGO stage, showed that VEGF concentrations measured in sera were not associated with FIGO stage. This may indicate that the effects promoted by VEGF are a continuous process and are independent of the clinical progression of the disease. Interestingly, in our review of literature, sVEGF appears to be the best prognostic marker for OS in comparison with the established prognostic variables, since it stands out as an independent prognostic factor in most of the studies considered. The scarcity of the data on the relationship between sVEGF levels and DFS makes it difficult to draw any firm conclusions in this regard. However, it is worth noting that sVEGF appears to be an independent prognostic factor for DFS in 2 out of 3 studies, as well as tumor stage and grade. Chen et al. [23] and Hefler et al. [28] analyzed the prognostic value of sVEGF in a selected “low-risk” group of patients. Chen et al. [23] showed that sVEGF, FIGO stage and tumour grade were independent prognostic factors for OS and DFS in 40 patients with size tumour less than 2 cm. Hefler et al. [28] in a cohort of 56 patients with FIGO stage I found that sVEGF and tumour grade were independent prognostic factor for OS. The value of these results is conspicuous in those situations where the usefulness of adjuvant chemotherapy or the advisability of more chemotherapy cycles for certain categories of patients is under discussion. In conclusion, almost all of the studies analysed in the present review, including the largest one by Hefler et al. [28], showed that elevated levels of sVEGF were significantly associated with shorter OS. It is worth noting that multiple phase III studies, ICON 7, GOG218, and OCEANS, have recently showed that the use of bevacizumab, a humanized antibody against VEGF, provides a clinically meaningful benefit in EOC patients outcome [40, 41]. Thus, from analysis of the literature reported in this review, as well as from results reported by recent clinical trials, sVEGF appears to be a promising prognostic factor in ovarian cancer that could identify a subgroup of patients with poor survival and higher risk of death that could benefit of bevacizumab therapy to improve their outcome.
  39 in total

1.  CA125 expression pattern, prognosis and correlation with serum CA125 in ovarian tumor patients. From The Danish "MALOVA" Ovarian Cancer Study.

Authors:  Estrid V S Høgdall; Lise Christensen; Susanne K Kjaer; Jan Blaakaer; Anette Kjaerbye-Thygesen; Simon Gayther; Ian J Jacobs; Claus K Høgdall
Journal:  Gynecol Oncol       Date:  2006-11-17       Impact factor: 5.482

2.  Preoperative serum vascular endothelial growth factor as a prognostic parameter in ovarian cancer.

Authors:  Lukas A Hefler; Robert Zeillinger; Christoph Grimm; Anil K Sood; Wen Fang Cheng; Angiolo Gadducci; Clemens B Tempfer; Alexander Reinthaller
Journal:  Gynecol Oncol       Date:  2006-06-05       Impact factor: 5.482

3.  FIGO (International Federation of Gynecology and Obstetrics) 26th Annual Report on the Results of Treatment in Gynecological Cancer.

Authors: 
Journal:  Int J Gynaecol Obstet       Date:  2006-11       Impact factor: 3.561

Review 4.  Vascular endothelial growth factor and vascular targeting of solid tumors.

Authors:  R A Brekken; P E Thorpe
Journal:  Anticancer Res       Date:  2001 Nov-Dec       Impact factor: 2.480

5.  Preoperative serum vascular endothelial growth factor levels: significance in ovarian cancer.

Authors:  Brian C Cooper; Justine M Ritchie; Carrie L W Broghammer; Jeremy Coffin; Joel I Sorosky; Richard E Buller; Mary J C Hendrix; Anil K Sood
Journal:  Clin Cancer Res       Date:  2002-10       Impact factor: 12.531

6.  Correlation of serum VEGF levels with clinical stage, therapy efficacy, tumor metastasis and patient survival in ovarian cancer.

Authors:  Li Li; Limei Wang; Wei Zhang; Bujian Tang; Jieqing Zhang; Honglin Song; Desheng Yao; Yong Tang; Xinqiu Chen; Zhihua Yang; Gangduo Wang; Xiping Li; Jinshun Zhao; Hong Ding; Eddie Reed; Qingdi Q Li
Journal:  Anticancer Res       Date:  2004 May-Jun       Impact factor: 2.480

7.  Prognostic significance of vascular endothelial growth factor expression in ovarian cancer patients: a long-term follow-up.

Authors:  C Rudlowski; A-K Pickart; C Fuhljahn; T Friepoertner; B Schlehe; S Biesterfeld; W Schroeder
Journal:  Int J Gynecol Cancer       Date:  2006 Jan-Feb       Impact factor: 3.437

8.  Vascular endothelial growth factor (VEGF) concentration in sera and tumor effusions from patients with ovarian carcinoma.

Authors:  A Harlozinska; P Sedlaczek; J Kulpa; M Grybos; E Wójcik; A Van Dalen; R Einarsson
Journal:  Anticancer Res       Date:  2004 Mar-Apr       Impact factor: 2.480

9.  Prognostic value of Ca 125 levels during primary therapy.

Authors:  Susanne Markmann; Bernd Gerber; Volker Briese
Journal:  Anticancer Res       Date:  2007 Jul-Aug       Impact factor: 2.480

Review 10.  Progress and challenges in screening for early detection of ovarian cancer.

Authors:  Ian J Jacobs; Usha Menon
Journal:  Mol Cell Proteomics       Date:  2004-02-05       Impact factor: 5.911

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  16 in total

1.  Evaluation of a hypoxia regulated gene panel in ovarian cancer.

Authors:  Amanda F Baker; Scott W Malm; Ritu Pandey; Cindy Laughren; Haiyan Cui; Denise Roe; Setsuko K Chambers
Journal:  Cancer Microenviron       Date:  2015-05-22

Review 2.  Precision targeted therapy of ovarian cancer.

Authors:  Justin Sapiezynski; Oleh Taratula; Lorna Rodriguez-Rodriguez; Tamara Minko
Journal:  J Control Release       Date:  2016-10-14       Impact factor: 9.776

Review 3.  The emerging role of HE4 in the evaluation of epithelial ovarian and endometrial carcinomas.

Authors:  Archana R Simmons; Keith Baggerly; Robert C Bast
Journal:  Oncology (Williston Park)       Date:  2013-06       Impact factor: 2.990

4.  Immunosuppressive parameters in serum of ovarian cancer patients change during the disease course.

Authors:  An Coosemans; Judit Decoene; Thaïs Baert; Annouschka Laenen; Ahmad Kasran; Tina Verschuere; Sven Seys; Ignace Vergote
Journal:  Oncoimmunology       Date:  2015-12-21       Impact factor: 8.110

5.  The roles of beta-adrenergic receptors in tumorigenesis and the possible use of beta-adrenergic blockers for cancer treatment: possible genetic and cell-signaling mechanisms.

Authors:  Khanh Vinh Quốc Lu'o'ng; Lan Thi Hoàng Nguyễn
Journal:  Cancer Manag Res       Date:  2012-12-18       Impact factor: 3.989

Review 6.  Ovarian cancer: in search of better marker systems based on DNA repair defects.

Authors:  Dominic Varga; Miriam Deniz; Lukas Schwentner; Lisa Wiesmüller
Journal:  Int J Mol Sci       Date:  2013-01-04       Impact factor: 5.923

7.  Prognostic significance of pretreatment VEGF, survivin, and Smac/DIABLO serum levels in patients with serous ovarian carcinoma.

Authors:  Bozena Dobrzycka; Beata Mackowiak-Matejczyk; Katarzyna Maria Terlikowska; Bozena Kulesza-Bronczyk; Maciej Kinalski; Slawomir Jerzy Terlikowski
Journal:  Tumour Biol       Date:  2015-01-12

Review 8.  Critical appraisal of bevacizumab in the treatment of ovarian cancer.

Authors:  Hiroyuki Yoshida; Akira Yabuno; Keiichi Fujiwara
Journal:  Drug Des Devel Ther       Date:  2015-04-28       Impact factor: 4.162

Review 9.  Bevacizumab in combination with chemotherapy for the treatment of advanced ovarian cancer: a systematic review.

Authors:  Gerasimos Aravantinos; Dimitrios Pectasides
Journal:  J Ovarian Res       Date:  2014-05-19       Impact factor: 4.234

10.  Stathmin Regulates Hypoxia-Inducible Factor-1α Expression through the Mammalian Target of Rapamycin Pathway in Ovarian Clear Cell Adenocarcinoma.

Authors:  Kazuhiro Tamura; Mikihiro Yoshie; Eri Miyajima; Mika Kano; Eiichi Tachikawa
Journal:  ISRN Pharmacol       Date:  2013-05-30
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