Introduction
Epithelial ovarian cancer (EOC) has the highest mortality
rate among all gynecological cancers worldwide which has been historically called "the silent killer" because
the symptoms of the disease cannot be seen until
advanced stages.[] The absence of symptoms in early
stages leads to delayed diagnosis of most cases and 5-year survival rate drops below 35% in the advanced
stages.[] At present, standard treatment of EOC involves
primary debulking surgery (PDS), followed by
adjuvant platinum-taxane combination chemotherapy.
However, patients with unresectable tumors which
confirmed by radiological assessment or laparoscopic
evaluation and patients with low-performance scores
due to comorbidities are not suitable for PDS. In such
cases, neoadjuvant chemotherapy followed by interval
surgery is an alternative strategy.[]
However, to date, there is no reliable biomarker has
been developed to predict the response to chemotherapy
in ovarian cancer patients in adjuvant or neoadjuvant
settings. Although attention has turned to genetic
tests and molecular biomarkers in this regard,
genetic tests are quite expensive and relatively timeconsuming,
and molecular biomarkers require special
equipment and trained personnel, which has a high
economic burden, also.[] On the other hand, recent
studies have shown that conventional biomarkers have
promising results on the issue. It is now known that
inflammation plays an important role in the development
of carcinogenesis, and is involved in all stages of
cancer development.[-] In this regard, many conventional
biomarkers are in use to assess systemic inflammation
including neutrophil and lymphocyte counts,
mean platelet volume (MPV), and platelet to lymphocyte
ratio (PLR). In addition to all these, platelets play
an active role in systemic inflammation, both enzymatically
and metabolically. In the chronic inflammatory
process, there is an increase in the thrombotic functions
of platelets. Accordingly, MPV increases as the
stimulation of chronic inflammation process.[] Several
studies have evaluated conventional hemogram
parameters such as neutrophil and lymphocyte counts,
MPV, red cell distribution width (RDW), PLR, and
neutrophil to lymphocyte (NLR) in terms of survival
on different cancers including ovarian cancer.[,]
The aim of the present study was to evaluate the clinical
importance of conventional biomarkers in newly
diagnosed advanced-stage ovarian cancer patients before
and after neoadjuvant chemotherapy compared to
healthy controls and to investigate the clinical importance
of conventional markers in terms of survival and
platinum response on ovarian cancer patients.
Methods
Participants
Newly diagnosed patients with advanced stage ovarian
carcinoma were evaluated for the study. The inclusion criteria were (a) patients with histologically confirmed
serous ovarian carcinoma that recurring neoadjuvant
treatment; (b) patients who completed planned chemotherapy;
and (c) patients who operated in our center.
The exclusion criteria were consisting the followings; (a)
recurrent disease or history of secondary malignancy;
(b) unavailability of laboratory and pathology results;
(c) primary refractory disease; (d) the evidence of
other comorbidities including hematologic, cardiopulmonary,
and inflammatory disease; and (e) treatment
with anti-aggregation/coagulant therapy, antilipidemic,
and anti-inflammatory drugs as well as recent blood
transfusions. Patients were given standard chemotherapy
regimen with carboplatin AUC 5-6 and paclitaxel
175 mg/m2 for every 21 days pre- and postoperatively
for 3-4 cycles which was decided by clinician opinion.
In addition, patients were followed up with physical examination
and computed tomography every 3 months
for 2 years and every 6 months after treatment.
Methods
Hematological parameters of patients at the time of the
diagnosis and after three cycle of neoadjuvant chemotherapy
were recorded. The following information was
obtained from the patient charts: Age, menopause status,
date of the operation, ascites, FIGO stage, postoperative
residual tumor, and the final status of the
patient. Optimal surgery is categorized as R1 in this
study and defined as the presence of ≤1 cm residual
tumor; while tumor free resection is categorized as R0.
Complete blood counts (CBC) are measured routinely
by Beckman Coulter DxH 800 Hematology Analyzer
(Beckman Coulter UniCel DxH 800 Coulter Cellular
Analysis System) in our center and blood samples are
measured with tri-potassium ethylenediamine tetraacetic
acid (K3-EDTA) and are analyzed 1 h after
venepuncture. The PLR was calculated by dividing the
platelet count by the lymphocyte count; and NLR was
calculated by dividing the neutrophil count by lymphocyte
count. Disease-free survival (DFS) is defined
as the time between the date of the operation and radiologically
confirmed disease recurrence. Overall survival
(OS) is defined as the time between the date of the
pathologically confirmed disease diagnosis and death
or the date of the last control.
Statistical Analysis
Statistical analysis and data collection were performed
with SPSS version 20.0 (SPSS Inc., Chicago, IL, USA).
The results were summarized as descriptive statistics
(median, minimum, and maximum). Patients were assigned to one of two study group which based on
median values hemogram parameters for comparison.
The relationship between the disease characteristics
and categorized laboratory data was tested using Chisquare
test. As the observed frequencies in the cells of
in the test were not below 5, Pearson Chi-Square values
are taken into consideration. Survival analyses were estimated
using the Kaplan-Meier Curve and compared
with log-rank test. Cox regression multivariate analyses
were used to evaluate independence analysis and
hazard ratio estimation. P value less than 0.05 was considered
as statistically significant.
Results
Patient Population
Median age of the all patient population was 57 years
(ranged between 38 and 78). Nineteen of patients
(36.5%) were operated with optimal surgery; whereas
tumor free resection is achieved in 63.5% (n=33). Median
DFS was 23.3 months (ranged between 9.1 and
111 months). Median OS was 50.6 months (ranged
between 15.3 and 111). Median and range values of
hemogram parameters are shown in Table 1 and median
values of hemogram parameters were accepted as
cutoff values to organize categorical variables.
Table 1: Median and range values of hemogram parameters
The Relationship of Hemogram Parameters with
Disease Characteristics
The relationships between hemogram parameters at the
time of diagnosis and disease characteristics/treatment response were tested. Elevated levels of neutrophils,
NLR and PLR at the time of diagnosis were statistically
significantly associated with excess amount of ascites
(p=0.023, p=0.021, and p=0.012, respectively). Furthermore,
the lower levels of neutrophils and hemoglobin
(HGB); and higher levels of RDW, RDW/PLT,
and RDW/HGB ratio than median were predictors
of platinum-sensitivity (p<0.05 for all). Only MPV to
lymphocyte ratio and HGB level at the time of diagnosis
were associated with post-operative residual disease
(p=0.044 and p=0.048, respectively) (Table 2).
Table 2: The relationship of hemogram parameters with disease characteristics
The Relationship of Hemogram Parameters with
Survival Results
In univariate analysis, while decreased MPV at the time
of diagnosis (p=0.037), platinum sensitivity (p=0.047),
and lower stage (p=0.049) were associated with longer
DFS significantly; in multivariate analysis, platinum
sensitivity, and MPV were statistically associated with
DFS significantly (Table 3).
Table 3: Univariate analysis of analyzed prognostics factors
In addition, decreased neutrophils (p=0.042), elevated
RDW (p=0.036), decreased MPV (p=0.046),
decreased NLR (p=0.033), decreased CA 12-5 preoperatively
(p=0.034), ascites amount of ?500 cc preoperatively
(p=0.049), presence of platinum sensitive
disease (p=0.015), and lower stage (p=0.043) were
significantly associated with longer OS in univariate
analysis. Multivariate analysis is showed that platinum
sensitivity and MPV were also significantly associated
with OS statistically (Table 4).
Table 4: Cox regression analysis of overall survival
results of the patients
Prediction of Chemotherapy Efficacy Based on the
MPV
To investigate the effect of chemotherapy on variation
of MPV and whether the difference is effective on survival,
we also evaluated preoperative MPV levels of
patients and analyzed as another factor. In univariate
analysis, decreased level of preoperative MPV was effective
for better OS results of the patients (p=0.036
for OS, p=0.270 for DFS). Furthermore, we divided all
patients into four groups to investigate the relationship
between prognosis of patients and MPV variation after
chemotherapy: Low-low group, low-high group,
high-low group, and high-high group. Patients with
persistently low MPV group had the best OS; while
persistently high MPV group had the worst OS in the
groups (p=0.011, Fig. 1). Patients with high diagnostic
MPV but low pre-operative MPV had an improved OS
of 62.3 months, and patients with a persistently high
MPV had a OS of 45.8 months.
Fig 1: The Kaplan-Meier plots of overall survival for patients
according to variation of MPV.
MPV: Mean platelet volume.
Discussion
The current study has evaluated the prognostic and
predictive importance of hemogram parameters in our
patient population who received pre-operative chemotherapy
for advanced ovarian carcinoma. Although,
few studies are existing which assessed diagnostic potential
of inflammatory markers in ovarian carcinoma;
it is the first study that evaluating and demonstrating
the MPV value is associated with survival results of patients
with advanced ovarian carcinoma, to the best of
our knowledge. In this study, multivariate analysis has showed that platinum sensitivity and MPV were statistically
significantly associated with DFS and OS. Moreover,
the patients with persistently low MPV group
had the best OS; while persistently high MPV group
had the worst OS in the groups. N MPV variation with
chemotherapy was predictive of better survival which
could be translated to predict the patients who will derive
more benefit from treatment. Patients with high
diagnostic MPV but low preoperative MPV had an improved
OS of 62.3 months, and patients with a persistently
high MPV had a OS of 45.8 months. Therefore,
evaluation of pre- and post-treatment MPV levels may
be considered as a potential predictor of better treatment
response.
Hemogram parameters can contribute to the diagnosis
of diseases and have a prognostic value in
some pathology which is studying in the many latest
researches. Changes in the serum levels of inflammatory
parameters in the blood count (e.g., absolute leucocyte
or neutrophil count, PLR, NLR, and recently,
MPV) have prognostic impact on many cancer subtypes.
Although the routine analysis of the complete
blood tests is commonly used in carcinoma patients
for many years; their clinical significance has not been
elucidated, and their prognostic value has been limitedly
studied in EOC. Recent studies have shown that
thrombocytosis might be associated with advanced
disease and probably has prognostic effect on EOC.
[,] Cho et al.[] have demonstrated that combination
of preoperative NLR and CA125 could be useful
as a discriminative marker for malign and benign
ovarian pathologies. On the other hand, Yang et al.[]
conducted a meta-analysis with 12 studies and found
that increased NLR was associated with worse survival
results in patients with EOC significantly.
Kemal et al.[] evaluated that MPV levels of patients
with EOC and pre-operative higher MPV levels
were measured in patients with EOC compared with
their control group. In addition, they showed that
MPV levels decreased significantly after surgical tumor
resection. Inversely, the results of the study that
held by Qin et al.[] showed that RDW levels were
higher; whereas lower MPV levels was observed in
cancer group compared with patients with benign
ovarian tumors. However, our study design was not
appropriate for diagnostic evaluation of MPV due to
lack of non-cancerous group, we have evaluated prognostic
significance of MPV. After multivariate analysis
MPV was found to be independent marker to predict
better survival results in patients with lower levels. The
association between survival of patients with EOC and the platelet parameters has been demonstrated in few
studies. Allensworth et al.[] suggested that thrombocytosis
predicted poorer DFS and OS in patients with
EOC. In contrast to our results, Yang et al. found that
MPV was lower in patients with all subtype of gynecological
cancer compared to controls, and patients with
low MPV showed shorter OS. However, they have evaluated
gynecological cancers comprehensively; their
cohort was consisting of 34 ovarian cancer patients.
Furthermore, they have not analyzed this specific subgroup
separately.[] Elevated MPV is associated with
worse survival outcome in patients with various cancers;
such as colorectal cancer,[] gastric cancer,[]
breast cancer,[] endometrial cancer,[] and biliary
tract cancer.[] However, there are conflicting results
in various other studies; which found that decreased
MPV levels were predicting poor prognosis in lung cancer,[] bladder cancer,[] renal cell carcinoma,[]
and pancreas carcinoma.[] Regarding the negatively or positively correlated outcomes that mentioned,
MPV has been shown to have prognostic value in the
previous studies of patients with malignancy. However,
within the 906 studies that we retracted with the comprehensive
PubMed search of "mean platelet volume,
MPV, and survival" keywords, no studies have showed
the survival effect of MPV on ovarian carcinoma. A
recent large meta-analysis which attempted to evaluate
prognostic and predictive value of MPV that held
on with 9894 cancer patients showed that; high MPV
had the strongest relationship with poor OS in gastric
cancer, followed by pancreatic cancer. There were no
patients with ovarian carcinoma in this meta-analysis.
[] Furthermore, another meta-analysis and review
that held with 2053 patients and 1396 healthy subjects
in 18 eligible studies, was not able to show survival effect
of MPV on this specific population.[]
Survival of Patients with Malignancy
We have also evaluated the relation of hemogram parameters
and disease characteristics; and found that elevated
levels of neutrophils, NLR and PLR at the time of
diagnosis were statistically significantly associated with
excess amount of ascites, HGB level and MPV to lymphocyte
ratio at the time of diagnosis were associated
with post-operative residual disease. In line with our
study, Sahin et al.[] evaluated inflammatory markers
in patients with ovarian carcinoma who undergone
primary resection; pre-operative PLR, NLR, and CRP
elevation were correlated with disease characteristics
such as ascites, stage, CA-125 levels and optimal resection
rates in their study. In addition, we have evaluated
predictors of platinum-sensitivity different from the
previous study; and found lower levels of neutrophils
and HGB; and higher levels of RDW, RDW/PLT, and
RDW/HGB ratio than median were correlated with
platinum sensitive disease (p<0.05 for all). The current
study is one of the few studies that able to show correlation
of hemogram parameters and treatment response.
Jeerakornpassawat et al.[] have shown that high NLR
is a potential predictive factor for platinum resistance.
However, we could not able to show any correlation
in serous ovarian carcinoma cohort; Kim et al.[]
showed that elevated PLR was predicting incomplete
response to chemotherapy in clear-cell cohort, which
subgroup is not included in our study.
The present study has some limitations. First, this
was a retrospective study with relatively small patient
population who diagnosed with advanced EOC.
Prospective studies with large patient populations are
therefore needed to confirm our study results. Further-more, since targeted therapies such as bevacizumab
or PARP inhibitors is not approved for first-line treatment
for EOC in our country, our patient population
was only used standard paclitaxel-carboplatin regimen
for treatment and was not used any maintenance therapy.
Hence, these results might be inconclusive for the
patients who have used globally standardized other
therapies. Nevertheless, to the best of our knowledge,
our study provides one of the few evidences for the use
of hemogram parameters for predicting survival and
chemotherapy response in patients with EOC.
Conclusion
MPV is a marker that can be easily evaluated during
CBC, with no additional cost to patients or health insurances.
Regarding the findings of the current study,
MPV might be a promising and a practical prognostic
factor in the field of EOC. However, we found
hemogram parameters are useful to predict disease
properties and survival in EOC; current knowledge is
extremely limited. Future studies should be designed
with large patient populations and predefined cutoffs
to reach firm conclusions.
Peer-review: Externally peer-reviewed.
Conflict of Interest: All authors declared no conflict of interest.
Ethics Committee Approval: The study was approved by
the Istanbul University, Istanbul Faculty of Medicine Dean's
Office Ethics Committee (No: 2021/156, Date: 05/02/2021).
Financial Support: None declared.
Authorship contributions: Concept - N.A., S.V., P.M.S.;
Design - N.A., S.V., P.M.S., S.T., H.S.; Supervision - N.A.,
Y.M., N.P., F.F., E.A., İ.D., H.O.S., S.T., S.V.; Funding - N.P.,
F.F., E.A., İ.D., S.V.; Materials - E.B., M.K., H.O.S.; Data collection
and/or processing - E.B., M.K., N.A., İ.D., E.A., F.F.,
Y.M., N.P.; Data analysis and/or interpretation - N.A., Y.M.,
P.M.S., S.V.; Literature search - S.T., H.S., N.A., İ.D., E.A.,
F.F., E.B.; Writing - N.A., Y.M.; Critical review - S.T., P.M.S.,
S.V., H.S.
References
Torre LA, Siegel RL, Ward EM, Jemal A. Global cancer
incidence and mortality rates and trends--an update.
Cancer Epidemiol Biomarkers Prev 2016;25(1):16?27.
Siegel RL, Miller KD, Jemal A. Cancer statistics, 2015.
CA Cancer J Clin 2015;65(1):5-29.
Wright AA, Bohlke K, Armstrong DK, Bookman MA, Cliby WA, Coleman RL, et al. Neoadjuvant chemotherapy
for newly diagnosed, advanced ovarian cancer:
Society of gynecologic oncology and american
society of clinical oncology clinical practice guideline.
Gynecol Oncol 2016;143(1):3-15.
Bhalla A, Zulfiqar M, Bluth MH. Molecular diagnostics
in colorectal carcinoma: Advances and applications
for 2018. Clin Lab Med 2018;38(2):311-42.
Itzkowitz SH, Yio X. Inflammation and cancer IV.
Colorectal cancer in inflammatory bowel disease: the
role of inflammation. Am J Physiol Gastrointest Liver
Physiol 2004;287(1):G7-17.
Elinav E, Nowarski R, Thaiss CA, Hu B, Jin C, Flavell
RA. Inflammation-induced cancer: Crosstalk between
tumours, immune cells and microorganisms. Nat Rev
Cancer 2013;13(11):759-71.
Lalosevic J, Gajic-Veljic M, Bonaci-Nikolic B, Stojkovic
Lalosevic M, Nikolic M. Combined intravenous pulse
and topical corticosteroid therapy for severe alopecia
areata in children: Comparison of two regimens. Dermatol
Ther. 2019;32(6):e13092.
Li JY, Li Y, Jiang Z, Wang RT, Wang XS. Elevated mean
platelet volume is associated with presence of colon
cancer. Asian Pac J Cancer Prev 2014;15(23):10501-4.
Kemal Y, Demirag G, Ekiz K, Yucel I. Mean platelet
volume could be a useful biomarker for monitoring
epithelial ovarian cancer. J Obstet Gynaecol
2014;34(6):515-8.
Sahin ZA, Toktas IU, Toraman C, Yuksel IT, Seyhan A,
Akbayir O. Clinical and prognostic value of pre-operative
systemic inflammatory markers in clinical course
and prognosis of ovarian cancer. Eur J Gynaecol Oncol
2020;41(6):924-30.
Soonthornthum T, Suraseraneewong V, Kengsakol K,
Wijaithum K, Kasemsan P, Prommatt S. Thrombocytosis
in advanced epithelial ovarian cancer. J Med Assoc
Thai 2007;90(8):1495-500.
Canzler U, Lück HJ, Neuser P, Sehouli J, Burges A,
Harter P, et al. Prognostic role of thrombocytosis in recurrent
ovarian cancer: A pooled analysis of the AGO
study group. Arch Gynecol Obstet 2020;301(5):1267-74.
Cho H, Hur HW, Kim SW, Kim SH, Kim JH, Kim YT,
et al. Pre-treatment neutrophil to lymphocyte ratio is
elevated in epithelial ovarian cancer and predicts survival
after treatment. Cancer Immunol Immunother
2009;58(1):15-23.
Yang Z, Gu JH, Guo CS, Li XH, Yang WC. Preoperative
neutrophil-to-lymphocyte ratio is a predictor of
survival of epithelial ovarian cancer: A systematic review
and meta-analysis of observational studies. Oncotarget
2017;8(28):46414-24.
Qin YY, Wu YY, Xian XY, Qin JQ, Lai ZF, Liao L, et
al. Single and combined use of red cell distribution width, mean platelet volume, and cancer antigen 125
for differential diagnosis of ovarian cancer and benign
ovarian tumors. J Ovarian Res 2018;11(1):10.
Allensworth SK, Langstraat CL, Martin JR, Lemens
MA, McGree ME, Weaver AL, et al. Evaluating the
prognostic significance of preoperative thrombocytosis
in epithelial ovarian cancer. Gynecol Oncol
2013;130(3):499-504.
Yang W, Chen YY, Bi C, Shu KY, Ye ML, Li FF, et al.
Predictive and prognostic values of preoperative
platelet parameters in patients with gynecological tumors.
J Clin Lab Anal 2020;34(7):e23295.
Li N, Yu Z, Zhang X, Liu T, Sun YX, Wang RT, et al. Elevated
mean platelet volume predicts poor prognosis
in colorectal cancer. Sci Rep 2017;7(1):10261.
Lian L, Xia YY, Zhou C, Shen XM, Li XL, Han SG, et al.
Mean platelet volume predicts chemotherapy response
and prognosis in patients with unresectable gastric
cancer. Oncol Lett 2015;10(6):3419-24.
Gu M, Zhai Z, Huang L, Zheng W, Zhou Y, Zhu R,
et al. Pre-treatment mean platelet volume associates
with worse clinicopathologic features and prognosis
of patients with invasive breast cancer. Breast Cancer
2016;23(5):752-60.
Chen H, Wu Q, Zhang Y, Li Q, Ma J, Kong F, et al.
Nomograms based on the novel platelet index score
predict postoperative prognosis in endometrial cancer.
Gynecol Oncol 2020;158(3):689-97.
Sun L, Wei Y, Chen Y, Hu W, Ji X, Xu H, et al. Comparison
of the prognostic value of platelet-related indices
in biliary tract cancer undergoing surgical resection.
Cancer Res Treat 2021;53(2):528-40.
Kumagai S, Tokuno J, Ueda Y, Marumo S, Shoji T,
Nishimura T, et al. Prognostic significance of preoperative
mean platelet volume in resected non-small-cell
lung cancer. Mol Clin Oncol 2015;3(1):197-201.
Wang X, Cui MM, Xu Y, Liu L, Niu Y, Liu T, et al.
Decreased mean platelet volume predicts poor
prognosis in invasive bladder cancer. Oncotarget
2017;8(40):68115-22.
Yun ZY, Zhang X, Liu YS, Liu T, Liu ZP, Wang RT, et al.
Lower mean platelet volume predicts poor prognosis
in renal cell carcinoma. Sci Rep 2017;7(1):6700.
Yagyu T, Saito H, Sakamoto T, Uchinaka E, Morimoto
M, Hanaki T, et al. Decreased mean platelet volume
predicts poor prognosis in patients with pancreatic
cancer. BMC Surg 2021;21(1):8.
Chen X, Li J, Zhang X, Liu Y, Wu J, Li Y, et al. Prognostic
and clinicopathological significance of pretreatment
mean platelet volume in cancer: A meta-analysis.
BMJ Open 2020;10(10):e037614.
Pyo JS, Sohn JH, Kang G. Diagnostic and prognostic
roles of the mean platelet volume in malignant tumors:
A systematic review and meta-analysis. Platelets
2016;27(8):722-8.
Jeerakornpassawat D, Suprasert P. Potential predictors
for chemotherapeutic response and prognosis in epithelial
ovarian, fallopian tube and primary peritoneal
cancer patients treated with platinum-based chemotherapy.
Obstet Gynecol Sci 2020;63(1):55-63.
Kim HS, Choi HY, Lee M, Suh DH, Kim K, No JH, et
al. Systemic inflammatory response markers and CA-
125 levels in ovarian clear cell carcinoma: A two center
cohort study. Cancer Res Treat 2016;48(1):250-8.
