Influence of thrombocytosis on the prognosis of endometrial cancer: Results from propensity score matching

Abstract

Thrombocytosis has been implicated as a potential prognostic biomarker in various malignancies, but its role in endometrial cancer (EC) remains unclear. This retrospective cohort study evaluated the prognostic value of elevated preoperative platelet count (PLT) in patients with EC. A total of 548 patients treated at Changhua Christian Hospital between 2010 and 2021 were included. Patients were classified into high (>400 × 10⁹/L) and normal PLT groups, and propensity score matching was applied in a 1:3 ratio to balance baseline characteristics. Recurrence, disease-free survival (DFS), and overall survival (OS) were assessed using Kaplan–Meier analysis and Cox proportional hazards modeling. After matching, 224 patients were analyzed. The high PLT group demonstrated significantly higher recurrence (37.5% vs 26.8%), shorter DFS (48.2% vs 67.3%), and reduced OS (71.4% vs 83.3%). Adjusted hazard ratios for high PLT were 1.76 for recurrence, 1.98 for DFS, and 2.11 for OS. These findings suggest that thrombocytosis is an independent prognostic factor in EC and may serve as a useful tool for risk stratification and treatment planning.

Keywords

endometrial cancer prognostic biomarkers thrombocytosis propensity score matching survival analysis

Introduction

Endometrial cancer (EC) is the fifth most common malignancy among women in Taiwan, with most patients diagnosed at an early stage and achieving a favorable 5-year overall survival (OS) rate of approximately 95% for localized disease.^1,2 However, the prognosis markedly worsens in cases of recurrence or metastasis, with 5-year survival declining to less than 20%.³ Despite advances in diagnostic methods and therapeutic strategies, predicting outcomes in EC remains challenging and heterogeneous.

Recent studies have demonstrated that hematological parameters such as preoperative anemia, thrombocytosis, and leukocytosis are associated with poor prognosis in EC, highlighting their potential value as prognostic biomarkers,^4–6 underscoring their potential utility as prognostic indicators. Among these, elevated platelet (PLT) counts have been identified as a potential predictor of unfavorable outcomes not only in EC but also in various other malignancies, including ovarian, colorectal, gastric, and lung cancers.^7–10 Biologically, platelets facilitate tumor progression by promoting angiogenesis, protecting tumor cells from immune surveillance, and aiding metastasis through multiple molecular pathways.¹¹ Given these pro-tumorigenic functions of platelets, several clinical studies have explored their prognostic relevance in EC.

Several studies have linked thrombocytosis with advanced stage, poor differentiation, and aggressive tumor behavior in EC.^5,12,13 However, these findings are not universally consistent, and the prognostic relevance of thrombocytosis in Asian populations remains unclear. Furthermore, many prior investigations have relied on univariate or conventional multivariate analyses that may not fully adjust for confounding factors such as comorbidities, tumor biology, and treatment modalities.^4,14,15

To address these gaps, this study evaluates the prognostic impact of preoperative thrombocytosis in a large, real-world cohort of Taiwanese patients with EC. By applying propensity score matching (PSM), we aimed to mitigate selection bias and better isolate the independent contribution of PLT count to survival outcomes. This study contributes population-specific evidence to support the incorporation of PLT count into risk stratification and individualized treatment planning in East Asian clinical settings.

Significance Statement

WHAT IS ALREADY KNOWN ON THIS TOPIC?

Thrombocytosis has been associated with poor prognosis in several malignancies, including gynecologic cancers.

Previous studies have suggested a link between elevated platelet counts and advanced stage, aggressive histology, and worse survival in endometrial cancer.

Most published evidence on thrombocytosis in endometrial cancer is derived from Western populations, and many studies lack rigorous adjustment for confounders.

WHAT THIS STUDY ADDS?

This study used a large, well-characterized Taiwanese cohort and applied propensity score matching (PSM) to evaluate the prognostic value of preoperative thrombocytosis in endometrial cancer.

High preoperative platelet counts (>400 × 10⁹/L) were independently associated with increased recurrence and lower disease-free and overall survival.

The association remained robust after multivariate adjustment and sensitivity analyses, confirming thrombocytosis as an independent prognostic biomarker.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE, OR POLICY?

Routine platelet count, a widely available and low-cost laboratory test, may be incorporated into preoperative risk stratification models for endometrial cancer.

These findings support further evaluation of thrombocytosis in population-specific prognostic tools and may influence decisions regarding adjuvant therapy or follow-up intensity.

Materials and methods

Patient cohort

A retrospective cohort study was conducted at Changhua Christian Hospital (CCH), a tertiary medical center in central Taiwan. Data were obtained from the CCH Clinical Research Database, which integrates cancer registry records, electronic medical records, laboratory data, outpatient visits, and mortality records. A total of 860 patients diagnosed with EC between January 1, 2010 and December 30, 2021, were initially reviewed. Patients with coexisting breast cancer, unspecified pathological diagnoses, or incomplete laboratory data were excluded, yielding a final cohort of 548 patients with EC (Figure 1). The study was approved by the Institutional Review Board of CCH (IRB No. 240710).

Definition of PLT count and other confounders

Preoperative PLT counts were categorized as high (>400 × 10⁹/L) or normal (≤400 × 10⁹/L), based on established clinical thresholds.¹⁶ Demographic and clinical variables were extracted, including age, body mass index (BMI), menopausal status, smoking and alcohol history, International Federation of Gynecology and Obstetrics (FIGO) stage, lymphovascular invasion, histologic subtype, comorbidities (hypertension and diabetes), and preoperative laboratory parameters. Laboratory tests included hemoglobin (Hb), red blood cell distribution width (RDW), hematocrit (Hct), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and cancer antigen 125 (CA-125).

Study outcomes

Patients were followed according to institutional guidelines, with clinical evaluations conducted every 3 months during the first 2 years post-treatment and semiannually thereafter. The primary objective of this study was to assess the long-term impact of preoperative PLT count on recurrence and survival outcomes in patients with EC who had undergone surgical intervention.

Recurrence was defined as radiologic or histologic evidence of disease during follow-up. Disease-free survival (DFS) was measured from the date of initial diagnosis to the first documented recurrence, secondary primary EC, or death from any cause. OS was defined as the time from diagnosis to cancer-related death or the end of the study period, whichever occurred first.

Statistical analysis

Continuous variables were reported as medians with interquartile ranges (IQRs), while categorical variables were summarized as counts and percentages. Group comparisons were performed using the Chi-square test for categorical variables and the Mann–Whitney U test for continuous variables. To address baseline differences between groups, PSM was conducted using a 1:3 optimal matching algorithm based on variables selected for their established prognostic relevance to both thrombocytosis and EC outcomes (age, FIGO stage, Hb, RDW, MCV, MCHC, and CA-125). Propensity scores were estimated using logistic regression. Optimal matching was applied to maximize covariate balance while retaining the greatest number of cases. After matching, baseline characteristics were well balanced between groups. This methodological approach—including covariate selection, propensity score estimation, and optimal matching—is supported by prior comparative methodological research and its widespread use in observational studies.^17,18

Survival outcomes were analyzed using the Kaplan–Meier method, and differences between groups were assessed with the log-rank test. Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HRs) for recurrence, DFS, and OS across PLT groups. Subgroup analyses were stratified by demographic variables and FIGO stage (I–II vs III–IV), and continuous variables were dichotomized by their median values.

A sensitivity analysis using an alternative PLT cutoff (>390 × 10⁹/L) was also performed to assess the robustness of findings. All statistical analyses and graphical visualizations were conducted using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA) and R version 4.3.2 (R Foundation for Statistical Computing, Vienna, Austria). A two-sided p-value < 0.05 was considered statistically significant.

Results

Clinical characteristics of the high PLT and normal PLT groups

The demographic and clinical characteristics of the patients are presented in Table 1. Of the 548 patients, 58 exhibited elevated PLT and 490 had normal PLT counts. Prior to PSM, significant differences were observed between the high and normal PLT groups in terms of age (p < 0.001); postmenopausal status (p < 0.001); FIGO stage (p = 0.002); and preoperative Hb (p < 0.001), RDW (p < 0.001), Hct (p < 0.001), MCV (p < 0.001), MCH (p < 0.001), MCHC (p < 0.001), and CA-125 (p < 0.001). Based on these findings, PSM was performed at a 1:3 ratio, resulting in a matched cohort of 224 patients that comprised 56 in the high PLT group and 168 in the normal PLT group with well-balanced clinical characteristics (Table 1).

Table 1.

Demographic and clinical characteristics of participants, stratified by preoperative platelet (PLT) count before and after PSM.

	Before PSM			After PSM
Characteristics	High PLT (n = 58)	Normal PLT (n = 490)	p-Value	High PLT (n = 56)	Normal PLT (n = 168)	p-Value
Age (years)	50.0 (45.0, 55.0)	56.5 (50.0, 62.0)	<0.001	50.0 (44.5, 55.0)	50.0 (44.5, 55.0)	0.881
BMI (kg/m²)	27.1 (22.8, 31.9)	25.5 (22.7, 29.3)	0.075	27.1 (22.7, 31.6)	25.0 (22.5, 30.5)	0.195
Postmenopausal	23 (39.66)	326 (66.53)	<0.001	22 (39.29)	57 (33.93)	0.467
Comorbidity disease
Diabetes mellitus	10 (17.24)	77 (15.71)	0.764	10 (17.86)	27 (16.07)	0.755
Hypertension	12 (20.69)	160 (32.65)	0.063	12 (21.43)	45 (26.79)	0.425
Smoking habits	2 (3.45)	10 (2.04)	0.489	2 (3.57)	5 (2.98)	0.825
Alcohol habits	6 (10.34)	29 (5.92)	0.192	6 (10.71)	9 (5.36)	0.165
FIGO stage			0.002			0.648
I	33 (56.90)	376 (76.73)		31 (55.26)	107 (63.69)
II	3 (5.17)	25 (5.10)		3 (5.36)	9 (5.36)
III	13 (22.41)	65 (13.27)		13 (23.21)	34 (20.24)
IV	9 (15.52)	24 (4.90)		9 (16.07)	18 (10.71)
Lymphovascular invasion	8 (13.79)	41 (8.37)	0.171	8 (14.29)	18 (10.71)	0.470
Endometrioid carcinoma	45 (77.59)	414 (84.49)	0.178	43 (76.79)	138 (82.14)	0.378
Preoperative laboratory tests
Hemoglobin (g/dL)	9.9 (8.1, 12.2)	13.0 (11.6, 13.9)	<0.001	10.2 (8.6, 12.3)	10.6 (9.4, 12.8)	0.083
RDW (%)	17.2 (13.6, 20.3)	13.7 (13.0, 15.2)	<0.001	17.1 (13.6, 20.2)	15.4 (13.6, 19.6)	0.339
Hct (%)	30.7 (27.2, 36.6)	38.8 (35.4, 41.5)	<0.001	31.5 (27.7, 36.7)	33.3 (29.4, 38.1)	0.070
MCV (fL)	81.3 (70.9, 87.1)	89.0 (82.6, 92.6)	<0.001	81.9 (70.4, 88.0)	82.6 (74.4, 89.9)	0.408
MCH (pg)	26.1 (21.9, 29.4)	29.7 (27.2, 31.2)	<0.001	26.5 (22.0, 29.4)	27.1 (23.1, 30.0)	0.316
MCHC (g/dL)	32.3 (30.8, 33.5)	33.3 (32.3, 33.9)	<0.001	32.4 (31.0, 33.5)	32.5 (31.4, 33.7)	0.255
CA-125			<0.001			0.396
<35 (kU/L)	134 (27.35)	356 (72.65)		82 (48.81)	86 (51.19)
≥35 (kU/L)	33 (56.90)	25 (43.10)		31 (55.36)	25 (44.64)
Recurrence	22 (37.93)	142 (28.98)	0.159	21 (37.50)	45 (26.79)	0.128
Death	16 (27.59)	63 (12.86)	0.003	16 (28.57)	28 (16.67)	0.052

BMI: body mass index; CA-125: cancer antigen 125; FIGO: international federation of gynecology and obstetrics; HCT: hematocrit; MCV: mean corpuscular volume; MCH: mean corpuscular hemoglobin; MCHC: mean corpuscular hemoglobin concentration; PLT: platelet; RDW: red blood cell volume distribution width.

Data are presented as median (interquartile range) or frequency (%).

Long-term outcomes and the influence of preoperative PLT count on prognosis

To assess the influence of preoperative PLT count on prognosis, the 5-year prevalence of recurrence, DFS, and OS were analyzed on the basis of the PLT count. The median follow-up time was 5.1 (IQR: 2.9–7.7) years. The 5-year prevalence rates of recurrence, DFS, and OS for the overall population were 29.9%, 31%, and 14.4%, respectively. After PSM, these rates for the matched patients were 29.5%, 37.5%, and 19.6%, respectively.

Figure 2 presents Kaplan–Meier survival curves comparing 5-year recurrence, DFS, and OS between the two groups after PSM. The Kaplan–Meier survival curves indicate that patients with a high PLT count exhibited significantly higher recurrence rates (37.5% vs 26.8%, p = 0.033), shorter DFS (48.2% vs 67.3%, p = 0.003), and lower OS (71.4% vs 83.3%, p = 0.017) than those with normal PLT counts.

To investigate the association between high preoperative PLT counts and EC survival, Cox regression analysis was conducted. The results revealed that patients with a high PLT count exhibited a significantly higher risk of recurrence, DFS, and OS events than those with normal PLT counts. The HR after PSM was 1.76 (95% CI: 1.05–2.96, p = 0.032) for recurrence, 1.98 (95% CI: 1.26–3.11, p = 0.003) for DFS, and 2.11 (95% CI: 1.14–3.90, p = 0.018) for OS (Table 2).

Table 2.

Results of the univariate and multivariate analysis of prognostic factors in the PLT groups before and after PSM.

	Recurrence		DFS		OS
Analysis	HR (95% CI)	p-Value	HR (95% CI)	p-Value	HR (95% CI)	p-Value
Univariate analysis
Normal PLT	1		1		1
High PLT	1.69 (1.08, 2.64)	0.022	2.23 (1.50, 3.32)	<0.001	2.73 (1.58, 4.71)	<0.001
Multivariate analysis^a
Normal PLT	1		1		1
High PLT	1.98 (1.19, 3.30)	0.008	1.89 (1.19, 3.00)	0.007	1.37 (0.72, 2.62)	0.338
Propensity score match analysis
Normal PLT	1		1		1
High PLT	1.76 (1.05, 2.96)	0.032	1.98 (1.26, 3.11)	0.003	2.11 (1.14, 3.90)	0.018

CI: confidence interval; DFS: disease-free survival; HR: hazard ratio; OS: overall survival; PLT: platelet.

In a multivariate Cox proportional-hazard regression analysis by using Firth’s penalized method, age, postmenopausal status, FIGO stage, hemoglobin level, RDW, MCV, MCHC, and CA-125 were adjusted for.

Supplemental Table S1 presents the results of the sensitivity analysis, which are consistent with the primary study findings.

Subgroup analysis of the influence of preoperative PLT count on prognosis

A subgroup analysis was conducted to investigate the influence of preoperative PLT count on prognosis. The results revealed no interaction effect between PLT count and clinical outcomes (Figure 3).

Additional risk factors for EC prognosis

The results of the risk factor analysis (Figure 4) revealed that the primary factors that contributed to recurrence were age (aHR: 1.02, 95% CI: 1.00–1.04, p = 0.047) and FIGO stage (III–IV vs I–II; aHR: 1.97, 95% CI: 1.33–2.91, p < 0.001). Conversely, a higher preoperative MCV level (aHR: 0.98, 95% CI: 0.95–1.00, p = 0.043) was associated with a lower risk of recurrence (Figure 4(a)). The factors that significantly influenced poorer DFS were age (aHR: 1.03, 95% CI: 1.01–1.05, p = 0.001) and FIGO stage (III–IV vs I–II; aHR: 2.98, 95% CI: 2.10–4.23, p < 0.001; Figure 4(b)). Moreover, the significant risk factors for poorer OS were age (aHR: 1.04, 95% CI: 1.02–1.07, p = 0.001), FIGO stage (III–IV vs I–II; aHR: 4.31, 95% CI: 2.62–7.11, p < 0.001), and CA-125 level (aHR: 1.89, 95% CI: 1.13–3.17, p = 0.016; Figure 4(c)).

Discussion

This study demonstrates that high preoperative PLT counts (>400 × 10⁹/L) are independently associated with adverse clinical outcomes in EC, including increased recurrence and reduced disease-free and OS. By employing PSM, we minimized potential confounding and confirmed the prognostic value of thrombocytosis using a methodology that approximates randomized comparisons. Subgroup and sensitivity analyses further corroborated the robustness and consistency of this association. As iron deficiency and anemia are well-recognized causes of secondary (reactive) thrombocytosis,¹⁹ we incorporated hematologic indices reflecting iron status—such as Hb, RDW, MCV, and MCHC—into the PSM model to balance these confounders between groups. This approach strengthens the inference that thrombocytosis represents an independent prognostic marker in EC rather than a byproduct of nonmalignant processes.²⁰

The prevalence of thrombocytosis in this cohort (10.6%) aligns with previously reported rates.^21,22 Although a PLT threshold of >400 × 10⁹/L is commonly used to define thrombocytosis,¹⁵ prior studies have explored alternative cutoffs. Notably, one study reported that a threshold of 350 × 10⁹/L was not associated with progression-free or OS,²³ whereas another using a 390 × 10⁹/L cutoff demonstrated significant associations with DFS.⁶ Our sensitivity analysis confirmed that a threshold of >390 × 10⁹/L remains prognostically relevant, while 350 × 10⁹/L lacked predictive accuracy in our population.

The biological plausibility of these findings is supported by literature across gynecologic and other solid malignancies. In ovarian cancer, thrombocytosis has been associated with anemia, elevated CA-125, advanced disease, and suboptimal cytoreduction,²⁴ while in cervical cancer, it has been linked to inferior survival following chemoradiation.²⁵ In EC, thrombocytosis is related to poor histologic differentiation, lymphovascular space invasion, deep myometrial invasion, cervical extension, and lymph node metastasis.²⁶ More broadly, thrombocytosis correlates with larger tumor burden, advanced stage, high-grade histology, and enhanced metastatic potential across multiple cancer types.^27,28

Importantly, the adverse prognostic significance of thrombocytosis extends beyond gynecologic malignancies. Multiple meta-analyses and large cohort studies have consistently demonstrated that elevated PLT counts are associated with inferior survival outcomes across a range of solid tumors, including lung, gastric, colorectal, and renal cancers. For instance, Zhang et al.²⁹ reported that thrombocytosis predicted worse OS and more advanced disease stages in a pooled analysis encompassing several malignancies, while Shu et al.³⁰ confirmed these findings in a comprehensive umbrella review. Collectively, these data reinforce that thrombocytosis serves as a robust, accessible, and clinically meaningful prognostic biomarker both within and beyond gynecologic oncology.

Beyond clinical associations, experimental evidence demonstrates that platelets actively promote tumor progression. Haemmerle et al.³¹ comprehensively delineated the molecular mechanisms by which platelet activation enhances tumor survival, angiogenesis, immune evasion, and metastasis. Inflammatory cytokines such as interleukin-1, interleukin-6, and interleukin-11 stimulate thrombopoiesis, while tumor-derived factors activate platelet aggregation.^32,33 Activated platelets release pro-angiogenic and immunosuppressive mediators—such as vascular endothelial growth factor, transforming growth factor-beta, and prostaglandin E2—that promote neovascularization and facilitate immune evasion.^34,35 Platelet adhesion molecules, including P-selectin and GPIIb/IIIa, enable tumor cells to adhere to the endothelium and extravasate, thereby supporting metastasis.^35,36 Tumor cell–induced platelet aggregation also shields cancer cells from natural killer cell–mediated cytotoxicity, thereby enhancing metastatic potential.

Given its wide availability and low cost, PLT count could serve as a practical component of preoperative risk stratification models in EC. Integration with other clinical and molecular parameters—such as CA-125, FIGO stage, and tumor histology—may further improve prognostic precision. Particularly in settings where molecular testing is not routinely accessible, thrombocytosis may serve as a surrogate marker to guide decisions regarding adjuvant therapy and surveillance intensity.

Our findings also underscore the relevance of other known prognostic factors in EC, including elevated CA-125 levels and FIGO stage.^37–40 While FIGO recently revised its staging system to incorporate molecular and histologic classifications,⁴¹ our study provides complementary evidence that readily available hematologic parameters retain prognostic value and should not be overlooked.

It is plausible that thrombocytosis reflects an underlying biological phenotype not yet captured by current staging systems. Future studies should investigate the relationship between thrombocytosis and molecular subtypes of EC, such as p53-abnormal or copy-number high tumors, which are associated with poor prognosis. In addition, several methodological and population-specific limitations should be considered when interpreting our findings. Although obesity is a well-established risk factor for EC,⁴² our study population was characterized by lower overall BMI values compared with typical Western cohorts, consistent with epidemiologic data indicating a substantially lower prevalence of obesity among East Asian populations.⁴³ This ethnic and geographic difference may limit the generalizability of our findings. Furthermore, we were unable to fully account for the effects of obesity on PLT count because BMI data were incomplete for some patients and, therefore, were not included in the matching process.

Recent studies suggest that obesity-driven chronic low-grade inflammation may increase PLT counts through upregulation of interleukin-6 and thrombopoietin signaling,⁴⁴ potentially influencing both PLT count and EC outcomes. Therefore, the potential impact of metabolic and inflammatory status should be considered when interpreting our results. This limitation highlights the need for future studies in larger, ethnically diverse cohorts with comprehensive metabolic profiling. Finally, the retrospective, single-center design may further limit generalizability, and residual confounding cannot be fully excluded, even with PSM. While our findings support the prognostic role of thrombocytosis in EC, causality cannot be established.

In conclusion, preoperative thrombocytosis is an independent predictor of poor prognosis in Taiwanese patients with EC. These results support the integration of PLT count into clinical decision-making and highlight the need for prospective studies to validate these findings and explore underlying molecular mechanisms.

Supplemental Material

sj-docx-1-imj-10.1177_10815589261422249 – Supplemental material for Influence of thrombocytosis on the prognosis of endometrial cancer: Results from propensity score matching

Supplemental material, sj-docx-1-imj-10.1177_10815589261422249 for Influence of thrombocytosis on the prognosis of endometrial cancer: Results from propensity score matching by Tung-Ying Wu, Pei-Ru Lin, Chew-Teng Kor, Ying-Lin Hsu and Ming-Ju Chen in Journal of Investigative Medicine

Footnotes

Ethical considerations

The study protocol was approved by the Institutional Review Board of Changhua Christian Hospital (IRB No. 240710) and was conducted in accordance with the principles of the Declaration of Helsinki. The requirement for informed consent was waived due to the retrospective nature of the study and the use of de-identified data.

Author contributions

M-JC, P-RL, and T-YW conceived and designed the study. M-JC and T-YW contributed to data acquisition. M-JC and P-RL contributed to statistical analysis. M-JC, C-TK, and Y-LH contributed to data interpretations. M-JC and T-YW contributed to the drafting of the manuscript. C-TK and Y-LH contributed to the final revision of the manuscript. All authors provided critical feedback on the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplemental material

Supplemental material for this article is available online.

ORCID iDs

Tung-Ying Wu

Pei-Ru Lin

Chew-Teng Kor

Ying-Lin Hsu

Ming-Ju Chen

References

Taiwan Cancer Registry. Incidence and mortality rates for the top 10 cancers among females in Taiwan, https://twcr.tw/?page_id=1855&lang=en (2021, accessed 28 March 2024).

Koppikar

Oaknin

Babu

, et al. Pan-Asian adapted ESMO Clinical Practice Guidelines for the diagnosis, treatment and follow-up of patients with endometrial cancer. ESMO Open 2023; 8(1): 100774.

Sykaras

Christofidis

Politi

, et al. Exosomes on endometrial cancer: a biomarkers treasure trove? Cancers (Basel) 2022; 14(7): 1733.

Yokoi

Mabuchi

Komura

, et al. Incorporation of pretreatment leukocytosis and thrombocytosis into the FIGO staging system for prognosis in surgically treated endometrial cancer. Int J Gynaecol Obstet 2020; 151(2): 272–278.

Tal

Eitan

Gemer

, et al. Prognostic significance of pretreatment thrombocytosis in endometrial cancer: an Israeli Gynecologic Oncology Group study. Int J Gynecol Cancer 2021; 31(11): 1437–1442.

Njolstad

Engerud

Werner

, et al. Preoperative anemia, leukocytosis and thrombocytosis identify aggressive endometrial carcinomas. Gynecol Oncol 2013; 131(2): 410–415.

Balescu

Bacalbasa

Brezean

, et al. The significance of preoperative thrombocytosis in ovarian cancer patients. Roman Med J 2022; 69(4): 144–146.

Pedersen

Milman

Prognostic significance of thrombocytosis in patients with primary lung cancer. Eur Respir J 1996; 9(9): 1826–1830.

Long

Wang

Gao

, et al. Prognostic significance of pretreatment elevated platelet count in patients with colorectal cancer: a meta-analysis. Oncotarget 2016; 7(49): 81849–81861.

10.

Chen

, et al. Thrombocytosis is a significant indictor of hypercoagulability, prognosis and recurrence in gastric cancer. Exp Ther Med 2014; 8(1): 125–132.

11.

Zhou

Zhang

Tian

, et al. The critical role of platelet in cancer progression and metastasis. Eur J Med Res 2023; 28(1): 385.

12.

Scholz

Petru

Gücer

, et al. Preoperative thrombocytosis is an independent prognostic factor in stage III and IV endometrial cancer. Anticancer Res 2000; 20(5c): 3983–3985.

13.

Bussies

Eta

Pinto

, et al. Thrombocytosis as a biomarker in type II, non-endometrioid endometrial cancer. Cancers (Basel) 2020; 12(9): 2379.

14.

Ekici

Malatyalioglu

Kokcu

, et al. Do leukocyte and platelet counts have benefit for\preoperative evaluation of endometrial cancer? Asian Pac J Cancer Prev 2015; 16(13): 5305–5310.

15.

Xia

, et al. Pre-treatment thrombocytosis predicts prognosis of endometrial cancer: a meta-analysis of 11 studies. Exp Ther Med 2020; 19(1): 359–366.

16.

Gücer

Moser

Tamussino

, et al. Thrombocytosis as a prognostic factor in endometrial carcinoma. Gynecol Oncol 1998; 70(2): 210–214.

17.

Austin

PC.

A comparison of 12 algorithms for matching on the propensity score. Stat Med 2014; 33(6): 1057–1069.

18.

Austin

PC.

An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res 2011; 46(3): 399–424.

19.

Evstatiev

Bukaty

Jimenez

, et al. Iron deficiency alters megakaryopoiesis and platelet phenotype independent of thrombopoietin. Am J Hematol 2014; 89(5): 524–529.

20.

Kristine

Florentina

Aran

, et al. Iron deficiency-induced thrombocytosis increases thrombotic tendency in rats. Haematologica 2021; 106(3): 782–794.

21.

Takahashi

Mabuchi

Kuroda

, et al. The significance of pretreatment thrombocytosis and its association with neutrophilia in patients with surgically treated endometrial cancer. Int J Gynecol Cancer 2017; 27(7): 1399–1407.

22.

Nie

Yang

Pretreatment thrombocytosis predict poor prognosis in patients with endometrial carcinoma: a systematic review and meta-analysis. BMC Cancer 2019; 19(1): 73.

23.

Nakamura

Nakayama

Ishikawa

, et al. High pretreatment plasma D-dimer levels are related to shorter overall survival in endometrial carcinoma. Eur J Obstet Gynecol Reprod Biol 2016; 201: 89–93.

24.

Balescu

Bacalbasa

Brezean

, et al. The impact of thrombocytosis on the long term outcomes in relapsed ovarian cancer. Roman Med J 2023; 70: 5–7.

25.

Wang

Huang

, et al. Prognostic values of platelet-associated indicators in resectable cervical cancer. Dose Response 2019; 17(3): 1559325819874199.

26.

Bai

Jing

, et al. Clinicopathological and prognostic significance of pretreatment thrombocytosis in patients with endometrial cancer: a meta-analysis. Cancer Manag Res 2019; 11: 4283–4295.

27.

Sivaprasad

Sheela

SR.

Association of thrombocytosis and its prognostic significance in cervical cancer. J Clin Diagn Res 2023; 17(2): QC10–QC13.

28.

Crasta

Premlatha

Krishnan

, et al. Significance of preoperative thrombocytosis in epithelial ovarian cancer. Indian J Pathol Microbiol 2010; 53(1): 54–56.

29.

Zhang

, et al. The clinicopathological and prognostic role of thrombocytosis in patients with cancer: a meta-analysis. Oncol Lett 2017; 13(6): 5002–5008.

30.

Shu

Wang

, et al. Revisiting the association between pretreatment thrombocytosis and cancer survival outcomes: an umbrella review of meta-analyses. BMC Cancer 2024; 24(1): 1246.

31.

Haemmerle

Stone

Menter

, et al. The platelet lifeline to cancer: challenges and opportunities. Cancer Cell 2018; 33(6): 965–983.

32.

Liao

Zhang

Liu

, et al. The role of platelets in the regulation of tumor growth and metastasis: the mechanisms and targeted therapy. MedComm (2020) 2023; 4(5): e350.

33.

Plantureux

Mège

Crescence

, et al. Impacts of cancer on platelet production, activation and education and mechanisms of cancer-associated thrombosis. Cancers (Basel) 2018; 10(11): 441.

34.

Labelle

Begum

Hynes

RO.

Direct signaling between platelets and cancer cells induces an epithelial-mesenchymal-like transition and promotes metastasis. Cancer Cell 2011; 20(5): 576–590.

35.

Wojtukiewicz

Sierko

Hempel

, et al. Platelets and cancer angiogenesis nexus. Cancer Metastasis Rev 2017; 36(2): 249–262.

36.

Kitagawa

Yamamoto

, et al. Involvement of platelet membrane glycoprotein Ib and glycoprotein IIb/IIIa complex in thrombin-dependent and -independent platelet aggregations induced by tumor cells. Cancer Res 1989; 49(3): 537–541.

37.

Shawn LyBarger

Miller

Frieboes

. CA125 as a predictor of endometrial cancer lymphovascular space invasion and lymph node metastasis for risk stratification in the preoperative setting. Sci Rep 2022; 12(1): 19783.

38.

Lombaers

Cornel

KMC

Visser

NCM

, et al. Preoperative CA125 significantly improves risk stratification in high-grade endometrial cancer. Cancers (Basel) 2023; 15(9): 2605.

39.

Sun

Wei

Zou

, et al. Preoperative serum CA125 level and age at diagnosis: an effective prognosis prediction tool for patients with early-stage endometrial cancer. Asia Pac J Clin Oncol 2023; 19(5): e258–e266.

40.

Borgfeldt

Holmberg

Marcickiewicz

, et al. Survival in endometrial cancer in relation to minimally invasive surgery or open surgery - a Swedish Gynecologic Cancer Group (SweGCG) study. BMC Cancer 2021; 21(1): 658.

41.

Berek

Matias-Guiu

Creutzberg

, et al. FIGO staging of endometrial cancer: 2023. Int J Gynaecol Obstet 2023; 162(2): 383–394.

42.

Onstad

Schmandt

KH.

Addressing the role of obesity in endometrial cancer risk, prevention, and treatment. J Clin Oncol 2016; 34(35): 4225–4230.

43.

Gao

Dai

Chen

, et al. Body mass index is positively associated with endometrial cancer in chinese women, especially prior to menopause. J Cancer 2016; 7(9): 1169–1173.

44.

Miyata

Shirai

Muraki

, et al. Associations of body mass index, weight change, physical activity, and sedentary behavior with endometrial cancer risk among Japanese women: the Japan collaborative cohort study. J Epidemiol 2021; 31(12): 621–627.