Abstract
Background
Endometriosis (EMS) is a prevalent gynecological condition, and its diagnosis remains challenging. Hematological indicators such as platelet count (PLT), mean platelet volume (MPV), and platelet-to-lymphocyte ratio (PLR) have recently received attention for their potential diagnostic value in EMS.
Objective
To assess the association of PLT, MPV, and PLR in EMS by a meta-analysis.
Methods
We systematically searched Embase, PubMed, Cochrane Library, and Web of Science up to June 2025 for studies on the association of platelet-related parameters (PLT, MPV, and PLR) with EMS. Standardized mean difference (SMD) with 95% confidence interval (CI) was calculated for PLT, MPV, and PLR using a random-effects model. All statistical analyses were performed using Stata16.0.
Results
Nineteen studies with 5675 subjects were included. Overall pooled analyses showed no statistically significant differences in PLT (SMD 0.35 [− 0.02, 0.71], I²=97.6%, P = 0.063) and PLR (SMD 0.24 [− 0.16, 0.64], I²=96.6%, P = 0.224) between EMS and non-EMS populations. However, MPV was significantly elevated in EMS compared with non-EMS populations (SMD 0.30 [0.09, 0.52], I²=82.7%, P = 0.006). Subgroup analyses by control group type revealed context-dependent associations. Compared with benign gynecological conditions (e.g., ovarian cysts, uterine fibroids), EMS showed significantly elevated PLT (SMD 0.20 [0.01, 0.38], I²=53.7%, P = 0.042) and PLR (SMD 0.33 [0.22, 0.43], I²=0.0%, P < 0.01). PLT was significantly lower in EMS than in ovarian cancer (SMD − 0.56 [− 0.81, − 0.32], I²=0.0%, P < 0.001). MPV was significantly elevated in EMS compared with healthy individuals (SMD 0.46 [0.11, 0.81], I²=84.7%, P = 0.010), whereas no significant difference was observed between EMS and other benign gynecological conditions (SMD 0.04 [− 0.10, 0.19], I²=0.0%, P = 0.547).
Conclusion
MPV shows potential as an adjunctive marker for EMS, while PLT and PLR have limited independent diagnostic value but may be useful in specific clinical contexts.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1186/s12905-026-04630-9.
Keywords: Endometriosis, Mean platelet volume, Platelet-to-lymphocyte ratio, Platelet count, Meta-analysis
Introduction
Endometriosis (EMS) is a chronic inflammatory disease affecting approximately 10% of reproductive-age women, characterized by extrauterine growth of endometrial tissue [1, 2]. It is responsible for up to 30%-50% of unexplained infertility [1, 2]. Suspected EMS cases are typically diagnosed first by detailed history collection and gynecological examination. Transvaginal ultrasound and magnetic resonance imaging are the preferred imaging modalities [3]. Non-invasive biomarkers (e.g., CA-125) can serve as indicators for EMS diagnosis, but they are primarily used for monitoring treatment responses rather than independent diagnosis due to limited sensitivity and specificity [4]. Laparoscopy remains the golden standard for EMS diagnosis, but it is invasive and expensive. This underscores the urgent need for non-invasive diagnostic markers [5].
Obvious inflammatory responses (e.g., increases in pro-inflammatory factors and chemokines) and coagulation disorders (e.g., increases in plasma fibrinogen, D-dimer, plasminogen activator inhibitor-1, and von Willebrand factor, and shortening of thrombin time and activated partial thromboplastin time) have been recently found in EMS patients [6]. Platelets are not only a crucial component of the coagulation system but also key mediators of inflammatory responses [7, 8]. Multiple studies have revealed differences in platelet-related parameters (PLT/MPV/PLR) in EMS patients from healthy controls and patients with other gynecological diseases [9, 10]. This suggests that these parameters may serve as potential biomarkers for EMS diagnosis.
However, available study results are inconsistent. Bakri et al. argued that MPV is significantly elevated in EMS patients and can be used for EMS assessment [11]. Celik et al. found that PLT and PLR can serve as indicators for differential diagnosis of benign and malignant ovarian lesions, but their specificity is low in EMS diagnosis [12]. No systematic review has yet been conducted to assess the diagnostic value of these parameters. Therefore, this study intends to fully assess the association of platelet-related parameters with EMS by a meta-analysis. The findings are expected to present evidence-based guidance for clinical practice.
Methods
This study followed the PRISMA guidelines, and it was registered with PROSPERO (CRD420250652141).
Study search
We systematically searched PubMed, Embase, Cochrane Library, and Web of Science up to June 2025 for studies on the association of platelet-related parameters (PLT/MPV/PLR) with EMS. The search strategy combined medical subject headings (MeSH) with free-text terms using Boolean operators (AND, OR). The complete search string for PubMed was as follows:
(“Endometriosis“[Mesh] OR “Endometrioma“[Mesh] OR “adenomyosis externa“[Title/Abstract] OR “Endometrioses“[Title/Abstract] OR “Endometriosis“[Title/Abstract]) AND (“Platelet Count“[Mesh] OR “Mean Platelet Volume“[Mesh] OR “platelet-to-lymphocyte ratio“[Title/Abstract] OR “PLT“[Title/Abstract] OR “MPV“[Title/Abstract] OR “PLR“[Title/Abstract] OR “platelet“[Title/Abstract] OR “thrombocyte“[Title/Abstract] OR “mean thrombocyte volume“[Title/Abstract]).
The same search strategy was adapted for Embase, Cochrane Library, and Web of Science using their respective syntax and controlled vocabulary. The complete search strings for all databases are provided in Supplementary Table S1. Reference lists of the included studies were also manually checked to identify any additional eligible studies.
Eligibility criteria
Inclusion criteria: (1) Population: EMS patients; (2) Exposure: platelets and platelet-related parameters (PLT/MPV/PLR); (3) Comparison: non-EMS patients, healthy individuals, or other diseases; (4) Outcome: SMD of platelet-related parameters; and (5) Study design: case-control, cross-sectional, or cohort studies.
Exclusion criteria: (1) duplicate publications; (2) reviews, meta-analyses, conference abstracts, animal studies, or case reports; (3) non-English-language studies; (4) incomplete or non-extractable data; and (5) inappropriate study objective or outcomes.
Screening and data extraction
Two investigators (Qiu and Li) independently conducted initial study screening based on the above eligibility criteria, and cross-checked the included studies. Disagreement was settled by a third investigator (Wang). Subsequently, data (first author, publication year, study type, country, number of subjects, control group, and platelet-related parameters) were extracted.
Control groups were categorized into three types (Table 1), but none of the 19 studies explicitly excluded patients with coagulation disorders or anticoagulant use, which was a limitation we acknowledge.
Table 1.
General characteristics of studies included in the meta-analysis
| ID | Author | Year | Country | Study design | Total subjects | Age | Classification | Control group | Exposure |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Kalem | 2020 | Turkey | Case-control | 213 | 29.84 ± 4.61 | NR | Benign ovarian mass | PLT, MPV, PLR |
| 2 | Özlem Kayacık Günday | 2024 | Turkey | Case-control | 267 | 34.43 ± 6.85 | NR | Infertility, chronic pelvic pain, bilateral tubal ligation, simple ovarian cyst, healthy individuals | PLT, MPV |
| 3 | Turgut | 2019 | Turkey | Case-control | 257 | 36.67 ± 6.56 | Grade 1–4 | Healthy women | PLT, MPV |
| 4 | Paola Vigano | 2018 | Italy | Cross-sectional | 314 | 36.34 ± 6.20 | Grade 1–4, lesion location | Benign ovarian mass | PLT, PLR |
| 5 | Roya Kabodmehri | 2024 | Iran | Case-control | 74 | 35.61 ± 5.13 | NR | Women with male-factor infertility, normal ultrasound findings, and no signs of EMS or other infertility-related conditions | PLR |
| 6 | Ashraf Moini | 2021 | Germany | Case-control | 321 | 32.50 ± 7.02 | Grade 1–4, lesion location | Healthy women | PLT PLR MPV |
| 7 | Zhou | 2025 | China | Case-control | 951 | 36 ± 6.40 | NR | Healthy women | PLT |
| 8 | Ml Vâvuzcan | 2013 | Turkey | Case-control | 94 | 36.21 ± 8.37 | Grade 3–4 | Healthy women, benign ovarian mass | PLT, MPV, PLR |
| 9 | Coskun | 2019 | Turkey | Case-control | 274 | 41.53 ± 10.43 | NR | Healthy women, adenomyosis | PLT, MPV |
| 10 | F. Celik | 2017 | Turkey | Case-control | 200 | 41.7 ± 15.1 | NR | Ovarian cancer (OC), benign ovarian tumor | PLT PLR |
| 11 | Evsen | 2014 | Turkey | Case-control | 108 | 28.94 ± 4.75 | Lesion location | Healthy women | PLT |
| 12 | Ding | 2019 | China | Case-control | 548 | 35.80 ± 0.43 | Grade 3–4 | Benign ovarian tumor, healthy women | PLT PLR |
| 13 | Bakir | 2016 | Turkey | Case-control | 333 | 33.21 ± 4.70 | Grade 1–4 | Healthy women | MPV |
| 14 | Yang | 2015 | China | Retrospective | 411 | 32.58 ± 6.37 | Grade 1–4 | Benign ovarian tumor, healthy women | PLT PLR |
| 15 | Guo | 2022 | China | Case-control | 272 | 31.02 ± 8.09 | Grade 1–4 | Benign ovarian tumor | PLT PLR |
| 16 | Gorun | 2024 | Romania | Cross-sectional | 207 | 33.07 ± 5.83 | NR | NR | PLT PLR |
| 17 | Sabra | 2024 | Egypt | Prospective | 88 | 32.83 ± 4.40 | NR | Healthy women | PLT PLR |
| 18 | Seckin | 2018 | Turkey | Case-control | 502 | 27.1 ± 7.2 | NR | Benign ovarian tumor | PLT PLR MPV |
| 19 | Chen | 2019 | China | Case-control | 241 | 38.35 ± 10.41 | Grade 3–4 | OC | PLT PLR |
We did not contact research groups or authors to obtain unpublished manuscripts or full texts that were not available by the search engines, as all included studies were peer-reviewed publications with available full text.
Quality assessment
Case-control studies were assessed for quality by the Newcastle-Ottawa Scale (NOS) from three domains: selection (four stars), comparability (two stars), and exposure (three stars), with a total of nine stars [13]. The JBI Scale was utilized for cross-sectional studies. Each study was assessed as low, moderate, or high risk of bias [14].
Statistical analysis
All analyses were performed using Stata16.0. SMDs with 95% CIs were used as the effect measure. Since the included studies reported platelet-related parameters using different units (e.g., 10⁹/L vs. L vs.r different methods, SMD was chosen to standardize effect sizes across studies. Heterogeneity was assessed using the Ids, atistic, which represents the percentage of total variability across studies that is due to between-study heterogeneity rather than chance. A random-effects model was selected a priori, as the true effect size was likely to vary across studies due to differences in EMS stage, phenotype, and control group type. To explore potential sources of heterogeneity, subgroup analyses were conducted by control group type. Leave-one-out sensitivity analyses were performed to evaluate the influence of each individual study on the pooled effect size by sequentially omitting one study at a time and recalculating the overall effect estimate. Publication bias was assessed using Egger’s test, with P < 0.05 deemed statistically significant.
Results
Search results
We initially retrieved 750 relevant studies. After duplicate removal, the remaining 457 studies were screened for the title and abstract, of which 430 were excluded. Then the remainder was examined for the full text. Finally, 19 studies were included (Fig. 1).
Fig. 1.
Identification of studies via databases and registers
Study characteristics
The included studies were published from 2013 to 2025. Five studies originated from China, nine from Turkey, and one each from Egypt, Germany, Romania, Iran, and Italy. They consisted of 15 case-control studies, two cross-sectional studies, one prospective study, and one retrospective study, involving 5675 subjects (Table 1) [10–12, 15–30].
Quality assessment
The 15 case-control studies, one prospective study, and one retrospective study were assessed for quality using the NOS from three domains: selection (four stars), comparability (two stars), and exposure/outcome (three stars), with a total of nine stars. The results showed that 16 studies were rated as high quality (NOS ≥ 7), one as moderate quality (NOS = 6), and one as low quality (NOS = 5). Besides, the two cross-sectional studies were assessed using the JBI Scale, both of which were rated as high quality.
Meta-analysis results
Association between PLT and EMS
Seventeen studies were included, displaying great heterogeneity (I²=97.6%, P < 0.001). The random-effects model revealed no statistically significant difference in PLT between EMS and non-EMS populations (SMD 0.35 [-0.02, 0.71], P = 0.063) (Fig. 2). One study (Ding et al., 2019) reported a significantly larger effect size than other studies. After excluding this study, the sensitivity analysis revealed a pooled SMD of 0.04 [− 0.10, 0.19] (I²=82.7%, P = 0.575), suggesting that the overall conclusion that “no significant difference was observed between the two groups” remained valid (Fig. S1).
Fig. 2.
Forest plot of PLT levels in endometriosis patients vs. Controls
We conducted subgroup analyses by control group type and country due to great heterogeneity (I²=97.6%). PLT was elevated in EMS compared with healthy individuals, with no statistically significant difference (SMD 0.51 [-0.12, 1.13], I²=98.1%, P = 0.111). PLT significantly increased in EMS compared with benign gynecological conditions (SMD 0.20 [0.01, 0.38], I²=53.7%, P = 0.042), showing moderate intra-group heterogeneity. PLT significantly decreased in EMS compared with ovarian cancer (OC) (SMD − 0.56 [-0.81, -0.32], I²=0.0%, P = 0.000), showing no intra-group heterogeneity. This suggests that the control group type was a potential source of overall heterogeneity (Fig. 3).
Fig. 3.
Subgroup analysis of PLT levels by control group type
Sensitivity analysis
The leave-one-out sensitivity analysis revealed that the pooled effect size remained within the overall 95% CI, indicating the robustness of results (Fig. 4).
Fig. 4.
Sensitivity analysis of PLT levels by omitting each study
Publication bias
The funnel plot was roughly symmetric (Fig. 5), and the Egger’s test also revealed no obvious publication bias (t=-0.06, P = 0.957 > 0.05).
Fig. 5.
Funnel plot for publication bias of PLT levels
Association between PLR and EMS
Thirteen studies were included, displaying great heterogeneity (I²=96.6%, P < 0.001). The random-effects model revealed no statistically significant difference in PLR between EMS and non-EMS populations (SMD 0.24 [− 0.16, 0.64], P = 0.224) (Fig. 6).
Fig. 6.
Forest plot of PLR levels in endometriosis patients vs. controls
After excluding the study by Ding et al. (2019), the sensitivity analysis yielded a pooled SMD of 0.07 [-0.12, 0.27] (I²=84.5%, P = 0.460), confirming that the exclusion did not alter the qualitative conclusion (Fig. S2).
We conducted subgroup analyses by control group type and country due to great heterogeneity (I²=96.6%). PLR was elevated in EMS compared with healthy individuals (SMD 0.10 [-0.26, 0.45], I²=69.0%, P = 0.596), with no statistically significant difference but moderate intra-group heterogeneity. PLR significantly increased in EMS compared with benign gynecological conditions (SMD 0.33 [0.22, 0.43], I²=0.0%, P < 0.01), showing no intra-group heterogeneity. This suggests that the control group type was a potential source of heterogeneity (Fig. 7).
Fig. 7.
Subgroup analysis of PLR levels by country
Sensitivity analysis
The leave-one-out sensitivity analysis revealed that the pooled effect size remained within the overall 95% CI, indicating the robustness of results (Fig. 8).
Fig. 8.
Sensitivity analysis of PLR levels by omitting each study
Publication bias
The funnel plot was roughly symmetric, and the Egger’s test also revealed no obvious publication bias (P = 0.409 > 0.05) (Fig. 9).
Fig. 9.
Funnel plot for publication bias of PLR levels
Association between MPV and EMS
Eight studies were included, displaying great heterogeneity (I²=82.7%, P < 0.001). The random-effects model revealed elevated MPV in EMS compared with non-EMS populations (SMD 0.30 [0.09, 0.52], P = 0.006), with a statistically significant difference (Fig. 10).
Fig. 10.
Forest plot of MPV levels in endometriosis patients vs. Controls
We conducted subgroup analyses by control group type and country due to great heterogeneity (I²=82.7%). MPV was elevated in EMS compared with healthy individuals (SMD 0.46 [0.11, 0.81], I²=84.7%, P = 0.010), with a statistically significant difference and high heterogeneity. MPV increased in EMS compared with benign gynecological conditions (SMD 0.04 [-0.10, 0.19], I²=0.0%, P = 0.547), with no statistically significant difference and no intra-group heterogeneity. This suggests that the control group type was a potential source of overall heterogeneity (Fig. 11).
Fig. 11.
Subgroup analysis of MPV levels by control group type
Sensitivity analysis
The leave-one-out sensitivity analysis revealed that the pooled effect size remained within the overall 95% CI, indicating the robustness of results (Fig. 12).
Fig. 12.
Sensitivity analysis of MPV levels by omitting each study
Publication bias
The funnel plot was roughly symmetric, and the Egger’s test also revealed no obvious publication bias (t = 0.58, P = 0.575 > 0.05) (Fig. 13).
Fig. 13.
Funnel plot for publication bias of MPV levels
Discussion
This meta-analysis fully assessed changes in PLT, MPV, and PLR in EMS. The results showed that MPV was obviously elevated in EMS compared with the control (SMD 0.30, P = 0.006), while PLT and PLR had no statistically significant differences. However, subgroup analyses revealed significant context dependency in these differences. Specifically, PLT and PLR were obviously elevated in EMS compared with other benign gynecological conditions, PLT obviously decreased in EMS compared with OC, and MPV increased compared with healthy individuals.
Biological interpretation of platelet parameters in EMS
The overall analysis identified MPV as the only platelet parameter consistently associated with EMS. The association of MPV with thrombotic and inflammatory diseases has been established [31]. EMS is inherently a chronic inflammatory disease characterized by complex local inflammatory cascades in the lesion. In this inflammatory microenvironment, dynamics of megakaryocytes for generating platelets are altered [31, 32], and they tend to produce larger, younger platelets with enhanced metabolic activity and pro-inflammatory capacity [8, 31]. Large platelets contain more dense granules and can release higher concentrations of key mediators (e.g., vascular endothelial growth factor, platelet-derived growth factor, transforming growth factor-β). These mediators are involved in the implantation, survival, and growth of ectopic endometrial tissue by promoting angiogenesis, cell proliferation, and immunomodulation [33]. Therefore, EMS itself may elevate MPV [31].
However, MPV elevation is not specific to EMS. The subgroup analysis revealed that MPV was obviously elevated in EMS only compared with healthy individuals, while it had no significant difference compared with benign gynecological conditions (e.g., ovarian cysts, uterine fibroids). This suggests that MPV may be a nonspecific rather than a specific marker for EMS. In other words, MPV can help distinguish “presence of inflammation” from “absence of inflammation” but is less effective in differentiating “EMS-associated inflammation” and “inflammation associated with other benign conditions”.
The overall association of PLT and PLR with EMS did not reach statistical significance, but the subgroup analysis revealed that PLT obviously decreased compared with OC. This suggests that platelet consumption or production mechanisms differ between malignancies and benign inflammatory diseases [34]. PLT contributes to tumor growth, invasion, and metastasis via physical protection, anti-apoptosis, angiogenesis promotion, immunosuppression, and signal regulation [35]. As a malignancy, OC is often closely associated with platelets during development, progression, and metastasis [36]. Research suggests that thrombocytosis, defined as PLT > 400 × 10⁹/L (or 300–450 × 10⁹/L as the cutoff in some studies), pre-diagnosis or pre-treatment in OC patients is closely linked to unfavorable progression-free survival and overall survival [36]. Ronsini et al. found in 163 patients with stage I endometrial cancer that PLR correlated with myometrial infiltration and LVSI (P < 0.05), suggesting its prognostic value in malignancy. In contrast, this study found only a moderate elevation of PLR in EMS (SMD 0.33) in specific subgroup comparisons [37]. However, we should interpret this finding with caution. This conclusion was drawn from only two studies, which inherently restricted statistical power and robustness of the pooled estimate.
We observed no statistically significant difference in PLT between EMS and healthy individuals. PLT remains stable in healthy individuals, while EMS, a localized chronic inflammation with systemic burden, may be insufficient to induce great PLT changes in all patients [38]. Therefore, PLT alone lacks sensitivity in distinguishing EMS and healthy status.
PLT and PLR were obviously elevated in EMS compared with other benign gynecological conditions (e.g., ovarian cysts, uterine fibroids). PLR fundamentally reflects the equilibrium between coagulation/inflammation (represented by platelets) and immunoregulation (represented by lymphocytes). This indicates that PLR (integrating both platelets and lymphocytes) may be more specific than PLT alone in distinguishing EMS and other benign gynecological conditions accompanied by chronic inflammation [28, 39].
Comparison with previous systematic reviews and progress
A previous retrospective study [40] reported elevated PLT in EMS but inadequately considered the influence of heterogeneity and the control group. By a more comprehensive study search and rigorous subgroup analyses, this study clarified that PLT elevation was not a universal phenomenon, and it was elevated when compared to specific diseases. More importantly, this meta-analysis was the first to explicitly highlight the potential association of MPV with EMS and reveal the value of PLR in specific scenarios. This constitutes an important supplement to current knowledge.
The high heterogeneity observed (I²>80%) was objectively present and stemmed from multiple sources
Heterogeneity in disease phenotype
EMS is highly heterogeneous according to rASRM stage (I-IV) and phenotypes (peritoneal, ovarian, deep infiltrating). Patients may greatly vary in disease severity and type across studies. For instance, evidence suggests that systemic inflammatory markers (including PLR) may be significantly higher in deep infiltrating EMS than in other phenotypes [41], and they are highly correlated with pelvic adhesions.
Clinical heterogeneity in the control group
This study identified the control group as the main source of heterogeneity. EMS exhibited distinct biological differences compared with healthy populations and other pelvic diseases (e.g., chronic pelvic inflammation, adnexal masses) [2, 42].
Methodological and regional variations
Due to variations in blood sample processing time, anticoagulant use, and instrument standardization across study sites [43], measurement variability occurred. Furthermore, the PLT heterogeneity observed in China may be related to differences in genetic background, environmental factors, or disease spectrum. They warrant further investigation as stratification variables in future research [44].
Clinical implications and limitations
Our findings offer new insights for the clinical management of EMS. As routine parameters in complete blood counts, MPV and PLR have low cost, non-invasiveness, and reproducibility. While insufficient as independent diagnostic tools, they can be integrated into multimodal diagnostic models as “risk reminders”. For example, abnormalities of MPV or PLR may more strongly indicate EMS in patients presenting with symptoms (e.g., dysmenorrhea, infertility) but atypical imaging findings. In this way, more proactive recommendations for laparoscopic exploration can be given.
This meta-analysis has several methodological features worth noting. It is the first meta-analysis to systematically evaluate PLT, MPV, and PLR in EMS, involving 19 studies with 5675 subjects. Subgroup analyses were performed by control group type (healthy, benign gynecological conditions, ovarian cancer). This study followed PRISMA guidelines, was registered with PROSPERO, and searched four databases with manual reference checking. Quality was assessed using NOS and JBI Scales. Random-effects models, sensitivity analyses, and Egger’s test were utilized.
Some limitations are worth noting in this study. First, causal inference was precluded due to the observational nature of the included studies. Second, although substantial heterogeneity (I²>80%) was observed, we could not perform subgroup analyses by rASRM stage or disease phenotype (peritoneal, ovarian, deep infiltrating), because the original studies did not report platelet-related parameters stratified by these clinical characteristics. This potentially contributed to residual heterogeneity. Third, NLR and MLR were not included in this meta-analysis due to insufficient data. Only a minority of the retrieved studies reported these indices, and among those, most lacked extractable data (e.g., mean, SD, or group sample sizes) required for calculating SMD. Fourth, although formal tests revealed non-significant publication bias, the possibility of unpublished negative results cannot be entirely ruled out. Fifth, our analysis was based on aggregate-level data extracted from published studies, which precluded the use of individual patient data. This prevented us from performing patient-level adjustments for potential confounders, such as age, hormone use, or disease severity, and restricted our ability to explore more granular dose-response relationships. Sixth, the failure to assess the influence of EMS stage on platelet-related parameters represents a key knowledge gap. Although the rASRM staging system is central to the clinical characterization of EMS, only a subset of the included studies reported platelet-related parameters stratified by rASRM stage. This precluded a formal subgroup analysis by disease severity, which remained an important source of heterogeneity and limited the clinical applicability of our findings. Finally, standardization of MPV measurement is known to be critically instrument-dependent. Variability in the time from venipuncture to analysis, the type of anticoagulant used will affect the results of MPV measurement.
Additionally, this meta-analysis did not evaluate diagnostic accuracy measures such as sensitivity, specificity, or area under the curve, because they were not reported in the included studies. Therefore, our findings should be interpreted as intergroup associations or differences in platelet-related parameters, rather than diagnostic performance.
Conclusion
In conclusion, MPV shows potential as an adjunctive marker for EMS, while PLT and PLR have limited independent diagnostic value but may be useful in specific clinical contexts. Subgroup analyses revealed that PLT and PLR were higher in EMS than in other benign gynecological conditions, but these effect sizes were small (PLT: SMD 0.20) and no diagnostic accuracy data were available. Prospective, large-cohort, multicenter studies are required in the future to assess the expression differences of these parameters across EMS phenotypes (particularly deep infiltrating endometriosis) under standardized preprocessing. Additionally, their combined diagnostic efficacy with CA-125 and imaging can be explored to create an efficient, non-invasive tool for auxiliary diagnosis and stratification of EMS.
Supplementary Information
Acknowledgements
Not applicable.
Abbreviations
- EMS
Endometriosis
- PLT
Platelet count
- MPV
Mean platelet volume
- PLR
Platelet-to-lymphocyte ratio
- SMD
Standardized mean difference
- NOS
Newcastle-Ottawa Scale
Authors’ contributions
All authors contributed to the study conception and design. Writing - original draft preparation: [Jincheng Qiu]; Writing - review and editing: [Jincheng Qiu]; Conceptualization: [Jiayi Li]; Methodology: [Kaiqing Lin]; Formal analysis and investigation: [Anya Wang]; Supervision: [Kaiqing Lin], and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Funding
The authors declare that they did not receive any funding from any source.
Data availability
All data generated or analysed during this study are included in this published article and its supplementary information files.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Data Availability Statement
All data generated or analysed during this study are included in this published article and its supplementary information files.