Abstract
Objectives
The objective of this study was to explore the lymph node metastasis (LNM) and related risk factors of low-grade endometrioid endometrial carcinomas (EECs) and analyse the efficacy of related risk factors in predicting LNM.
Design
Data from 424 patients with low-grade EEC treated between January 2019 and June 2024 were retrospectively analysed, according to the International Federation of Gynecology and Obstetrics (FIGO) 2009.
Methods
Univariate and multivariate logistic regression analyses were used to examine the factors associated with LNM. Receiver operating characteristic (ROC) curves were plotted to assess the predictive efficacy of independent risk factors for LNM.
Results
The rate of LNM was 7.8% (33/424). Histological grade, tumour size, depth of myometrial invasion, cervical stromal invasion, lymphovascular space invasion (LVSI), microcystic, elongated, fragmented (MELF) pattern, carbohydrate antigen 125 (CA125), carbohydrate antigen 199, and human epididymis protein 4 were associated with LNM. However, only LVSI, MELF pattern, depth of myometrial invasion, and CA125 were identified as independent risk factors. The area under the ROC curve for CA125 and depth of myometrial invasion was 0.796 and 0.734, respectively. The optimal cut-off value for CA125 was 31.36 U/mL, with a maximum Youden index of 53.9%. Combining CA125 with depth of myometrial invasion improved diagnostic accuracy compared to either parameter alone.
Limitations
This is a single-center retrospective study.
Conclusions
LNM is more likely with independent risk factors. Combining CA125 and depth of myometrial invasion enhances diagnostic accuracy for LNM. This study provides valuable insights for predicting LNM risk in low-grade EEC patients and guiding stratified management.
Keywords: Low-grade endometrioid endometrial carcinomas, Lymph node metastasis, Risk factors, Predicting lymph node metastasis
Introduction
Endometrial cancer (EC) is one of the most common gynaecological malignancies worldwide, ranking seventh among all female cancers, with a higher prevalence in middle-aged and elderly women [1]. Endometrioid endometrial carcinoma (EEC) represents the most frequent histopathological subtype of EC and is classified into low-grade (G1 and G2) and high-grade (G3) categories based on a binary grading system recommended by the International Association of Gynaecological Pathologists [2] and the World Health Organization (WHO) Classification of Female Genital Tumours 2020 [3].
High-grade EC, encompassing grade 3 EEC (G3 EEC) and non-endometrioid subtypes (including serous, clear cell, carcinosarcoma, and undifferentiated carcinoma), constitutes a group of aggressive malignancies characterized by elevated risks of lymph node metastasis (LNM) and disease recurrence [4]. Current guidelines recommend systematic lymphadenectomy (pelvic ± para-aortic) for accurate staging of these high-risk tumours [5].
In contrast, low-grade EEC demonstrates fundamentally different biological behaviour with substantially lower LNM potential. NCCN guidelines endorse sentinel lymph node (SLN) biopsy for low-grade EEC [5], while clinical implementation faces challenges. Many institutions continue to perform routine systematic lymphadenectomy for all cases due to concerns regarding incomplete staging, recurrence risk, and technical difficulties associated with SLN biopsy, potentially resulting in overtreatment [6]. This practice persists despite large-scale analyses demonstrating no significant overall survival benefit from lymph node resection in early-stage EC [7].
The development of reliable risk stratification systems for LNM could optimize treatment individualization and prevent unnecessary lymph node dissection [8]. However, current risk prediction models lack consensus [9]. Consequently, refining LNM risk stratification for low-risk patients remains a critical research priority [9–11], underscoring the need for larger-scale studies to establish evidence-based management strategies. In this context, our study retrospectively analysed the medical records of 424 patients with low-grade EEC treated in our hospital, aiming to provide insights into the risk factors and hierarchical management of LNM in low-grade EEC patients.
Materials and Methods
The clinical data of patients with low-grade EEC who underwent surgery in the Department of Gynaecology at the Affiliated Hospital of Xuzhou Medical University between January 2019 and June 2024 were retrospectively analysed.
Inclusion Criteria
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1.
Surgical treatment at our hospital, including hysterectomy, bilateral salpingo-oophorectomy, and pelvic and para-aortic lymph node resection.
-
2.
Pathologically confirmed low-grade EEC (grade 1 or grade 2, G1–G2).
-
3.
Complete clinical data.
-
4.
Complete peripheral blood data, including preoperative blood routine and tumour markers: carbohydrate antigen 125 (CA125), carbohydrate antigen 199 (CA199), carcinoembryonic antigen (CEA), alpha-fetoprotein (AFP), and human epididymis protein 4 (HE4).
Exclusion Criteria
-
1.
Special pathological types, grade 3 tumours, secondary malignant tumours, or the presence of other synchronous malignancies.
-
2.
Preoperative adjuvant therapy (e.g., radiotherapy, chemotherapy, or hormone therapy).
-
3.
Comorbid infectious diseases.
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4.
Low-grade EEC patients who did not undergo lymphadenectomy or had incomplete medical records.
Patient data were collected by reviewing medical records, operation notes, preoperative laboratory results, and postoperative pathological reports. The clinicopathological characteristics recorded included age at surgery (years), body mass index (BMI, kg/m2), reproductive history, menopausal status, tubal ligation, hypertension, diabetes, uterine leiomyoma, histological grade (G1 or G2), International Federation of Gynaecology and Obstetrics (FIGO) 2009 stage, tumour size (<2 cm or ≥2 cm), depth of myometrial invasion (postoperative histopathology, <50% or ≥50%), serosal/adnexal invasion, cervical stromal invasion, lymphovascular space invasion (LVSI), microcystic, elongated, and fragmented (MELF) invasion pattern, and LNM.
Preoperative laboratory results collected included: serum levels of CA125 (U/mL), CA199 (U/mL), CEA (ng/mL), AFP (ng/mL), and HE4 (pmol/L), as well as absolute neutrophil count (ANC, 109/L), absolute lymphocyte count (ALC, 109/L), absolute monocyte count (AMC, 109/L), and platelet count (PLT, 109/L). Additionally, the neutrophil-to-lymphocyte ratio (NLR = ANC/ALC), platelet-to-lymphocyte ratio (PLR = PLT/ALC), and monocyte-to-lymphocyte ratio (MLR = AMC/ALC) were calculated and recorded. Surgical pathological staging was performed according to the FIGO 2009 criteria [12].
Statistical Analysis
Statistical analyses were performed using the SPSS 23.0 software package (IBM Corp., Armonk, NY, USA). In univariate analysis, the Mann-Whitney U test was used for continuous variables (as they were not normally distributed), while the chi-square or Fisher’s exact tests were applied for categorical variables. Variables with a p value <0.05 in the univariate analysis were included in the multivariate analysis. Multivariable logistic regression analysis was used to identify independent risk factors. Receiver operating characteristic (ROC) curves were generated using SPSS software, and the predictive ability of relevant independent risk factors for LNM in EEC patients – either alone or in combination – was analysed by calculating and comparing the differences in the area under the curve.
Results
General Situation
A total of 424 subjects met the inclusion criteria and were enrolled in the study. According to the FIGO 2009 staging criteria, 305 cases (71.9%) were classified as stage IA, 51 cases (12.0%) as stage IB, and 21 cases (5.0%) as stage II. Additionally, 45 cases (10.6%) were classified as stage III, including 12 cases (2.8%) in stage IIIA and 33 cases (7.8%) in stage IIIC. Two cases (0.5%) were classified as stage IV (note: neither of these patients had LNM, but both exhibited fallopian tube and omental metastases).
Based on the final pathological results, patients were divided into two groups: the LNM group (positive group) and the lymph node non-metastasis group (negative group). The positive group comprised 33 cases (33/424, 7.8%), while the negative group included 391 cases (391/424, 92.2%). The median age in the positive group was 56 years (range: 38–79 years), compared to 55 years (range: 24–84 years) in the negative group.
In the positive group, the median number of lymph nodes removed was 10 (range: 5–23) in the left pelvic cavity, 10 (range: 5–28) in the right pelvic cavity, and 5 (range: 1–27) in the para-aortic region. In the negative group, the median number of lymph nodes removed was 9 (range: 1–34) in the left pelvic cavity, 8 (range: 1–27) in the right pelvic cavity, and 5 (range: 1–20) in the para-aortic region. No significant difference was observed between the two groups (p > 0.05).
Among the 33 patients with LNM, the frequency and number of metastatic lymph nodes were as follows: the left pelvic lymph node region was involved in 20 cases (range: 1–4), the right pelvic lymph node region in 19 cases (range: 1–9), and the para-aortic region in 13 cases (range: 1–7). Notably, 3 patients exhibited isolated para-aortic LNM (without pelvic lymph node involvement). The clinical and pathological characteristics of the 424 low-grade EEC patients are summarized in Table 1, and the peripheral blood data are presented in Table 3.
Table 1.
Clinical and pathological characteristics of 424 EEC patients
| Variable | Patients, n | % |
|---|---|---|
| Age | ||
| ≥60 years | 117 | 27.6 |
| <60 years | 307 | 72.4 |
| BMI | ||
| ≥25 kg/m2 | 248 | 58.49 |
| <25 kg/m2 | 176 | 41.51 |
| Menopause | ||
| Yes | 326 | 76.89 |
| No | 98 | 23.11 |
| Tubal ligation | ||
| Yes | 41 | 9.7 |
| No | 383 | 90.3 |
| Live birth | ||
| Yes | 413 | 97.41 |
| No | 11 | 2.59 |
| Hypertension | ||
| Yes | 166 | 39.2 |
| No | 258 | 60.8 |
| Diabetes | ||
| Yes | 89 | 21.0 |
| No | 335 | 79.0 |
| Uterine leiomyoma | ||
| Yes | 198 | 46.7 |
| No | 226 | 53.3 |
| Histologic grading | ||
| G2 | 181 | 42.7 |
| G1 | 243 | 57.3 |
| LVSI | ||
| Positive | 35 | 8.3 |
| Negative | 389 | 91.7 |
| MELF | ||
| Yes | 16 | 3.8 |
| No | 408 | 96.2 |
| Tumour size | ||
| ≥2 cm | 173 | 40.8 |
| <2 cm | 251 | 59.2 |
| Myometrial invasion | ||
| ≥50% | 87 | 20.5 |
| <50% | 337 | 79.5 |
| Cervical stromal | ||
| Yes | 31 | 7.3 |
| No | 393 | 92.7 |
| Serous layer/adnexa | ||
| Yes | 16 | 3.8 |
| No | 408 | 96.2 |
| LNM | ||
| Yes | 33 | 7.8 |
| No | 391 | 92.2 |
BMI, body mass index; LVSI, lymphovascular space invasion; MELF, microcystic, elongated, fragmented; LNM, lymph node metastasis.
Table 3.
Peripheral blood data and univariate analysis
| Factors | Scope | Median (P25–P75) | Positive, median (P25–P75) | Negative, median (P25–P75) | Z | p value |
|---|---|---|---|---|---|---|
| NLR | 0.59–21.26 | 2.07 (1.57–2.79) | 1.82 (1.56–2.64) | 2.08 (1.57–2.80) | −0.831 | 0.406 |
| PLR | 42.86–581.67 | 148.50 (117.16–193.05) | 151.82 (100.95–196.00) | 146.47 (117.36–190.96) | −0.382 | 0.702 |
| MLR | 0.04–1.00 | 0.18 (0.14–0.23) | 0.17 (0.13–0.22) | 0.18 (0.14–0.23) | −0.360 | 0.719 |
| CA125 | 3.57–535.00 | 15.64 (11.60–25.10) | 37.59 (17.62–66.68) | 15.23 (11.32–23.70) | 5.646 | <0.001 |
| CA199 | 0.60–547.80 | 13.30 (8.21–24.04) | 24.38 (8.71–93.20) | 13.20 (8.20–22.77) | 2.535 | 0.011 |
| CEA | 0.20–36.70 | 1.70 (1.19–2.58) | 1.94 (1.31–2.96) | 1.70 (1.18–2.54) | 1.136 | 0.256 |
| AFP | 0.88–9.98 | 3.02 (2.10–3.92) | 3.03 (1.83–3.36) | 3.00 (2.11–3.97) | −0.953 | 0.341 |
| HE4 | 25.94–1,242.00 | 60.75 (49.21–79.08) | 69.60 (57.91–91.19) | 60.20 (48.45–76.81) | 2.560 | 0.010 |
Did not conform to the normal distribution and were expressed as median (P25–P75).
NLR, neutrophil to lymphocyte ratio; PLR, platelet to lymphocyte ratio; MLR, monocyte to lymphocyte ratio.
Univariate Analysis of Clinicopathological Parameters
Univariate analysis revealed that histological grade, tumour size, depth of myometrial invasion, cervical stromal invasion, LVSI, and MELF invasion pattern were significantly associated with LNM in low-grade EEC patients (p < 0.05) (Table 2).
Table 2.
Univariate analysis of clinicopathological parameters
| Risk factors | LNM, n (%) | χ2 | p value | |
|---|---|---|---|---|
| positive (n = 33) | negative (n = 391) | |||
| Age | ||||
| ≥60 years | 12 (10.3) | 105 (89.7) | 1.377 | 0.241 |
| <60 years | 21 (6.8) | 286 (93.2) | ||
| BMI | ||||
| ≥25 kg/m2 | 14 (5.6) | 234 (94.4) | 3.805 | 0.051 |
| <25 kg/m2 | 19 (10.8) | 157 (89.2) | ||
| Menopause | ||||
| Yes | 26 (8.0) | 300 (92.0) | 0.073 | 0.787 |
| No | 7 (7.1) | 91 (92.9) | ||
| Tubal ligation | ||||
| Yes | 4 (9.8) | 37 (90.2) | 0.036 | 0.850 |
| No | 29 (7.6) | 354 (92.4) | ||
| Live birth | ||||
| Yes | 31 (7.5) | 382 (92.5) | 0.539 | 0.463 |
| No | 2 (18.2) | 9 (81.8) | ||
| Hypertension | ||||
| Yes | 9 (5.4) | 157 (94.6) | 2.119 | 0.145 |
| No | 24 (9.3) | 234 (90.7) | ||
| Diabetes | ||||
| Yes | 8 (9.0) | 81 (91.0) | 0.228 | 0.633 |
| No | 25 (7.5) | 310 (92.5) | ||
| Uterine leiomyoma | ||||
| Yes | 16 (8.1) | 182 (91.9) | 0.046 | 0.830 |
| No | 17 (7.5) | 209 (92.5) | ||
| Histologic grading | ||||
| G2 | 21 (11.6) | 160 (88.4) | 6.418 | 0.011 |
| G1 | 12 (4.9) | 231 (95.1) | ||
| LVSI | ||||
| Positive | 19 (54.3) | 16 (45.7) | 107.989 | <0.001 |
| Negative | 14 (3.6) | 375 (96.4) | ||
| MELF | ||||
| Yes | 13 (81.2) | 3 (18.8) | 114.629 | <0.001 |
| No | 20 (4.9) | 388 (95.1) | ||
| Tumour size | ||||
| ≥2 cm | 21 (12.1) | 152 (87.9) | 7.725 | 0.005 |
| <2 cm | 12 (4.8) | 239 (95.2) | ||
| Myometrial invasion | ||||
| ≥50% | 21 (24.1) | 66 (75.9) | 40.794 | <0.001 |
| <50% | 12 (3.6) | 325 (96.4) | ||
| Cervical stromal | ||||
| Yes | 6 (19.4) | 25 (80.6) | 4.622 | 0.032 |
| No | 27 (6.9) | 366 (93.1) | ||
| Serous layer/adnexa | ||||
| Yes | 3 (18.8) | 13 (81.2) | 1.425 | 0.233 |
| No | 30 (7.4) | 378 (92.6) | ||
BMI, body mass index; LVSI, lymphovascular space invasion; MELF, microcystic, elongated, fragmented; LNM, lymph node metastasis.
Univariate Analysis of Peripheral Blood Indicators
Univariate analysis of preoperative peripheral blood indicators demonstrated that CA125, CA199, and HE4 were significantly associated with LNM (p < 0.05). In contrast, NLR, PLR, MLR, CEA, and AFP showed no significant association with LNM (Table 3).
Multivariate Logistic Regression Analysis of Risk Factors for LNM in Low-Grade EEC Patients
Multivariate logistic regression analysis identified LVSI, MELF invasion pattern, depth of myometrial invasion, and CA125 as independent risk factors for LNM (odds ratio >1, p < 0.05) (Table 4).
Table 4.
Logistic regression analysis of risk factors for LNM
| Factors | β | SE | Wald | p value | OR | OR (95% CI) | |
|---|---|---|---|---|---|---|---|
| lower | upper | ||||||
| LVSI | 2.798 | 0.543 | 26.590 | <0.001 | 16.415 | 5.667 | 47.549 |
| MELF | 3.110 | 0.839 | 13.741 | <0.001 | 22.428 | 4.331 | 116.151 |
| Myometrial invasion | 1.380 | 0.518 | 7.089 | 0.008 | 3.973 | 1.439 | 10.969 |
| CA125 | 0.014 | 0.005 | 9.014 | 0.003 | 1.014 | 1.005 | 1.023 |
| HE4 | −0.006 | 0.004 | 2.286 | 0.131 | 0.994 | 0.985 | 1.002 |
| Tumour size | 0.884 | 0.577 | 2.345 | 0.126 | 2.420 | 0.781 | 7.497 |
| Cervical stromal | 0.864 | 0.704 | 1.507 | 0.220 | 2.372 | 0.597 | 9.418 |
| CA199 | 0.003 | 0.003 | 1.173 | 0.279 | 1.003 | 0.998 | 1.008 |
| Histologic grading | 0.093 | 0.588 | 0.025 | 0.875 | 1.097 | 0.346 | 3.476 |
LVSI, lymphovascular space invasion; MELF, microcystic, elongated, fragmented; OR, odds ratio.
The Efficacy of Combining CA125 and Depth of Myometrial Invasion or Parameter Alone for Diagnosing LNM
The area under the curve for CA125 and depth of myometrial invasion was 0.796 and 0.734, respectively, both of which were statistically significant (p < 0.05). The optimal diagnostic cut-off value for CA125 was identified as 31.36 U/mL, corresponding to the maximum Youden index of 53.9%, with a positive likelihood ratio of 5.2. Among the four independent risk factors analysed, ROC curve analysis was conducted to assess the predictive efficacy of CA125 and myometrial invasion depth, both individually and in combination for LNM. The results indicated that the combined use of CA125 and depth of myometrial invasion yielded higher diagnostic accuracy for LNM compared to either parameter alone, as demonstrated by the larger area under the ROC curve (Table 5; Fig. 1).
Table 5.
The efficacy of combining CA125 and depth of myometrial invasion or parameter alone for diagnosing LNM
| Variables | AUC (95% CI) | Sensitivity, % | Specificity, % | Positive predictive value | Negative predictive value | p value |
|---|---|---|---|---|---|---|
| CA125, U/mL | 0.796 (0.716–0.876) | 66.7 | 87.2 | 0.31 | 0.97 | <0.001 |
| Myometrial invasion | 0.734 (0.634–0.833) | 63.6 | 83.1 | 0.24 | 0.96 | <0.001 |
| Predicted probability (combining) | 0.840 (0.765–0.914) | 84.8 | 74.2 | 0.22 | 0.98 | <0.001 |
AUC, area under the curve.
Fig. 1.
ROC curves of CA125 and depth of myometrial invasion alone and in combination to predict LNM: receiver operating characteristic (ROC) curve analysis was employed to assess the predictive value of CA125 and myometrial invasion depth, individually and in combination, for detecting lymph node metastasis (LNM).
Discussion
A total of 424 patients with low-grade EEC were included in our study, with a LNM rate of 7.8%. Among them, 305 cases (71.9%) were classified as FIGO 2009 stage IA and 51 cases (12.0%) as stage IB, collectively accounting for 83.9% (356/424). CA125, depth of myometrial invasion, LVSI, and MELF pattern were identified as independent risk factors for LNM in low-grade EEC patients. The optimal diagnostic cut-off value for preoperative CA125 was determined to be 31.36 U/mL. Among the four independent risk factors, CA125 is derived from preoperative serological testing, while the depth of myometrial invasion can be preliminarily assessed using preoperative magnetic resonance imaging (MRI). CA125, though not a highly specific marker, and preoperative MRI assessment of myometrial invasion, despite possible inconsistencies with postoperative pathology, are still meaningful indicators for preoperative risk evaluation and deserve attention. By comparing the area under the ROC curve, we found that combining CA125 and depth of myometrial invasion provided greater diagnostic accuracy for LNM than either parameter alone. Our findings align with a Korean study [11], further confirming the importance of MRI and CA125 in the preoperative evaluation of EC [13, 14]. In conclusion, even low-risk, low-grade EEC carries a potential risk of LNM. If preoperative examinations indicate deep myometrial invasion and elevated CA125 levels, the possibility of LNM should be carefully considered, and systematic lymph node resection is recommended. Therefore, preoperative evaluation of CA125 and myometrial invasion is crucial, and a more detailed risk stratification approach should be adopted for low-grade EEC patients.
LVSI positivity has long been recognized as a predictor of poor prognosis, a finding supported by our study. Substantial evidence indicates that LVSI not only predicts LNM in EC but also significantly impacts patient outcomes [15–17]. A large Swedish study identified LVSI as the strongest independent risk factor for both LNM and survival in endometrioid adenocarcinoma patients [18]. Jorge et al. [19] further confirmed this association through their analysis of 25,907 patients, demonstrating that LVSI increases LNM risk by 3- to 10-fold. Currently, preoperative determination of LVSI status remains challenging. Consequently, investigating the reliability of endometrial biopsies for LVSI assessment represents an important research direction. The potential role of immunohistochemical markers (e.g., p53) in preoperative LVSI detection warrants further exploration [20]. For EC patients not undergoing staging surgery, LVSI presence may justify consideration of lymphadenectomy or adjuvant therapy [21].
Studies have shown that the MELF pattern is a unique form of invasion in EC, primarily observed in low-grade endometrioid carcinomas [22, 23]. The MELF pattern is also a risk factor for LNM in EC [24, 25]. Lymph nodes from grade I EEC exhibiting cellular budding or lymphovascular invasion should be carefully examined for occult metastases, particularly in the form of histiocyte-like cells [22]. In our study, the MELF pattern was identified in 16 cases, of which 13 (81.2%, 13/16) had LNM. Para-aortic LNM was observed in 6 patients, suggesting that the MELF pattern is associated with a higher likelihood of LNM. Analysis of the location of positive lymph nodes in patients with LNM revealed that 3 patients had isolated para-aortic LNM without pelvic lymph node involvement. These 3 patients exhibited diffusely positive LVSI or MELF pattern invasion. Therefore, both LVSI positivity and MELF pattern invasion are independent risk factors for LNM and are more likely to be associated with isolated para-aortic LNM, warranting further investigation with a larger sample size.
Furthermore, some studies have suggested that grade 2 lesions should be considered an important prognostic factor for recurrence in low-risk EC [26]. Additionally, tumour diameter has been linked to LNM and recurrence in EC patients [27], with tumour size identified as an independent predictor of LNM and survival in early-stage endometrioid endometrial cancer [28]. However, our findings indicate that while histological grade and tumour size are associated with LNM in low-grade EEC, they are not independent risk factors. Some studies have proposed that pretreatment NLR and HE4 are predictors of LNM in EC patients [29–32]. Unfortunately, our study did not validate these findings in low-grade EEC, as NLR, PLR, MLR, and HE4 were not identified as independent risk factors in this cohort.
Overtreatment remains a significant concern in EC management [6]. For low-grade EEC patients, identifying independent risk factors for LNM is crucial to enable more precise risk stratification. This highlights the necessity of comprehensive preoperative evaluation, incorporating peripheral blood indicators, imaging studies, immunohistochemical markers, and emerging molecular subtyping techniques to better assess LNM risk – an area deserving further systematic investigation. Besides, the judicious application of SLN biopsy also merits careful consideration [33, 34]. In conclusion, further research is essential to enhance risk-stratified management and optimize precision care for EEC patients.
Limitations
Although histological grade G2, tumour size ≥2 cm, cervical stromal invasion, CA199, and HE4 were not identified as independent risk factors in low-grade EEC, they remain worthy of continued attention. Further research with larger sample sizes may be necessary to explore these factors in greater depth. As our study is a single-centre, retrospective analysis, future multicentre, large-scale, prospective studies are needed to provide more robust evidence for clinical practice.
Conclusion
LNM is more likely to occur when positive LVSI, MELF pattern invasion, depth of myometrial invasion ≥50%, and CA125 are present. Combining CA125 and depth of myometrial invasion enhances diagnostic accuracy for LNM. This study provides valuable insights for predicting LNM risk in low-grade EEC patients and guiding stratified management.
Acknowledgments
The authors thank all colleagues involved in the manuscript. Special thanks to Dr. Yuping Li from the medical records department and Dr. Chen Li from the pathology department for their assistance in data collection.
Statement of Ethics
This retrospective study was approved and informed consent was waived by the Institutional Review Board of the Affiliated Hospital of Xuzhou Medical University, Approval No. (XYFY2025-KL012-01).
Conflict of Interest Statement
All authors have no conflicts of interest.
Funding Sources
The authors have no funding to declare.
Author Contributions
Lina Cao is the first author and corresponding author, who designed the study and wrote the manuscript. Xiaoyuan Lu supervised and guided the manuscript. Yijun Wang and Luyao Wang contributed to data collection. All authors have read and approved the final manuscript.
Funding Statement
The authors have no funding to declare.
Data Availability Statement
All data generated or analysed during this study are included in this article. Further enquiries can be directed to the corresponding author.
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Associated Data
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Data Availability Statement
All data generated or analysed during this study are included in this article. Further enquiries can be directed to the corresponding author.