Prognostic analysis of different pathological types of uterine sarcoma

doi:10.21203/rs.3.rs-4373773/v1

Purpose

There is a high recurrence rate and poor prognosis of uterine sarcomas, which are rare and aggressive gynecologic malignancies. Therefore, the study aims to examine the clinicopathological characteristics and prognostic factors associated with different histology types of uterine sarcomas.

Method

This study is a retrospective study. The clinical data of 80 patients (40 patients of uterine leiomyosarcom (ULMS) and 40 patients of endometrial stromal sarcomas (ESS)) treated at Chunliu Hospital of Dalian Women and Children's Center (group) over the past ten years were collected. A follow-up was conducted for all patients. For revealing the prognostic factors for different pathological types, SPSS25.0 statistical software was used to analyze the data retrospectively.

Results

Among the ULMS patients, univariate analysis showed that the postmenopausal patients had poor survival results (P = 0.025). While the patients with lower tumor stage (P = 0.000), tumor size ≤ 5 cm (P = 0.012), Ki-67 expression ≤ 10% (P = 0.012), PR expression negative (P = 0.007) and without lymph node resection (P = 0.049) had better survival results. Among the ESS patients, univariate analysis showed that postmenopausal patients with a higher tumor stage (P = 0.026) and those with tumor > 5 cm (P = 0.007) had poorer survival results. Multivariate analysis showed that surgical stage and tumor size are independent prognostic and survival indicators for ULMS, while menopause is an independent prognostic and survival indicator for ESS.

Conclusion

Multiple factors can affect the prognosis of uterine sarcoma. However, tumor size, and tumor stage, are independent risk factors for ULMS and menopause status is an independent risk factor for ESS prognosis.

Uterus leiomyosarcoma

endometrial stromal sarcoma

prognostic analysis

pathological character

The postmenopausal status, tumor grade, tumor stage, ki-67 expression, PR expression, lymph node resection are main factors which affect the prognosis of uterine sarcoma. Tumor stage and size are independent prognostic and survival indicators for ULMS and menopause status for ESS.

Uterine sarcomas, with an unknown etiology, account for around 1% of all female reproductive tract malignancies and 3%-7% of uterine malignancies. There are several types of uterine sarcomas, based on their origins in different types of cells: Uterine leiomyosarcoma (ULMS) and endometrial stromal sarcoma (ESS) [further subdivided into lower-grade and higher grade ESS], undifferentiated uterine sarcoma (UUS), and other rare types including adenosarcoma, perivascular epithelioid cell tumor and rhabdomyosarcoma (1, 2). Among them, ULMS is the most common type, accounting for about 40%-50% of uterine sarcomas, followed by ESS (3). These are malignant mesenchymal tissue-derived tumors and their pathology, treatment options, and prognosis are closely related. However, because of their rarity and histopathological diversity, there is no consensus on risk factors and optimal treatment for these diseases (4). Moreover, there are fewer specific symptoms, diagnostic technologies, or standard treatments for uterine sarcomas than for other types of endometrial cancers, so they usually have a worse prognosis and behave more aggressively. (5). Some expert believed that age, clinical stage, depth of myometrial invasion, presence, or absence of tumor thrombi in vessels and lymphatic vessels, lymph node metastasis, estrogen receptors and progesterone receptors and treatment methods are the main factors that affect patients' prognosis (6). On the other hand, the correlation between prognosis and patient age, clinical stage, tumor size, and vascular invasion has not been consistent among various studies (6). Therefore, data collection and follow-up of patients with uterine sarcoma were conducted to explore the prognostic factors of different pathological types of uterine sarcomas in this study. Because the incidence rate of undifferentiated uterine sarcoma is low and the number of cases is very small, it is not included in this study. The aim of this study is to analyze the prognosis of uterine leiomyosarcoma and endometrial stromal sarcoma.

2.1 Data collection

We collected the complete data of 80 patients with uterine sarcoma who visited Chunliu Hospital of Dalian Women and Children's Medical Center (Group) between January 2010 and December 2019. Among them, there were 40 patients with ULMS and 40 patients with ESS. This is an observational study.

2.2 Inclusion criteria

Patients with complete medical records were included in the study if they met one of the following conditions: (1) Patients who were hospitalized in our hospital and pathologically diagnosed with uterine sarcoma after surgery. (2) Those who were diagnosed with uterine sarcoma in any other hospital and were confirmed with uterine sarcoma by routine pathology after consultation in our hospital or after the operation.

2.3 Exclusion criteria

Patients with one of the following conditions were excluded from the study group: (1) Patients with malignant tumors of other systems (excluding those with metastasis of uterine sarcoma) (2) Patients with incomplete medical records.

2.4. Study design.

Each patient's general clinical data, including age, parity, menopausal status, clinical manifestations, imaging examinations (Color Doppler ultrasound prompt the tumor location, the tumor echo, and the blood flow signal), serological examinations (such as CA125), Lymphectomy or metastasis, adjuvant therapy, and postoperative pathology type (histology, immunohistochemistry), was retrospectively analyzed. According to the Federation of International Gynecology and Obstetrics (FIGO) guidelines, the tumor was staged. The patients were followed up for more than 3 years, until December 2022. Survival time was calculated from the date of diagnosis of sarcoma to death or the cut-off date for follow-up. We considered five cases dead due to lack of follow-up.

2.5. Statistical methods

This study is a retrospective study. A multivariate and univariate analysis was conducted using SPSS (25.0) statistical software. Chi-square test was used for single factor comparison of different clinical characteristics, and Fisher's exact probability test was performed for the number of cases < 40. Multivariate analysis was carried out with the COX proportional hazards model, and P < 0.05 indicated a statistically significant difference.

3.1 Prognosis of patients with uterine leiomyosarcoma (ULMS) based on univariate analysis.

The average onset age of uLMS is (47.55 ± 7.07) years old. 40 patients underwent surgical treatment. Among them, there were 9 cases of total hysterectomy and double fallopian tube resection, 17 cases of total hysterectomy and double adnexectomy, and 14 cases of hysteromyomectomy. Based on univariate analysis of 40 patients with ULMS, the 3-year survival rate is shown in table.1. The average progression free survival (PFS) was 61.27 ± 31.99 months. There were 4 cases of systemic recurrence, with a recurrence rate of 10%. Chi-square and Fisher's exact probability tests were used in the univariate analysis.

The 3-year survival rate of postmenopausal patients (7.5%) was significantly higher (P = 0.025) than that of nonmenopausal patients (6.5%). Similarly, the 3-year survival rate of patients without lymph node resection (70%) was significantly greater (P = 0.049) compared to that of patients with lymph node resection (2.5%). Our results showed that patients with stages I, II, III, and IV have a 3-year survival rate of 67.5%, 5%, 0%, and 0%, the prognosis of stage I patients is better than that of stage II and III patients (P = 0.00). The 3-year survival rate of patients with ≤ 5 cm size tumors (47.5%) was significantly higher (P = 0.012) than that of patients with > 5 cm size tumors. The 3-year survival rate of patients with Ki-67 expression ≤ 10% (40%) was higher (P = 0.012) than that of patients with > 10% expression (32.5%). The 3-year survival rate of patients with positive PR expression was 35%, which was significantly lower (P = 0.007) than that of patients with negative PR expression (37.5%).

Table 1

Univariate analysis of the prognosis of uterine leiomyosarcoma (ULMS)
Characteristics	Survived (number)		χ2.	P
age			0.457	0.7
≤ 45	14	35
> 45	15	37.5
menopause			6.144	0.025
yes	3	7.5
no	26	6.5
clinical manifestations			4.438	0.207
abnormal uterine bleeding	14	35
pelvic mass	5	12.5
lower abdominal pain	3	3
postmenopausal vaginal bleeding	0	0
other	7	7
pregnancy			0.398	0.715
< 3 times	18	45
≥ 3 times	11	27.5
CA125			1.792	0.319
≤ 35	26	65
> 3 5	3	7.5
tumor location			2.412	0.306
intrauterine	8	20
subserosa	10	25
intramural	11	27.5
tumor echo			1.083	0.438
even echo	12	30
uneven echo	17	42.5
blood flow signal			1.999	0.205
visible blood flow signal	6	15
no blood flow signal	23	57.5
surgical approach			1.794	0.493
laparoscopy	16	40
laparotomy	12	30
hysteroscopy	1	2.5
lymph nodes			5.030	0.049
removal	1	2.5
unresected	28	70
ovaries			2.489	0.163
reserved	16	40
not reserved	14	32.5
tumor phase			22.858	0.000
Phase I	27	67.5
Phase II	2	5
Phase III	0	0
Phase IV	0	0
adjuvant chemotherapy			0.376	0.696
yes	8	20
no	21	52.5
Lymph node metastasis			2.704	0.275
transfer	1	2.5
no transfer	28	70
tumor size			7.166	0.012
≤ 5cm	19	47.5
> 5cm	10	25
Ki-67expression			6.930	0.012
≤ 10%	16	40
> 10%	13	32.5
P 53 expression			0.755	0.488
mutant	15	37.5
wild type	14	35
ER expression			2.048	0.233
positive	9	22.5
negative	20	50
P R expression			8.170	0.007
positive	14	35
negative	15	37.5

3.2 Prognosis of ULMS based on multivariate analysis.

The Cox proportional hazards regression model was used to conduct multivariate analysis of factors such as age, menopause status, surgical stage, postoperative pathological tumor size, chemotherapy, and recurrence in all ULMS patients. According to the results, surgical stage and postoperative pathological tumor size are independent prognostic indicators of ULMS patient’s survival (Table.2). The tumor stage (P = 0.001) and tumor size (P = 0.023) are dependent prognostic indicators of ULMS patient’s survival. A decrease in survival rate (Fig. 1A) and increase in risk rate (Fig. 1B) was observed.

Table 2

Multivariate analysis of the prognosis of ULMS patients
covariate	Hazard ratio (HR)	P	9 5% confidence interval
Age	-1.938	0.185	0.008–2.525
Menopausal condition	-0.466	0.624	0.097–4.040
Tumor stage	3.780	0.001	4.313-444.981
Tumor size	1.079	0.023	0.494–17.506
Chemotherapy	-0.023	0.985	0.094–10.117
Whether to relapse	2.464	0.079	0.754-118.996

3.3 Prognosis of patients with endometrial stromal sarcoma (ESS) based on univariate analysis.

The average age of onset of ESS is (44.36 ± 9.80) years old. Among them, there were12 cases of total hysterectomy and double fallopian tube resection, 13 cases of total hysterectomy and double adnexectomy, and 15 cases of hysteromyomectomy. Table.3 shows the 3-year survival rate of 40 patients with ESS based on univariate analysis. The average PFS was 73.20 ± 38.96 months. There were 6 cases of systemic recurrence, with a recurrence rate of 15%. Chi-square and Fisher's exact probability tests were used in the univariate analysis.

The 3-year survival rate of ESS with menopause status (5%) was significantly lower (P = 0.003) than that of patients with non-menopause status (72.5%). Patients with stages I, II, III, and IV had a 3-year survival rate of 52.5%, 15%, 7.5%, and 0%, respectively (P = 0.026). Furthermore, patients with tumors ≤ 5 cm in size (50%) had a higher 3-year survival rate (P = 0.007) than those with tumors > 5 cm (27.5%).

Table 3

Univariate analysis of the prognosis of endometrial stromal sarcoma (ESS)
Characteristics	Survived (number)	3-year survival rate (%)	χ2	P
age			0.523	0.705
≤ 45	18	45
> 45	13	32.5
menopause			11.649	0.003
yes	2	5
no	29	72.5
clinical manifestations			4.066	0.354
abnormal uterine bleeding	14	35
pelvic mass	12	30
lower abdominal pain	2	5
postmenopausal vaginal bleeding	1	2.5
other	2	5
Pregnancy			0.833	0.453
< 3 times	19	47.5
≥ 3 times	12	30
CA125			1.290	0.348
≤ 35	26	65
> 3 5	3	12.5
tumor location			3.052	0.289
intrauterine	6	15
subserosa	3	7.5
intramural	18	45
tumor echo			0.442	0.703
even echo	12	30
uneven echo	16	40
blood flow signal			3.997	0.081
visible blood flow signal	2	5
no blood flow signal	26	65
surgical approach			2.428	0.287
Laparoscopy	12	30
laparotomy	14	35
Hysteroscopy	5	12 .5
lymph nodes			0.782	0.394
removal of lymph nodes	6	15
unresected lymph nodes	25	62.5
ovaries			0.239	0.705
reserve	11	27.5
not reserved	20	50
tumor phase			6.589	0.026
Phase I	21	52.5
Phase II	6	15
Phase III	3	7.5
Stage IV	0	0
adjuvant chemotherapy			3.061	0.115
yes	3	7.5
no	28	70
Lymph node metastasis			1.290	0.348
transfer	5	12.5
no transfer	26	65
tumor size			7.977	0.007
≤ 5cm	20	50
> 5cm	11	27.5
Weather LGESS			2.434	0.149
yes	16	40
no	15	37.5
Ki − 67 expression			0.810	0.456
≤ 10%	19	47.5
> 10%	12	30
P 53 expression			3.533	0.225
mutant	0	0
Wild type	31	77.5
ER expression			0.639	0.476
positive	15	37.5
negative	16	40
P R expression			0.935	0.457
positive	16	40
negative	15	37.5

3.4 Prognosis of ESS based on multivariate analysis.

Cox proportional hazards regression model was used to conduct multivariate analysis of factors such as age, menopause status, surgical stage, tumor size indicated by postoperative pathology, chemotherapy, and recurrence in all patients. The results indicated that menopause status was an independent prognostic indicator for ESS patients' survival (Table.4). The menopausal condition is a dependent prognostic indicator for ESS patients' survival(P = 0.050). A decrease in survival rate (Fig. 2A) and increase in risk rate (Fig. 2B) was observed.

Table 4

Multivariate analysis of the prognosis of ESS patients
covariate	Hazard ratio (HR)	P	9 5% confidence interval
age	0.191	0.849	0.168–8.699
menopausal condition	2.167	0.050	0.927–82.229
surgical staging	1.495	0.270	0.314–63.394
tumor size	1.938	0.226	0.300-160.574
chemotherapy	− 0.140	0. 894	0.109-6.900
whether to relapse	− 0.305	0.828	0.047–11.540

14 CA125 positive patients were analyzed in detail. Table 5 analyzes the relationship between different clinical characteristics and survival outcomes of CA125 positive patients. The 3-year survival rate of CA125 positive patients with menopause was 7.14%, while the 3-year survival rate of those without menopause was 57.14%.

There was a statistically significant relationship between menopause and survival outcome in CA125 positive patients (Fisher's exact test: 5.091, P = 0.049), and those without menopause had better survival outcomes. The 3-year survival

rate was 50% for CA125 positive patients with tumor size ≤ 5m, and 7.14% for those with tumor size > 5cm. The relationship between tumor size and survival outcome was statistically significant in CA125 positive patients (Fisher's exact test: 7.024, P = 0.028), and the smaller the tumor, the better the survival outcome.

Table 5

The relationship between clinical characteristics and outcomes of CA125 positive patients
Characteristics		3-year survival rate (%)	χ2 value
age		0.389	0.627
≤ 45	4
> 45	4
menopause		5.091	0.049
yes	8
no	1
clinical manifestations		3.022	0.600
abnormal uterine bleeding	4
pelvic mass	2
lower abdominal pain	1
postmenopausal vaginal bleeding	1
tumor size		7.024	0.028
≤ 5cm	7
> 5cm	1
tumor location		0.966	0.773
intrauterine	3
subserosa	1
intramural	3
tumor echo		0.389	0.627
even echo	4
uneven echo	4
blood flow signal		1.527	0.417
visible blood flow signal	7
no blood flow signal	0
tumor staging		4.499	0.149
Phase I	6
Phase II	1
Phase III	1
Lymph node metastasis		0.884	0.538
transfer	1
no transfer	7

Clinical research with large samples of uterine sarcoma in a single institution is challenging due to its low incidence and high malignancy. Moreover, the preoperative diagnosis of uterine sarcoma is difficult, and it is often misdiagnosed as uterine leiomyoma, which is often diagnosed during postoperative pathological examination (7). Most patients have no specific signs, and up to 25% of patients are asymptomatic (8). Although the use of magnetic resonance imaging (MRI) in the evaluation of malignancies is crucial, the cost of this imaging modality prevents it from becoming a routine preoperative examination tool (9). A study reported that ULMS occurred in 0.25 percent (1:400 patients) and unexpectedly in 0.12% (1:865) (10). Because uterine sarcomas arise in the deep muscle layers of the uterus, preoperative endometrial sampling is not easy to detect. For instance, a multicenter retrospective study of 302 patients found that 65% of cases were diagnosed as uterine sarcoma before surgery, and only 25% after endometrial sampling (11).

In current study, ULMS had the same incidence as ESS and 3-year survival rate of ULMS and ESS was 72.5%, and 77.5%, respectively. However, A retrospective analysis of 114 uterine sarcoma patients in western China showed that ESS cases (65.3%) were greater than LMS cases (29.8%) (12) and the 3-year survival rate of uterine sarcoma was 65.1% (13). This study's results are slightly higher than those reported in the literature, possibly because the number of patients was small and most of them were early-stage patients. Additionally, laparoscopy and laparotomy are surgical options, and some patients choose hysteroscopy because of submucosal fibroids. Minimally invasive technology has gradually increased the use of rotary cutters. FDA (Food and Drug Administration) issued a recommendation to limit the use of power pulverizers in 2014, and in the 2020 update, it was prohibited in principle. Doctors need to understand the risk of malignant intraperitoneal dissemination (14). The standard surgical procedure for uterine sarcoma is a total hysterectomy + double adnexectomy. Generally, systematic pelvic and para-aortic lymph node dissection is not routinely performed. Exploration should be performed during the operation, and enlarged or suspicious lymph nodes should be resected (15–17). Nasioudis et al., recently published a report showing the role of lymphadenectomy in early-stage uterine sarcomas. The report found that lymphadenectomy was not associated with better survival for patients with adenosarcoma, or low-grade ESS (after controlling for confounders). While patients with high-grade endometrial stromal/undifferentiated sarcoma who underwent lymphadenectomy had better survival. However, patients with leiomyosarcoma who underwent lymphadenectomy had a poorer survival (18). It is still controversial whether the ovaries should be preserved in patients with uterine sarcoma. Studies have shown that the recurrence rate of ovarian preservation in patients with lower-grade ESS is extremely high. Therefore, double adnexectomy is recommended, and postoperative estrogen replacement therapy is not advocated. However, some scholars have suggested that ovarian preservation can be considered for ESS patients of stage I after strict selection, and more evidence is needed to confirm this (19–21).

According to current study, menopausal status, tumor stage, pathological tumor size, lymph node resection, K i-67 expression, and PR expression in ULMS were associated with prognosis, but surgical stage and tumor size were independent risk factors. Similarly, there was an association between tumor size, tumor stage and prognosis in ESS, and menopausal status was an independent risk factor. Like our study, many studies have shown that the later the clinical stage of a tumor, the poorer the prognosis will be (22). Many studies have shown that PR is highly expressed in patients with uterine sarcoma and is associated with a favorable prognosis and improved overall survival. There are a few possible explanations for why PR receptor negativity is a negative prognostic factor in leiomyosarcoma. For example, PRs are involved in the cell cycle, and PR negativity may lead to uncontrolled cell growth. Additionally, PRs are involved in the production of proteins that promote angiogenesis and suppress the immune system. Therefore, PR negativity may limit the ability of tumors to grow and make them more susceptible to immune attack. Overall, the evidence suggests that PR receptor negativity is a negative prognostic factor in leiomyosarcoma. Patients with PR-negative tumors are more likely to have a shorter survival time than patients with PR-positive tumors (23, 24).

Tumor size is a significant prognostic factor in uterine sarcomas. D’Angelo et al., examined the impact of clinicopathological findings in ULMS on survival outcomes(25). They proposed that larger tumors (e.g. >10cm) have a poorer prognosis. Another study concluded that mitotic count is an independent prognostic factor for uterine sarcomas (26). Tumor stage is also a crucial prognostic factor in uterine sarcoma. The 5-year overall survival rate of patients with stage I (50–55%) is higher than that of patients with stage II-IV (8–12%). (1). Similarly, Li et al also observed a significant correlation between tumor stage and overall survival in both univariate and multivariate analyses. The 3-year overall survival rate for all histological types was 75.4% for stage I, 57.1% for stage II, 33.3% for stage III, and 7.1% for stage IV (27). This study also shows that tumor stage and tumor size are associated with prognosis across pathological types, a finding that is consistent with literature. In addition, the prognosis of uterine sarcoma is also influenced by factors such as menopausal status, sarcoma overgrowth, lymphovascular space invasion, resection margin, depth of myometrial invasion, and mitotic figures (28–31). High-grade ESS and undifferentiated uterine sarcomas that are treated with adjuvant chemotherapy are likely to have better disease-free survival rates (32). According to a meta-analysis of hormone therapy in 315 cases of low-grade ESS, hormone therapy reduced the recurrence risk for stage I patients(33). Similarly, another retrospective cohort study revealed that hormone therapy reduces recurrence in stage II-IV low-grade ESS (34). Since 2014, UUS has no longer been classified as ESS, and the histology of some ESS in this study did not clearly mark weather LGESS or HGESS. Therefore, this study only conducted statistical analysis on whether it is LGESS.

Ki-67 was significantly expressed in leiomyosarcoma tissue compared to leiomyoma patients. Therefore, the combination of Ki-67 detection can be used in differential diagnosis of uterine sarcoma (35). A study showed that a Ki-67 index cut-off value of 35% was the most reliable indicator for predicting recurrent ESS. Therefore, the Ki-67 index may be a significant indicator of ESS prognosis (36). In this study, ULMS patients with Ki-67 expression ≤ 10% had a better prognosis. However, a small sample size and a short follow-up time were used in this study. Therefore, more studies with a larger sample size and multi-center trials are still needed in the future. This institution is a specialized hospital for obstetrics and gynecology and does not have the conditions for radiotherapy. Therefore, it is difficult to collect data on radiotherapy patients. Another limitation of the study is that it lacks residual tumor data. We were unable to obtain residual tumor data for most of our patients because they were at an early stage after surgery. Moreover, studies have shown that elevated serum LDH levels are common in patients with multiple malignant tumors, including ESS. LDH type A and LDH type D are specifically expressed in uterine sarcoma. The expression of LDH and its subtypes in serum can be a useful biomarker for the preoperative diagnosis of ESS (37, 38). However, our study is a recent project, and we were not able to collect a full 10 years of patient data. This is a limitation of our study, but we believe that the results are still clinically significant. We have included this paragraph in the discussion. For the impact of treatment methods on prognosis of uterine sarcoma, a larger sample size and longer follow-up are still needed in the future.

The study concludes that postmenopausal status, tumor grade, tumor stage, ki-67 expression, PR expression, lymph node resection are main factors which affect the prognosis of uterine sarcoma. Tumor stage and size are independent prognostic and survival indicators for ULMS and menopause status for ESS. Based on this study's findings, strict follow-up is recommended for patients with these factors. Moreover, research with large samples and long-term follow-up is necessary.

Funding statement: This work was funded by the Dalian Science and Technology Innovation Project (grant number: 2020JJ27SN096).

Conflicts of interest statement: The authors declare that there is no relevant financial or non-financial interests to disclose.

Author Contributions:

Aziz ur Rehman Aziz:

Conceptualization: Equal

Formal analysis: Equal

Investigation: Equal

Methodology: Equal

Software: Equal

Writing – original draft: Equal

Siyi Yang:

Data curation: Equal

Formal analysis: Equal

Investigation: Equal

Methodology: Equal

Software: Equal

Writing – original draft: Equal

Xiaohui Yu:

Conceptualization: Equal

Data curation: Equal

Funding acquisition: Lead

Resources: Equal

Writing – review & editing: Equal

Daqing Wang:

Project administration: Equal

Resources: Equal

Supervision: Lead

Writing – review & editing: Equal

All authors read and approved the final manuscript.

Ethical approval statement: All methods were carried out in accordance with relevant guidelines and regulations. all experimental protocols were approved by the ethical committee of Dalian Maternal and Child Health Care Hospital Research Ethics Committee and has confirmed that no ethical approval is required.

Consent to participate: Informed consent was obtained from each participant.

Consent to publish: Consent to publish was obtained.

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No competing interests reported.

Prognostic analysis of different pathological types of uterine sarcoma

Status:

Version 1

Abstract

Purpose

Method

Results

Conclusion

Figures

Take home message

1 Introduction

2 Materials and methods

2.1 Data collection

2.2 Inclusion criteria

2.3 Exclusion criteria

2.4. Study design.

2.5. Statistical methods

3 Results

3.1 Prognosis of patients with uterine leiomyosarcoma (ULMS) based on univariate analysis.

3.2 Prognosis of ULMS based on multivariate analysis.

3.3 Prognosis of patients with endometrial stromal sarcoma (ESS) based on univariate analysis.

3.4 Prognosis of ESS based on multivariate analysis.

4 Discussion

5 Conclusion

Declarations

References

Additional Declarations

Status:

Version 1