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Article

Prognostic Nomogram for Predicting Survival, Clinicopathological Analysis, and Racial Disparities in Uterine Carcinosarcoma: A Retrospective Population-Based Study

by
Asad Ullah
1,*,
Lily Rubin
2,
Alexa Rakusin
2,
Abdul Qahar Khan Yasinzai
3,
Abdullah Chandasir
2,
Amir Humza Sohail
4,
Asif Iqbal
5,†,
Abdul Waheed
6,
Roona Khan
7,
Luis Brandi
1,
Bisma Tareen
7,
Aman Goyal
8,
Abu Baker Sheikh
9,
Agha Wali
7,
Thomas Paterniti
10 and
Mark Reedy
11
1
Department of Pathology, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA
2
Medical College of Georgia, Augusta, GA 30912, USA
3
University of Florida Health Cancer Center, Gainesville, FL 32608, USA
4
Department of Surgery, University of New Mexico, Albuquerque, NM 87131, USA
5
Mercy Medical Center, Ardmore, OK 73401, USA
6
Department of Surgery, Baycare Health System, Clearwater, FL 33759, USA
7
Bolan Medical College, Quetta 83700, Pakistan
8
Department of Internal Medicine, Seth GS Medical College and KEM Hospital, Mumbai 400 012, India
9
Department of Medicine, University of New Mexico, Albuquerque, NM 87131, USA
10
Department of Gynecology and Obstetrics, Medical College of Georgia, Augusta University, Augusta, GA 30901, USA
11
Department of Gynecologic Oncology, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA
 
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*
Author to whom correspondence should be addressed.
†
Current address: Northeasten Health System, Tahlequah, OK 74464, USA.
Surgeries 2024, 5(3), 743-757; https://doi.org/10.3390/surgeries5030059
Submission received: 16 June 2024 / Revised: 13 August 2024 / Accepted: 14 August 2024 / Published: 20 August 2024
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Abstract

:
Introduction: Uterine carcinosarcoma is an aggressive gynecologic malignancy that accounts for 5% of all gynecological malignancies. There is a disproportion in its incidence and mortality among different races. This study describes demographic and clinicopathological factors and racial disparities affecting the survival of patients with uterine carcinosarcoma. Methods: Data on uterine carcinosarcoma patients were obtained from the Surveillance, Epidemiology, and End Results (SEER) database from 2000 to 2020. Results: Of the 11,338 patients identified, the median age at diagnosis was 68 years, and the five-year cause-specific survival (CSS) rate was 38.7%. for all races. Compared with Asian patients (39.5%, 95% CI, 36.0–43.4%), Hispanic patients (39.4%, 95% CI, 36.5–42.5%), and White patients (37.9%, 95% CI, 36.7–39.2%), Black patients accounted for 21% of the patients and had a significantly lower 5-year CSS (95% CI, 27.2–31.2%). The CSS rates were 84.4% (95% CI, 83.3–85.6%) for localized tumors, 68.5% (95% CI, 66.9–70.1%) for regional tumors, and 39.0% (95% CI, 36.9–41.2%) for distant tumors. Multimodal treatment involving chemotherapy, surgery, and radiation improved the overall one- and five-year survival rates by 88.2% (95% CI, 87.0–89.5%) and 52.8% (95% CI, 50.7–55.1%), respectively, across all disease stages. Multivariate analysis identified age >60 years, Black race, tumor size >4 cm, and distant metastases as independent risk factors for mortality (p < 0.0001). Conclusions: This large database study presents the most up-to-date epidemiological information regarding cases of uterine carcinosarcoma. The findings suggest that a combination of surgery, chemotherapy, and radiation may be most efficacious in treating this malignancy, especially in patients with distant disease.

1. Introduction

Uterine carcinosarcoma (UCS), previously referred to as malignant mixed Müllerian tumor, is a rare and aggressive gynecologic malignancy that accounts for approximately 5% of all endometrial cancers but is responsible for 16.4% of all uterine cancer-related deaths [1]. UCS tumors are biphasic and are characterized by both epithelial (carcinomatous) and mesenchymal (sarcomatous) components. UCS most often originates in the uterus, although it may rarely arise in the fallopian tubes, ovaries, peritoneum, or vaginal canal [2]. UCS typically presents in postmenopausal women after age 60 with symptoms of abnormal uterine bleeding, rapid uterine enlargement, and pelvic pain [2,3]. Symptoms generally occur late in the disease course, with lymphatic invasion observed in 30–40% and metastatic disease in >10% of patients at diagnosis [3]. Metastasis may occur at almost any site, although it is most common in the lungs [3,4,5,6]. It may be challenging to differentiate UCS from other uterine pathologies, such as leiomyosarcoma, based on clinical examination alone; therefore, a thorough evaluation via biopsy, pelvic ultrasound, and/or magnetic resonance imaging is necessary for diagnostic confirmation [6].
Uterine carcinosarcoma shares many risk factors with other endometrial malignancies, including excess estrogen exposure, nulliparity, obesity, smoking, tamoxifen use, and prior pelvic radiation [1,7,8,9]. Racial disparities are seen in UCS outcomes, as non-Hispanic Black women have a 38% greater risk of death from UCS than White women [1,10]. The exact mechanism of uterine carcinosarcoma pathogenesis is still debated; however, most evidence supports the “conversion” hypothesis, whereby the cancer originates from a single endometrial epithelial cell that undergoes metaplastic differentiation into carcinoma [11]. This epithelial-to-mesenchymal transition is a key step in the pathogenesis of UCS and may be regulated by several hormonal and immunologic modulators [12].
The standard treatment approach for patients with operable UCS tumors ranges from radical surgical excision to total hysterectomy, with complete surgical staging recommended via lymphadenectomy of the pelvic and para-aortic lymph nodes [1,2,12]. Adjuvant chemotherapy and/or radiotherapy are commonly included in treatment regimens, as the combination of both has been shown to reduce the risk of recurrence compared to adjuvant radiotherapy alone [3,12]. For patients with advanced metastatic disease, conservative surgical approaches or palliative chemotherapy are typically more appropriate [1]. Additionally, several targeted therapeutic agents, such as tyrosine kinase inhibitors, HER-2-targeting drugs, and immune checkpoint inhibitors, are under investigation as potential treatment options [1,12].
The purpose of this study was to investigate racial disparities in addition to key demographic, clinical, and pathological factors affecting the prognosis and survival of patients with uterine carcinosarcoma.

2. Materials and Methods

The Surveillance, Epidemiology, and End Results (SEER) database initiated by the National Cancer Institute in 1973 covers approximately 26.5% of the United States population. SEER*Stat software (version 8.4.3) was used to collect data from 17 registries which includes the Alaska Native, Arizona Indians, Cherokee Nation, Connecticut, Detroit, Greater Georgia, Greater Bay Area Cancer, Greater California, Los Angeles, Hawaii, Iowa, Kentucky, Louisiana, New Jersey, Seattle-Puget Sound, New Mexico, and Utah Tumor Registry from 2000 to 2020 using the International Classification of Diseases version 3 (ICD-O-3) and SEER software (https://seer.cancer.gov/seerstat/, accessed on 18 February 2024). The data were exported to R version 4.2.3 (Shortstop Beagle) for analysis.
The demographic and clinical data collected included age, race, tumor grade, tumor size, lymph node status, metastasis status, surgical treatment, radiotherapy, chemotherapy, overall survival and survival after surgery, radiation therapy, and chemotherapy. The included cases were those labeled “microscopically confirmed positive histology”. The exclusion criteria were “direct visualization without microscopic confirmation”, “radiography without microscopic confirmation”, “clinical diagnosis only”, and an unknown status.
The cases included in the study were those reported from “hospital inpatient/outpatient or clinic”, “laboratory only (hospital or private)”, “physician’s office/private medical practitioner (LMD)”, and “nursing/convalescent home/hospice”. Patients whose data were reported from “autopsy only” or “death certificate only” were excluded. For survival analysis, patients were included only if they were microscopically confirmed, if malignant behavior was reported, or if the patient’s age was known. Patients excluded from the survival analysis were those with a death certificate or autopsy only and those who were alive with no survival time (Supplemental Figure S1).
R version 4.2.3 (Shortstop Beagle) was used for the statistical analysis. Univariate analysis was conducted to identify significant factors for multivariate analysis. The Cox regression method was used to calculate hazard ratios and to identify independent factors affecting survival outcomes. Unidentified or missing data were removed from the multivariate analysis. The data were analyzed using multivariate Cox regression, with statistical significance defined as p < 0.05. A prognostic nomogram was also constructed to predict future patient mortality and survival rates. This was performed through the “rms” package in R. After pertinent prognostic variables were identified, the resulting mathematical models were then used to construct a nomogram. By giving each variable a numerical score determined by how much of an impact it has on the overall forecast, the nomogram provides a visual representation of the predictive model. Following the addition of these scores, a total point value is produced that is correlated with the expected likelihood or risk of the specified outcome, such as the course of the disease or survival. The accuracy and generalizability of the nomogram were confirmed through the use of internal and external validation approaches. Internal validation entailed evaluating the nomogram’s performance within the original dataset using resampling techniques such as bootstrapping or cross-validation.

3. Results

3.1. Demographic Data, Tumor Characteristics, and Metastatic Sites

Between 2000 and 2020, 11,338 patients with uterine carcinosarcoma were identified. The median age at diagnosis was 68 years. A total of 58.3% of patients were aged >65 years. Compared to the U.S. census percentages (https://www.census.gov/quickfacts/fact/table/US/PST045222, accessed on 10 March 2024), uterine carcinosarcoma affects Black patients at a higher rate (21.5%). Rural-Urban Continuum Codes distinguish metropolitan (metro) counties by the population size of their metro area, and nonmetropolitan (nonmetro) counties by the degree of urbanization and adjacency to a metro area or areas (https://seer.cancer.gov/seerstat/variables/countyattribs/ruralurban.html, accessed on 10 May 2024). Most patients (88.9%) lived in the Urban setup. Median household income in the United States in 2022 was $74,580 (https://www.census.gov/library/publications/2023/demo/p60-279.html, accessed on 10 March 2024). The household income was divided into upper and lower quartiles of $75,000. Disease incidence was evenly spread across a range of household incomes, with a slight majority of patients earning less than USD 75,000 per year (56.4%). In addition, the majority (88.9%) of patients resided in urban areas (Table 1). Of the tumors described, 10,065 (90.9%) were found within the endometrium, 808 (7.1%) within the corpus uteri, 156 (1.4%) in the uterine fundus, and 50 (0.4%) in the uterine isthmus (Table 1). Tumor size was known in 67.1% of patients, of whom the majority (75.2%) had tumors 2–4 cm in size (Table 1). The tumor stage was known in 78.8% of the patients; 3162 (35.4%) had localized tumors, 3769 (42.2%) had regional tumors, and 2003 (22%) had distant tumors (Table 1). Lymph node status was known in 66.6% of patients, with 2066 (27.4%) patients having a positive lymph node status at the time of diagnosis. The AJCC 6th, 7th, and 8th editions were performed contemporaneously to reflect the staging criteria at the time of diagnosis. (Table 1).

3.2. Treatment Characteristics

In patients for whom the modality of therapy was known, the most common treatment was surgery, followed by surgery with adjuvant chemoradiation (Figure 1).

3.3. Overall and Cause-Specific Survival

The 1-year and 5-year overall survival rates of patients with uterine carcinosarcoma were 68.4% (95% CI, 67.6–69.3%) and 36.4% (95% CI, 35.5–37.4%), respectively (Supplemental Figure S2A). As a point of clarification, disease-specific survival is listed as “cause-specific survival” in the SEER database. The 1-year and 5-year cause-specific survival rates of the patients were 69.4% (95% CI, 68.4–70.4%) and 38.7% (95% CI, 37.6–39.8%), respectively (Supplemental Figure S2B and Supplemental Table S1).

3.4. Survival Analysis of Demographic Outcomes

The 1-year and 5-year OS rates were better for patients younger than 65 years than for patients older than 65 years (1-year OS 73.4% vs. 65.0%, 5-year OS 44.8% vs. 30.5%) (Figure 2A; Supplemental Table S2). The 1-year and 5-year overall survival (OS) rates differed significantly by race. Hispanics with a 1-year OS of 72.1% (95% CI, 69.6–74.7%) and a 5-year OS of 39.4% (95% CI, 36.5–42.5%), Asians with a 1-year OS of 70.7% (95% CI, 67.6–73.9%) and a 5-year OS of 39.5% (95% CI, 36.0–43.4%), and Whites with a 1-year OS of 69.1% (95% CI, 68.0–70.3%) and a 5-year OS of 37.9% (95% CI, 36.7–39.2%) all had better survival outcomes than Black patients, who had a 1-year OS of 63.9% (95% CI, 61.9–65.9%) and a 5-year OS of 29.1% (95% CI, 27.2–31.2%) (Figure 2B and Supplemental Table S3). The 1-year survival rate with multimodal therapy was 88.2% (87.0–89.5%), and at 5 years, it was 52.8% (50.7–55.1%) (Figure 2C). Univariate analysis revealed that race was a significant prognostic factor, with Black patients having a worse prognosis (hazard ratio (HR) = 1.3 (95% CI, 1.2–1.4; p < 0.001)) (Table 2).
Univariate analysis revealed increased age to be a prognostic indicator of survival, with patients older than 65 years having decreased survival (H. R = 1.6 (95% CI, 1.5–1.7); p < 0.001) (Table 2). Housing area and median annual household income were not found to be significant prognostic factors.

3.5. Outcomes by Tumor Characteristics and Treatment Modalities

3.5.1. Tumor Characteristics

The 1-year and 5-year OS rates for patients with endometrial tumors (1-year OS, 69.5% (95% CI, 68.6–70.5%); 5-year OS, 37.4% (95% CI, 36.4–38.5%)) were significantly better than those for patients with myometrial tumors (1-year OS, 59.7% (95% CI, 53.2–66.9%); 5-year OS, 26.5% (95% CI, 21.0–33.5%)); and corpus uteri tumors (1-year OS, 58.1% (95% CI, 54.8–61.7%) and 5-year OS, 27.8% (95% CI, 24.7–31.3%)). Univariate analysis revealed that tumor site was a significant prognostic factor, and patients with tumors of the corpus uteri (H. R = 1.3 (95% CI, 1.2–1.4); p < 0.001) and myometrium (H. R = 1.2 (95% CI, 1.1–1.5); p = 0.007) were both found to have significantly decreased survival times (Table 2).
The 1-year and 5-year OS rates for localized tumors (1-year OS 84.4% (95% CI, 83.3–85.6%) and 5-year OS 56.8% (95% CI, 55.2–58.4%)) were significantly better than those for regional tumors (1-year OS 68.5% (95% CI, 66.9–70.1%) and 5-year OS 29.7% (95% CI, 28.1–31.3%)). Patients with distant tumors had the worst 1-year and 5-year OS (1-year OS 39.0% (95% CI, 36.9–41.2%) and 5-year OS 9.0% (95% CI, 7.8–10.4%)) (Figure 2D; Supplemental Table S4). Univariate analysis revealed that tumor stage was a significant prognostic factor, with localized tumors having the best prognosis (H. R = 0.23 (95% CI, 0.21–0.25); p < 0.001), followed by regional tumors (H. R –0.44 (95% CI, 0.42–0.48); p < 0.001) (Table 2).
The 1-year and 5-year OS rates for tumors less than 2 cm in size (1-year OS rates of 83.0% (95% CI, 78.9–87.3%) and 5-year OS rates of 50.2% (95% CI, 44.5–56.7%)) and for those between 2 and 4 cm in size (1-year OS rates of 84.4% (95% CI, 82.6–86.2%) and 5-year OS rates of 52.9% (95% CI, 50.2–55.7%)) were significantly better than those for tumors greater than 4 cm in size (1-year OS rates of 68.1% (95% CI, 66.9–69.4%) and 5-year OS rates of 34.5% (95% CI, 33.1–35.9%)) (Supplemental Figure S4 and Table S5). Univariate analysis revealed tumor size to be a significant prognostic factor for survival, with tumors greater than 4 cm in size having a worse prognosis (H. R = 1.6 (95% CI, 1.4–1.9); p < 0.001) (Table 2).

3.5.2. Treatment Modality

The patients with the best 1-year and 5-year OS were those who received multimodal treatment (1-year OS 88.2% (95% CI, 87.0–89.5%), 5-year OS 51.8% (95% CI, 50.7–55.1%)) or radiation and surgery (1-year OS 77.3% (95% CI, 75.2–79.5%), 5-year OS 43.6% (95% CI, 41.1–46.4%)) (Supplemental Table S6). Univariate analysis revealed treatment modality to be a prognostic indicator of survival, and multimodal treatment (H. R = 0.58 (95% CI, 0.54–0.62); p < 0.001), as well as radiation combined with surgery (H. R = 0.83 (95% CI, 0.77–0.89); p < 0.001), indicating better survival outcomes. Patients who underwent surgery only (H. R = 1.18 (95% CI, 1.11–1.26) p < 0.001) and patients who did not receive any treatment (H. Patients with R = 4.84 (95% CI, 4.36–5.36); p < 0.001) had significantly lower survival (Table 2).
When further stratified by tumor stage, the best 1-year and 5-year OS in patients with localized disease were in those receiving multimodal treatment (1-year OS 93.3%, 95% CI, 91.6–95.0%), 5-year OS 69.5% (95% CI, 66.3–72.8%) or chemotherapy and surgery (1-year OS 90.0% (95% CI, 87.7–92.4%), 5-year OS 64.7% (95% CI, 60.0–68.7%)). The combination of radiation and surgery had a similar survival rate to that of chemotherapy and surgery at 1 year (85.7% (95% CI, 83.3–88.2%)), but survival was significantly worse than that of multimodal treatment at 1 year and 5 years. Among patients with regional disease, multimodal treatment had the best 1-year and 5-year OS (1-year OS 87.8% (95% CI, 85.7–90.0%), 5-year OS 44.3% (95% CI, 41.0–47.8%)). For patients with distant disease, the best 1-year and 5-year OS rates were observed for patients who underwent multimodal treatment (1-year OS 64.4% (95% CI, 58.1–71.3%), 5-year OS 18.9% (95% CI, 14.2–25.2%)) or who received a combination of chemotherapy and surgery (1-year OS 57.4% (95% CI, 54.1–60.9%), 5-year OS 13.9% (95% CI, 11.7–16.6%)). The combination of radiation and surgery in patients with distant disease also improved the 5-year OS (13.9% (95% CI, 7.4–26.0%)). Patients who underwent no treatment had a significantly worse 1-year and 5-year OS for all tumor stages, except for 5-year survival rates, compared to surgery only for patients with regional (16.4%, 95% CI, 14.0–19.2%) or distant disease (2.2%, 95% CI, 1.2–4.1%) (Supplemental Table S7).

3.6. Racial Disparities in Survival by Tumor Stage

There was a difference in survival between the White and Black populations stratified by tumor stage. White patients had the highest observed survival in all stages at 1 and 5 years. The 5-year survival rate for patients with localized disease was 56.9% (54.9–58.9%) for White females and 50.5% (46.8–54.4%) for Black females. For regional disease, the 5-year survival rate was 31.2% (29.2–33.4%) for White females and 24.1% (21.1–27.4%) for Black females. For patients with distant metastasis, the 5-year survival rate was 10.1% (8.5–12.0%) for White females and only 4.6% (2.9–7.1%) for Black females (Supplemental Table S8).

3.7. Multivariate Analysis and Propensity Score Matching

Multivariate analysis was performed using Cox survival regression analysis (Table 2). Independent factors associated with increased mortality were identified as age above 65 years (H. R = 1.36 (95% CI, 1.26–1.45); p < 0.001), Black race (H. R = 1.14 (95% CI, 1.01–1.28); p = 0.03), a tumor size greater than 4 cm (H. R = 1.46 (95% CI, 1.21–1.75); p < 0.001), positive nodal status (H. R = 1.46 (95% CI, 1.33–1.61); p < 0.001), and patients receiving either no treatment (H. R = 5.85 (95% CI, 2.39–14.30); p < 0.001) or surgery only (H. R = 1.72 (95% CI, 1.55–1.92); p < 0.001). The factors that were associated with decreased mortality were localized tumors (H. R = 1.46 (95% CI, 1.21–1.75); p < 0.001) and receiving multimodal treatment (H. R = 0.82 (95% CI, 0.74–0.92); p < 0.001) or radiation combined with surgery (H. R = 0.89 (95% CI, 0.81–0.97); p < 0.001). A hazard ratio above 1 indicates that there is a higher incidence of mortality in the pertaining group, whereas a hazard ratio below 1 indicates a decreased incidence of mortality. All statistically significant hazard ratio coefficients are displayed graphically in the forest plot (Figure 3).
Table 2. Univariate and multivariate analyses of independent factors influencing mortality in patients with uterine carcinosarcoma based on 11,338 patients with uterine carcinosarcoma from the Surveillance Epidemiology and End Results (SEER) database (2000–2020).
Table 2. Univariate and multivariate analyses of independent factors influencing mortality in patients with uterine carcinosarcoma based on 11,338 patients with uterine carcinosarcoma from the Surveillance Epidemiology and End Results (SEER) database (2000–2020).
Univariate AnalysisMultivariate Analysis
VariablesHazard Ratio
(95% CI)		p ValueHazard Ratio
(95% CI)		p Value
Age≤65 years1 (reference)1 (reference)1 (reference)1 (reference)
>65 years1.6 (1.5–1.7)<0.001 *1.36 (1.26–1.45)<0.001 *
RaceBlack1.3 (1.2–1.4)<0.001 *1.14 (1.01–1.28)0.03 *
Tumor Size<2 cm1 (reference)1 (reference)1 (reference)1 (reference)
2–4 cm0.93 (0.78–1.12)0.431.06 (0.87–1.29)0.60
>4 cm1.61 (1.37–1.89)<0.001 *1.46 (1.21–1.75)<0.001 *
Tumor StageLocalized0.23 (0.22–0.25)<0.001 *0.47 (0.27–0.78)0.03 **
Regional0.45 (0.42–0.48)<0.001 *1 (reference)1 (reference)
Distant1 (reference)1 (reference)2.08 (1.00–6.78)0.04 *
Tumor SiteEndometrium1 (reference)1 (reference)1 (reference)1 (reference)
Corpus Uteri1.32 (1.06–1.47)<0.001 *1.10 (0.54–1.57)0.77
Myometrium1.25 (1.21–1.43)0.007 *1.04 (0.51–1.58)0.71
Nodal StatusNegative1 (reference)1 (reference)1 (reference)1 (reference)
Positive2.22 (2.08–2.37)<0.0011.46 (1.33–1.61)<0.001 *
Treatment ModalityChemotherapy and Radiation1 (reference)1 (reference)1 (reference)1 (reference)
Radiation therapy and Surgery0.83 (0.77–0.89)<0.001 **0.89 (0.81–0.97)<0.001 **
Surgery only1.18 (1.11–1.26)<0.001 *1.72 (1.55–1.92)<0.001 *
Multimodal Therapy0.58 (0.54–0.62)<0.001 **0.82 (0.74–0.92)<0.001 **
No Treatment4.84 (4.36–5.36)<0.001 *5.85 (2.39–14.30)<0.001 *
* = associated with increased mortality. ** = associated with decreased mortality.
To further investigate the effect of race on mortality, we performed propensity score matching. The Black and White patients were matched based on demographic, tumor, and treatment factors that were found to have a significant effect on survival via multivariate analysis: age, tumor stage, tumor size, and treatment. Propensity score matching confirmed that Black patients had significantly increased mortality (p < 0.001).

3.8. Prognostic Nomogram

To create a predictive measure that could predict the survival of patients with uterine carcinosarcoma, a prognostic nomogram was created to measure patient survival using the factors of age and treatment. The nomogram visually represents the predictive model by assigning a numerical score to each variable based on its relative contribution to the overall prognosis. These scores are then summed to generate a total point value, which correlates with the predicted probability or risk of the defined outcome, which is overall survival (OS). The prognostic nomogram showed increased mortality for older patients. In addition, the prognostic nomogram predicted increased mortality for patients with tumors greater than 4 cm in size. Distant metastases were associated with a significantly increased probability of death, whereas regional metastases were associated with a moderate increase in mortality. The prognostic nomogram revealed a significant increase in mortality probability for patients who received no treatment and a decrease in mortality for patients who received multimodal treatment (Figure 4).

4. Discussion

This study examined cases of uterine carcinosarcoma from the SEER database, with an emphasis on demographic, clinical, and pathological variables and a view toward identifying racial disparities that may be present. Black race, a tumor size > 4 cm, and distant metastases were associated with a worse CSS. Overall, patients who received multimodal treatment (chemotherapy, radiation, and surgery) or surgery with adjuvant radiation had the best CSS.
The median age at diagnosis was 68 years, consistent with the findings of previous studies [13]. The average age at diagnosis decreased from 71.7 years in 1989 to 67.0 years in 2013, largely due to an increase in disease incidence among women aged 60–69 years [12]. UCS staging trends have also shown an increase in lymph node involvement from 6.9% to 28.7% from 1988 to 2016, with a concomitant decrease in the rates of distant metastasis, possibly due to enhanced utilization of lymphadenectomy at the time of hysterectomy [12]. Historically, UCS is diagnosed at later stages and follows a bimodal distribution, as illustrated in a 2003–2011 National Cancer Database analysis, where 42.9% of cases were stage I, 9.2% were stage II, 29.1% were stage III, and 18.8% were stage IV [13,14]. However, in our study, most cases were localized (35.4%) or regional (42.2%), with fewer distant cases (22.4%). The rates of distant metastasis in UCS patients declined significantly from 1988 to 2014, potentially due to improved endometrial sampling leading to earlier diagnosis [1]. Epithelial metaplasia is more common in patients with distant metastasis, while sarcomatous metaplasia prevails in patients with localized tumors [1]. Previous studies reported >10% distant metastasis rates, primarily to the lungs; our study showed similar rates (8.9%) with metastases in the lungs, liver, bone, and brain.
Studies have demonstrated that Black patients experience more than double the age-adjusted disease incidence of UCS compared to non-Black patients (2.9 vs. 0.8–1.2 per 100,000) [12,15,16]. In our study, Black patients comprised 23.6% of the patients, despite representing only 13% of the U.S. population. Race and ethnicity also impact uterine corpus cancer outcomes, with Black patients facing higher mortality rates due to a combination of histopathologic and socioeconomic factors, including aggressive histologic subtypes, later-stage diagnosis, idiosyncratic gene expression patterns, decreased healthcare access, failure to receive standard-of-care, and greater comorbidities [15,17,18,19,20]. Mortality disparities have been linked to tumor subtypes and advanced staging rather than to race alone, as studies have shown no significant association between race and survival in cohorts who receive similar treatment regimens when stage and histologic subtype are corrected [21]. A prior SEER analysis revealed that Black patients were less likely to undergo surgery than White patients with the same uterine cancer stage [22]. Black patients also exhibited lower responsiveness to chemotherapy than White patients did (34.9% vs. 43.2%) in multiple trials [19]. Despite representing approximately 30% of the U.S. population, Hispanic and Black patients comprise less than 6% of all federally funded clinical trials, which may account for the decreased effectiveness of certain molecular and chemotherapeutic agents in this population [23]. These findings suggest that addressing race as a risk factor and ensuring inclusivity in clinical trials are crucial for improving outcomes in UCS patients.
Because UCS is relatively rare, there is no standardized treatment approach. UCS management is multimodal and typically involves surgery followed by radiation and/or chemotherapy. Surgery, which is recommended for the staging and treatment of both local and regional diseases, may include radical hysterectomy, bilateral salpingo-oophorectomy, and lymphadenectomy [1,13]. In our study, 92.3% of patients with known treatment status underwent surgery, often with adjuvant radiation, chemotherapy, or both.
The benefits of adjuvant radiation therapy for uterine sarcoma are a matter of debate. In a previous SEER study of uterine sarcomas, surgery alone had better five-year overall survival rates than surgery with radiation in patients with localized disease (74.4% vs. 66.4%). Conversely, in regional disease, patients who underwent surgery with radiation had slightly better five-year overall survival than those who underwent surgery alone (36.2% vs. 35.4%) [24]. We found that 5-year survival rates did not differ significantly between patients with localized disease who underwent surgery only and those who underwent surgery and radiation (50.3% vs. 55.4%). However, compared with surgery alone, adjuvant radiation significantly improved the 1-year and 5-year survival rates of patients with regional or distant disease. This suggests that adjuvant radiation may only be beneficial for patients with uterine carcinosarcoma in later stages of disease.
Currently, the recommended first-line chemotherapy agent for UCS is carboplatin/paclitaxel, which was recently shown to have a better toxicity profile and noninferiority than ifosfamide/paclitaxel [13]. Our study revealed that compared with surgery alone, adjuvant chemotherapy significantly improved 1- and 5-year survival in patients with all disease stages. In patients with distant disease, the combination of chemotherapy and surgery had similar 5-year survival rates to the combination of radiation and surgery and multimodal treatment. This suggests that adjuvant therapy with chemotherapy, radiation, or both is important for improving survival in patients with distant disease. Ultimately, the five-year cause-specific survival rate of UCS patients in this study was 38.7%, which is worse than that of patients with adenosarcoma, stromal sarcoma, or leiomyosarcoma. This dismal prognosis emphasizes the importance of investigating novel treatment approaches to improve survival outcomes [24]. Studies have shown that incomplete cytoreduction, residual cancer, larger tumor size and advanced disease are associated with a decrease in survival in uterine carcinomas [25].
The molecular characteristics of UCS vary due to the heterogeneous nature of these tumors. The most frequently occurring mutations include those in TP53, PTEN, FBXW7, PIK3CA, KRAS, and ARID1A [26]. Spontaneous TP53 mutations are believed to play a key role in early carcinoma development and are found in 62–91% of UCS tumors, depending on the proportion of high-grade tumors included in each study [1,26,27]. Unlike other endometrial cancers, many UCS tumors contain simultaneous TP53 and PTEN mutations [26,28]. PTEN mutations are themselves found in 18–41% of UCS samples and may be associated with a loss of genes necessary for DNA mismatch repair [26,29]. Mutations in the FBXW7 tumor suppressor gene are also found in 19–39% of tumor samples [26]. In one preclinical study, inactivating mutations in PTEN and FBXW7 led to the formation of well-differentiated endometrioid adenocarcinomas, which subsequently developed into uterine carcinosarcomas [27]. Further genetic analysis revealed that most of the examined tumors acquired a TP53 mutation, suggesting that defects in the triad of the FBX27, PTEN, and TP53 pathways are synergistic and critical to the epithelial-to-mesenchymal transition that UCS is hypothesized to undergo [27].
Several novel therapies are currently under investigation as second-line treatments for UCS. Epidermal growth factor receptor 2 (HER2) is overexpressed in 10–35% of UCS patients, making this receptor a potential therapeutic target [30,31]. Several preclinical studies have investigated agents targeting HER2. First, trastuzumab-emtansine (a HER2-targeting immunotoxin) was more effective than trastuzumab alone in inducing cell cycle arrest and inhibiting tumor cell proliferation in HER2-positive cell lines [32]. In another study, the anti-HER2 antibody-drug conjugate SYD985 exhibited an even stronger antitumor effect on HER2-overexpressing cell lines than trastuzumab-emtansine [33]. In clinical trials, the addition of trastuzumab to carboplatin/paclitaxel in women with HER2-positive uterine serous adenocarcinoma significantly improved progression-free survival compared to carboplatin/paclitaxel alone [34]. Due to the similar tumor biology between UCS and serous adenocarcinoma, these findings suggest a possible role for trastuzumab in the treatment of HER2-positive UCS [12].
Transforming growth factor beta (TGF-β) is another potential drug target due to its key role in cellular differentiation and proliferation, motility, apoptosis, and epithelial-to-mesenchymal transition [12]. Galunisertib, a small-molecule inhibitor of TGF-B receptor 1 kinase, was shown to reduce cell viability, differentiation, growth, and invasion while sensitizing UCS cells to chemotherapy in vivo [35]. A phase Ib clinical trial is currently investigating the combination of galunisertib and carboplatin/paclitaxel in women with newly diagnosed, persistent, or recurrent gynecologic carcinosarcoma [12].
Immune checkpoint inhibitors are another class of drugs with the potential to treat UCS, specifically tumors with a high mutational burden or programmed cell death protein (PD-1)/programmed death ligand 1 (PD-L1) overexpression [1]. There are very few cases of UCS treated with immune checkpoint inhibitors owing to its rarity. Pembrolizumab, an anti-PD-1 monoclonal antibody, has been shown to successfully treat two cases of UCS [36,37]. The combination of pembrolizumab and lenvatinib, a tyrosine kinase inhibitor, showed promising antitumor activity in women with advanced endometrial cancer, and while this study did not report any cases of UCS, it did include 35 cases of serous adenocarcinoma [38]. This drug combination is currently FDA-approved for treating endometrial carcinoma that is microsatellite-stable and not mismatch repair-deficient [26]. Another anti-PD-1 monoclonal antibody, nivolumab, improved progression-free survival in a sample of 42 patients with pretreated mismatch repair-deficient cancers, including four patients with UCS [39]. Several clinical trials are currently evaluating immune checkpoint inhibitors for the treatment of UCS specifically and advanced uterine corpus cancer in general [26].

5. Conclusions

In this study of uterine carcinosarcoma from the SEER database, one of the largest to date, increased mortality was associated with age > 65 years, Black race, tumor size > 4 cm, and distant staging. Patients treated with combination therapy (surgery with adjuvant chemoradiation) had better 5-year overall survival rates than those treated with chemotherapy or surgery alone. Many novel drugs targeting the unique molecular characteristics of specific tumor subtypes are under investigation as potential adjuvant therapies for UCS. To better understand these potential targeted therapies, information on the molecular characteristics and genomic profiles of UCS neoplasms should be included in national databases. Continued efforts should be made to ensure that Black patients and other marginalized racial and ethnic groups are included in national clinical trials for UCS, as they are disproportionately affected by UCS.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/surgeries5030059/s1, Figure S1: Exclusion Flowchart describing the filtering of Uterine Carcinosarcoma cases; Figure S2: Overall (A) and Cause-Specific (B) Kaplan Meier Survival Curves for of 11,338 patients with Uterine Carcinosarcoma from the Surveillance Epidemiology and End Result (SEER) Database (2000–2020); Figure S3: Survival by Housing location; Figure S4: Survival by Tumor Size; Table S1: Overall and Cause-Specific Survival; Table S2: Survival by Age; Table S3: Survival by Race; Table S4: Survival by Stage; Table S5: Survival by Tumor Size; Table S6: Survival by Treatment Modality; Table S7: Survival by Stage for Therapy; Table S8: Survival by Tumor Stage comparing Black and White patients.

Author Contributions

A.U., M.R., T.P. and A.H.S.: Conceptualization, Methodology, Software. A.Q.K.Y., A.C. and B.T.: Data curation, Writing—Original draft preparation. A.U., A.W. (Abdul Waheed), A.G. and R.K.: Visualization, Investigation. A.Q.K.Y., L.R., A.R., L.B., A.I., A.W. (Agha Wali) and A.B.S.: Supervision. A.U., T.P., L.B., M.R., A.W. (Abdul Waheed) and L.R.: Software, Validation. R.K., A.C., A.R. and A.U.: Writing—Reviewing and Editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

All data are publicly available, and no IRB is required.

Informed Consent Statement

Patient consent was waived due to this article being from SEER database, which are publicly available deidentified patient data from National Cancer Institute (NCI), USA.

Data Availability Statement

All data are publicly available.

Acknowledgments

This study is an extension of our previous work on uterine carcinosarcoma in Cureus titled ‘Carcinosarcoma of the Uterus: A Study From the Surveillance Epidemiology and End Result (SEER) Database’.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Pezzicoli, G.; Moscaritolo, F.; Silvestris, E.; Silvestris, F.; Cormio, G.; Porta, C.; D’oronzo, S. Uterine carcinosarcoma: An overview. Crit. Rev. Oncol. Hematol. 2021, 163, 103369. [Google Scholar] [CrossRef] [PubMed]
  2. Singh, R. Review literature on uterine carcinosarcoma. J. Cancer Res. Ther. 2014, 10, 461–468. [Google Scholar] [CrossRef] [PubMed]
  3. Ravishankar, P.; Smith, D.A.; Avril, S.; Kikano, E.; Ramaiya, N.H. Uterine carcinosarcoma: A primer for radiologists. Abdom. Radiol. 2019, 44, 2874–2885. [Google Scholar] [CrossRef] [PubMed]
  4. Rose, P.G.; Piver, M.S.; Tsukada, Y.; Lau, T. Patterns of metastasis in uterine sarcoma. An autopsy study. Cancer 1989, 63, 935–938. [Google Scholar] [CrossRef] [PubMed]
  5. Ho, K.-C.; Lai, C.-H.; Wu, T.-I.; Ng, K.-K.; Yen, T.-C.; Lin, G.; Chang, T.-C.; Wang, C.-C.; Hsueh, S.; Huang, H.-J. 18F-fluorodeoxyglucose positron emission tomography in uterine carcinosarcoma. Eur. J. Nucl. Med. Mol. Imaging 2008, 35, 484–492. [Google Scholar] [CrossRef] [PubMed]
  6. Zwahlen, D.R.; Schick, U.; Bolukbasi, Y.; Thariat, J.; Abdah-Bortnyak, R.; Kuten, A.; Igdem, S.; Caglar, H.; Ozsaran, Z.; Loessl, K.; et al. Outcome and predictive factors in uterine carcinosarcoma using postoperative radiotherapy: A rare cancer network study. Rare Tumors 2016, 8, 42–48. [Google Scholar] [CrossRef] [PubMed]
  7. Zelmanowicz, A.; Hildesheim, A.; Sherman, M.E.; Sturgeon, S.R.; Kurman, R.J.; Barrett, R.J.; Berman, M.L.; Mortel, R.; Twiggs, L.B.; Wilbanks, G.D.; et al. Evidence for a common etiology for endometrial carcinomas and malignant mixed mullerian tumors. Gynecol. Oncol. 1998, 69, 253–257. [Google Scholar] [CrossRef] [PubMed]
  8. Schwartz, S.M.; Weiss, N.S.; Daling, J.R.; Gammon, M.D.; Liff, J.M.; Watt, J.; Lynch, C.F.; Newcomb, P.A.; Armstrong, B.K.; Thompson, W.D. Exogenous sex hormone use, correlates of endogenous hormone levels, and the incidence of histologic types of sarcoma of the uterus. Cancer 1996, 77, 717–724. [Google Scholar] [CrossRef]
  9. Varela-Duran, J.; Nochomovitz, L.E.; Prem, K.A.; Dehner, L.P. Postirradiation mixed müllerian tumors of the uterus: A comparative clinicopathologic study. Cancer 1980, 45, 1625–1631. [Google Scholar] [CrossRef] [PubMed]
  10. Rojas, C.; Tian, C.; Powell, M.A.; Chan, J.K.; Bateman, N.W.; Conrads, T.P.; Rocconi, R.P.; Jones, N.L.; Shriver, C.D.; Hamilton, C.A.; et al. Racial disparities in uterine and ovarian carcinosarcoma: A population-based analysis of treatment and survival. Gynecol. Oncol. 2020, 157, 67–77. [Google Scholar] [CrossRef] [PubMed]
  11. McCluggage, W.G. Uterine carcinosarcomas (malignant mixed Mullerian tumors) are metaplastic carcinomas. Int. J. Gynecol. Cancer Off. J. Int. Gynecol. Cancer Soc. 2002, 12, 687–690. [Google Scholar] [CrossRef] [PubMed]
  12. Matsuzaki, S.; Klar, M.; Matsuzaki, S.; Roman, L.D.; Sood, A.K.; Matsuo, K. Uterine carcinosarcoma: Contemporary clinical summary, molecular updates, and future research opportunity. Gynecol. Oncol. 2021, 160, 586–601. [Google Scholar] [CrossRef] [PubMed]
  13. Bogani, G.; Ray-Coquard, I.; Concin, N.; Ngoi, N.Y.L.; Morice, P.; Caruso, G.; Enomoto, T.; Takehara, K.; Denys, H.; Lorusso, D.; et al. Endometrial carcinosarcoma. Int. J. Gynecol. Cancer 2023, 33, 147–174. [Google Scholar] [CrossRef] [PubMed]
  14. Rauh-Hain, J.A.; Starbuck, K.D.; Meyer, L.A.; Clemmer, J.; Schorge, J.O.; Lu, K.H.; del Carmen, M.G. Patterns of care, predictors and outcomes of chemotherapy for uterine carcinosarcoma: A National Cancer Database analysis. Gynecol. Oncol. 2015, 139, 84–89. [Google Scholar] [CrossRef] [PubMed]
  15. Henley, S.J.; Miller, J.W.; Dowling, N.F.; Benard, V.B.; Richardson, L.C. Uterine cancer incidence and mortality—United States, 1999–2016. MMWR Morb. Mortal. Wkly. Rep. 2018, 67, 1333–1338. [Google Scholar] [CrossRef] [PubMed]
  16. Sherman, M.E.; Devesa, S.S. Analysis of racial differences in incidence, survival, and mortality for malignant tumors of the uterine corpus. Cancer 2003, 98, 176–186. [Google Scholar] [CrossRef] [PubMed]
  17. Paterniti, T.A.; Schrader, E.A.; Deibert, E.; Wilkinson, E.A.; Ahmad, S. Changing Trends in the Epidemiology of Endometrial Cancer. In Recent Advances in Endometrial Cancer; Mehta, S., Gupta, B., Eds.; Springer: Singapore, 2020. [Google Scholar]
  18. Allard, J.E.; Maxwell, G.L. Race disparities between black and white women in the incidence, treatment, and prognosis of endometrial cancer. Cancer Control 2009, 16, 53–56. [Google Scholar] [CrossRef] [PubMed]
  19. Maxwell, G.L.; Tian, C.; Risinger, J.; Brown, C.L.; Rose, G.S.; Thigpen, J.T.; Fleming, G.F.; Gallion, H.H.; Brewster, W.R. Racial disparity in survival among patients with advanced/recurrent endometrial adenocarcinoma: A Gynecologic Oncology Group study. Cancer 2006, 107, 2197–2205. [Google Scholar] [CrossRef] [PubMed]
  20. Yap, O.W.; Matthews, R.P. Racial and ethnic disparities in cancers of the uterine corpus. J. Natl. Med. Assoc. 2006, 98, 1930–1933. [Google Scholar] [PubMed]
  21. Smotkin, D.; Nevadunsky, N.S.; Harris, K.; Einstein, M.H.; Yu, Y.; Goldberg, G.L. Histopathologic differences account for racial disparity in uterine cancer survival. Gynecol. Oncol. 2012, 127, 616–619. [Google Scholar] [CrossRef] [PubMed]
  22. Randall, T.C.; Armstrong, K. Differences in treatment and outcome between African-American and white women with endometrial cancer. J. Clin. Oncol. 2003, 21, 4200–4206. [Google Scholar] [CrossRef] [PubMed]
  23. Baskovic, M.; Lichtensztajn, D.Y.; Nguyen, T.; Karam, A.; English, D.P. Racial disparities in outcomes for high-grade uterine cancer: A California cancer registry study. Cancer Med. 2018, 7, 4485–4495. [Google Scholar] [CrossRef] [PubMed]
  24. Hosh, M.; Antar, S.; Nazzal, A.; Warda, M.; Gibreel, A.; Refky, B. Uterine Sarcoma: Analysis of 13,089 Cases Based on Surveillance, Epidemiology, and End Results Database. Int. J. Gynecol. Cancer 2016, 26, 1098–1104. [Google Scholar] [CrossRef] [PubMed]
  25. Gracia, M.; Yildirim, Y.; Macuks, R.; Mancari, R.; Achimas-Cadariu, P.; Polterauer, S.; Iacoponi, S.; Zapardiel, I. Influence of Clinical and Surgical Factors on Uterine Carcinosarcoma Survival. Cancers 2023, 15, 1463. [Google Scholar] [CrossRef] [PubMed]
  26. Nakad Borrego, S.; Lengyel, E.; Kurnit, K.C. Molecular Characterizations of Gynecologic Carcinosarcomas: A Focus on the Immune Microenvironment. Cancers 2022, 14, 4465. [Google Scholar] [CrossRef] [PubMed]
  27. Cuevas, I.C.; Sahoo, S.S.; Kumar, A.; Zhang, H.; Westcott, J.; Aguilar, M.; Cortez, J.D.; Sullivan, S.A.; Xing, C.; Hayes, D.N.; et al. Fbxw7 is a driver of uterine carcinosarcoma by promoting epithelial–mesenchymal transition. Proc. Natl. Acad. Sci. USA 2019, 116, 25880–25890. [Google Scholar] [CrossRef] [PubMed]
  28. Cherniack, A.D.; Shen, H.; Walter, V.; Stewart, C.; Murray, B.A.; Bowlby, R.; Hu, X.; Ling, S.; Soslow, R.A.; Broaddus, R.R.; et al. Integrated Molecular Characterization of Uterine Carcinosarcoma. Cancer Cell 2017, 31, 411–423. [Google Scholar] [CrossRef]
  29. De Jong, R.A.; Nijman, H.W.; Wijbrandi, T.F.; Reyners, A.K.L.; Boezen, H.M.; Hollema, H. Molecular markers and clinical behavior of uterine carcinosarcomas: Focus on the epithelial tumor component. Mod. Pathol. 2011, 24, 1368–1379. [Google Scholar] [CrossRef] [PubMed]
  30. Rottmann, D.; Snir, O.L.; Wu, X.; Wong, S.; Hui, P.; Santin, A.D.; Buza, N. HER2 testing of gynecologic carcinosarcomas: Tumor stratification for potential targeted therapy. Mod. Pathol. 2020, 33, 118–127. [Google Scholar] [CrossRef] [PubMed]
  31. Buza, N.; English, D.P.; Santin, A.D.; Hui, P. Toward standard HER2 testing of endometrial serous carcinoma: 4-year experience at a large academic center and recommendations for clinical practice. Mod. Pathol. 2013, 26, 1605–1612. [Google Scholar] [CrossRef] [PubMed]
  32. Nicoletti, R.; Lopez, S.; Bellone, S.; Cocco, E.; Schwab, C.L.; Black, J.D.; Centritto, F.; Zhu, L.; Bonazzoli, E.; Buza, N.; et al. T-DM1, a novel antibody-drug conjugate, is highly effective against uterine and ovarian carcinosarcomas overexpressing HER2. Clin. Exp. Metastasis 2015, 32, 29–38. [Google Scholar] [CrossRef] [PubMed]
  33. Menderes, G.; Bonazzoli, E.; Bellone, S.; Black, J.; Predolini, F.; Pettinella, F.; Masserdotti, A.; Zammataro, L.; Altwerger, G.; Buza, N.; et al. SYD985, a Novel Duocarmycin-Based HER2-Targeting Antibody-Drug Conjugate, Shows Antitumor Activity in Uterine and Ovarian Carcinosarcoma with HER2/Neu Expression. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2017, 23, 5836–5845. [Google Scholar] [CrossRef] [PubMed]
  34. Fader, A.N.; Roque, D.M.; Siegel, E.; Buza, N.; Hui, P.; Abdelghany, O.; Chambers, S.K.; Secord, A.A.; Havrilesky, L.; O’malley, D.M.; et al. Randomized Phase II Trial of Carboplatin-Paclitaxel Versus Carboplatin-Paclitaxel-Trastuzumab in Uterine Serous Carcinomas That Overexpress Human Epidermal Growth Factor Receptor 2/neu. J. Clin. Oncol. 2018, 36, 2044–2051. [Google Scholar] [CrossRef] [PubMed]
  35. Dhar Dwivedi, S.K.; McMeekin, S.D.; Slaughter, K.; Bhattacharya, R. Role of TGF-β signaling in uterine carcinosarcoma. Oncotarget 2015, 6, 14646–14655. [Google Scholar] [CrossRef] [PubMed]
  36. Bhangoo, M.S.; Boasberg, P.; Mehta, P.; Elvin, J.A.; Ali, S.M.; Wu, W.; Klempner, S.J. Tumor Mutational Burden Guides Therapy in a Treatment Refractory POLE-Mutant Uterine Carcinosarcoma. Oncologist 2018, 23, 518–523. [Google Scholar] [CrossRef] [PubMed]
  37. Yano, M.; Aso, S.; Sato, M.; Aoyagi, Y.; Matsumoto, H.; Nasu, K. Pembrolizumab and Radiotherapy for Platinum-refractory Recurrent Uterine Carcinosarcoma With an Abscopal Effect: A Case Report. Anticancer. Res. 2020, 40, 4131–4135. [Google Scholar] [CrossRef] [PubMed]
  38. Makker, V.; Taylor, M.H.; Aghajanian, C.; Oaknin, A.; Mier, J.; Cohn, A.L.; Romeo, M.; Bratos, R.; Brose, M.S.; DiSimone, C.; et al. Lenvatinib Plus Pembrolizumab in Patients With Advanced Endometrial Cancer. J. Clin. Oncol. 2020, 38, 2981–2992. [Google Scholar] [CrossRef] [PubMed]
  39. Azad, N.S.; Gray, R.J.; Overman, M.J.; Schoenfeld, J.D.; Mitchell, E.P.; Zwiebel, J.A.; Sharon, E.; Streicher, H.; Li, S.; McShane, L.M.; et al. Nivolumab Is Effective in Mismatch Repair-Deficient Noncolorectal Cancers: Results From Arm Z1D-A Subprotocol of the NCI-MATCH (EAY131) Study. J. Clin. Oncol. 2020, 38, 214–222. [Google Scholar] [CrossRef]
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Figure 1. Treatment modalities used to treat 11,338 patients with uterine carcinosarcoma from the Surveillance Epidemiology and End Results (SEER) database, 2000–2020.
Figure 1. Treatment modalities used to treat 11,338 patients with uterine carcinosarcoma from the Surveillance Epidemiology and End Results (SEER) database, 2000–2020.
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Figure 2. Kaplan–Meier survival curves for 11,338 patients with uterine carcinosarcoma from the Surveillance Epidemiology and End Results (SEER) database (2000–2020), stratified by age (A), race (B), treatment modality (C), and metastasis (D).
Figure 2. Kaplan–Meier survival curves for 11,338 patients with uterine carcinosarcoma from the Surveillance Epidemiology and End Results (SEER) database (2000–2020), stratified by age (A), race (B), treatment modality (C), and metastasis (D).
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Figure 3. Forest plot depicting multivariate analysis for statistically significant variables affecting survival in 11,338 patients with uterine carcinosarcoma from the Surveillance Epidemiology and End Results (SEER) Database (2000–2020).
Figure 3. Forest plot depicting multivariate analysis for statistically significant variables affecting survival in 11,338 patients with uterine carcinosarcoma from the Surveillance Epidemiology and End Results (SEER) Database (2000–2020).
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Figure 4. Prognostic nomogram indicating survival in 11,338 patients with uterine carcinosarcoma from the Surveillance Epidemiology and End Results (SEER) database (2000–2020).
Figure 4. Prognostic nomogram indicating survival in 11,338 patients with uterine carcinosarcoma from the Surveillance Epidemiology and End Results (SEER) database (2000–2020).
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Table 1. Demographic, socioeconomic, and tumor characteristics of 11,338 patients with uterine carcinosarcoma from the Surveillance Epidemiology and End Results (SEER) database, 2000–2020.
Table 1. Demographic, socioeconomic, and tumor characteristics of 11,338 patients with uterine carcinosarcoma from the Surveillance Epidemiology and End Results (SEER) database, 2000–2020.
Variable (n = 11,338)Frequency (%)
Age (years)≤65 years4717 (41.7%)
>65 years6603 (58.3%)
RaceWhite6679 (58.9%)
Black2445 (21.5%)
Asian or Pacific Islander837 (7.4%)
Native American or Alaska Native70 (0.6%)
Hispanic (All Races)1276 (11.3%)
Unknown31 (0.3%)
Rural-Urban ContinuumUrban10,065 (88.9%)
Rural1263 (11.1%)
Income<USD 75,0006392 (56.4%)
USD 75,000+4946 (43.6%)
Tumor SiteEndometrium NOS10,324 (90.9%)
Fundus Uteri156 (1.4%)
Corpus Uteri808 (7.1%)
Isthmus Uteri50 (0.4%)
Tumor SizeKnown7613 (67.1%)
Unknown3725 (32.9%)
Size where known (n = 7613)
<2 cm319 (4.2%)
2–4 cm5762 (75.7%)
>4 cm1532 (20.1%)
Tumor StageKnown8934 (78.8%)
Unknown2404 (21.2%)
Stage where known (n = 8934)
Localized3162 (35.4%)
Regional3769 (42.2%)
Distant2003 (22.4%)
Lymph Node StatusKnown7550 (66.6%)
Unknown3788 (33.4%)
Status where known (n = 7550)
Positive2066 (27.4%)
Negative5484 (72.6%)
AJCC TNM classificationKnown6995 (61.7%)
Unknown4343 (38.3%)
T ClassificationT03 (0.04%)
T1244 (3.5%)
T1a1992 (28.5%)
T1b1214 (17.4%)
T1c183 (2.6%)
T2599 (8.6%)
T2a54 (0.8%)
T2b101 (1.4%)
T354 (0.7%)
T3a1065 (15.2%)
T3b742 (10.6%)
T4411 (5.9%)
Tx333 (4.8%)
N ClassificationN04922 (58.2%)
N1977 (14.0%)
N1a153 (2.2%)
N2409 (6.1%)
N2a105 (1.5%)
NX348 (5.0%)
M ClassificationM05541 (79.2%)
M11396 (20.0%)
MX58 (0.8%)
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Ullah, A.; Rubin, L.; Rakusin, A.; Yasinzai, A.Q.K.; Chandasir, A.; Sohail, A.H.; Iqbal, A.; Waheed, A.; Khan, R.; Brandi, L.; et al. Prognostic Nomogram for Predicting Survival, Clinicopathological Analysis, and Racial Disparities in Uterine Carcinosarcoma: A Retrospective Population-Based Study. Surgeries 2024, 5, 743-757. https://doi.org/10.3390/surgeries5030059

AMA Style

Ullah A, Rubin L, Rakusin A, Yasinzai AQK, Chandasir A, Sohail AH, Iqbal A, Waheed A, Khan R, Brandi L, et al. Prognostic Nomogram for Predicting Survival, Clinicopathological Analysis, and Racial Disparities in Uterine Carcinosarcoma: A Retrospective Population-Based Study. Surgeries. 2024; 5(3):743-757. https://doi.org/10.3390/surgeries5030059

Chicago/Turabian Style

Ullah, Asad, Lily Rubin, Alexa Rakusin, Abdul Qahar Khan Yasinzai, Abdullah Chandasir, Amir Humza Sohail, Asif Iqbal, Abdul Waheed, Roona Khan, Luis Brandi, and et al. 2024. "Prognostic Nomogram for Predicting Survival, Clinicopathological Analysis, and Racial Disparities in Uterine Carcinosarcoma: A Retrospective Population-Based Study" Surgeries 5, no. 3: 743-757. https://doi.org/10.3390/surgeries5030059

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