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Shi XL, Chen S, Guo GD, Yang YL, Tong KM, Cao W, Huang LL, Zhang YR. Precise lymph node biopsy for endometrial cancer confined to the uterus: Analysis of 43 clinical cases. Taiwan J Obstet Gynecol 2024; 63:369-374. [PMID: 38802200 DOI: 10.1016/j.tjog.2023.11.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/18/2023] [Indexed: 05/29/2024] Open
Abstract
OBJECTIVE To explore a precise association between tumor location and lymph node (LN) biopsy algorithm in uterine confined endometrial cancer (EC). MATERIALS AND METHODS Patients with EC treated in the Department of Obstetrics and Gynecology, South Branch of Fujian Provincial Hospital were included in this observational retrospective study. Based on the procedure of treatment, patients were separated to stage I (2015.07-2019.09) and stage II (2019.09-2021.9). In each stage, patients were separated to high and low-risk group by the predicted results. Patients in the high-risk group received systematic lymphadenectomy in stage I and sentinel lymph node (SLN) dissection in stage II. The efficiency of lymph node metastasis (LNM) detection rates was compared between stage I and stage II cases. Precise lymph node biopsy algorithm was also constructed based on the outcomes of stage II. RESULTS Overall, 43 patients, 28 in stage I and 15 in stage II, were included in the study. No recurrence or death cases had been found within follow-up terms. Based on the difference in the detection efficiency of LNM (p > 0.05), there was no difference between two stages. Thus, systematic lymphadenectomy and SLN biopsy provided similar success rates. The location of tumor site was also important for deciding whether pelvic or para-aortic SLN should be sampled for LNM. CONCLUSIONS Precise SLN biopsy for EC confined to the uterus showed comparable LNM detection rate as systematic lymphadenectomy. EC location may be used to determine whether pelvic or para-aortic SLN sampling should be conducted for treatment.
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Affiliation(s)
- Xiao-Long Shi
- Provincial Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, 350001, PR China; Department of Obstetrics and Gynecology, Fujian Provincial Hospital, Fuzhou, Fujian Province, 350001, PR China.
| | - Shuo Chen
- Provincial Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, 350001, PR China; Department of Obstetrics and Gynecology, Fujian Provincial Hospital, Fuzhou, Fujian Province, 350001, PR China
| | - Guo-Dong Guo
- Provincial Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, 350001, PR China; Department of Obstetrics and Gynecology, Fujian Provincial Hospital, Fuzhou, Fujian Province, 350001, PR China
| | - Yun-Ling Yang
- Provincial Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, 350001, PR China; Department of Obstetrics and Gynecology, Fujian Provincial Hospital, Fuzhou, Fujian Province, 350001, PR China
| | - Kang-Mei Tong
- Provincial Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, 350001, PR China; Department of Obstetrics and Gynecology, Fujian Provincial Hospital, Fuzhou, Fujian Province, 350001, PR China
| | - Wen Cao
- Provincial Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, 350001, PR China; Department of Obstetrics and Gynecology, Fujian Provincial Hospital, Fuzhou, Fujian Province, 350001, PR China
| | - Lin-Lin Huang
- Provincial Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, 350001, PR China; Department of Obstetrics and Gynecology, Fujian Provincial Hospital, Fuzhou, Fujian Province, 350001, PR China
| | - Yan-Ru Zhang
- Provincial Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, 350001, PR China; Department of Obstetrics and Gynecology, Fujian Provincial Hospital, Fuzhou, Fujian Province, 350001, PR China
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Imai K, Hirooka-Nakama J, Hotta Y, Shigeta H. A Review of Laparoscopic Para-aortic Lymphadenectomy for Early-stage Endometrial Cancer: Extraperitoneal Approach May Have the Advantage over Intraperitoneal Approach. Gynecol Minim Invasive Ther 2024; 13:10-18. [PMID: 38487605 PMCID: PMC10936721 DOI: 10.4103/gmit.gmit_25_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 08/29/2023] [Accepted: 09/21/2023] [Indexed: 03/17/2024] Open
Abstract
The importance of lymphadenectomy, including para-aortic nodes, for the accurate staging of endometrial cancer, is well established. Although the therapeutic role of lymph node resection in endometrial cancer is still under debate, some studies support its usefulness for survival benefit. To predict the necessity of lymphadenectomy, several preoperative scoring systems have been proposed as being effective. For endometrial cancer, there is a trend towards minimally invasive surgery, including para-aortic lymphadenectomy. For para-aortic lymphadenectomy, there are two different approaches: the extraperitoneal approach and the transperitoneal approach. The extraperitoneal approach has advantages over the transperitoneal approach in terms of better access to the left aortic nodes, no interference of the bowel, and possibly better options for obese or elderly patients. However, the extraperitoneal approach may have a longer learning curve than the transperitoneal approach. Robot-assisted extraperitoneal para-aortic lymphadenectomy is feasible and safe and may be suitable for patients irrespective of their baseline characteristics.
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Affiliation(s)
- Kazuaki Imai
- Department of Obstetrics and Gynecology, Yokohama Municipal Citizen’s Hospital, Japan
| | - Junko Hirooka-Nakama
- Department of Obstetrics and Gynecology, Yokohama Municipal Citizen’s Hospital, Japan
| | - Yuichiro Hotta
- Department of Obstetrics and Gynecology, Yokohama Municipal Citizen’s Hospital, Japan
| | - Hiroyuki Shigeta
- Department of Obstetrics and Gynecology, Yokohama Municipal Citizen’s Hospital, Japan
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Ren Z, Chen B, Hong C, Yuan J, Deng J, Chen Y, Ye J, Li Y. The value of machine learning in preoperative identification of lymph node metastasis status in endometrial cancer: a systematic review and meta-analysis. Front Oncol 2023; 13:1289050. [PMID: 38173835 PMCID: PMC10761539 DOI: 10.3389/fonc.2023.1289050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 12/06/2023] [Indexed: 01/05/2024] Open
Abstract
Background The early identification of lymph node metastasis status in endometrial cancer (EC) is a serious challenge in clinical practice. Some investigators have introduced machine learning into the early identification of lymph node metastasis in EC patients. However, the predictive value of machine learning is controversial due to the diversity of models and modeling variables. To this end, we carried out this systematic review and meta-analysis to systematically discuss the value of machine learning for the early identification of lymph node metastasis in EC patients. Methods A systematic search was conducted in Pubmed, Cochrane, Embase, and Web of Science until March 12, 2023. PROBAST was used to assess the risk of bias in the included studies. In the process of meta-analysis, subgroup analysis was performed according to modeling variables (clinical features, radiomic features, and radiomic features combined with clinical features) and different types of models in various variables. Results This systematic review included 50 primary studies with a total of 103,752 EC patients, 12,579 of whom had positive lymph node metastasis. Meta-analysis showed that among the machine learning models constructed by the three categories of modeling variables, the best model was constructed by combining radiomic features with clinical features, with a pooled c-index of 0.907 (95%CI: 0.886-0.928) in the training set and 0.823 (95%CI: 0.757-0.890) in the validation set, and good sensitivity and specificity. The c-index of the machine learning model constructed based on clinical features alone was not inferior to that based on radiomic features only. In addition, logistic regression was found to be the main modeling method and has ideal predictive performance with different categories of modeling variables. Conclusion Although the model based on radiomic features combined with clinical features has the best predictive efficiency, there is no recognized specification for the application of radiomics at present. In addition, the logistic regression constructed by clinical features shows good sensitivity and specificity. In this context, large-sample studies covering different races are warranted to develop predictive nomograms based on clinical features, which can be widely applied in clinical practice. Systematic review registration https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023420774.
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Affiliation(s)
- Zhonglian Ren
- Department of Obstetrics and Gynecology, Chengdu Shuangliu Distract Maternal and Child Health Hospital, Chengdu, China
| | - Banghong Chen
- Data Science R&D Center of Yanchang Technology, Chengdu, China
| | - Changying Hong
- Department of Obstetrics and Gynecology, Chengdu Shuangliu Distract Maternal and Child Health Hospital, Chengdu, China
| | - Jiaying Yuan
- Department of Obstetrics and Gynecology, Chengdu Shuangliu Distract Maternal and Child Health Hospital, Chengdu, China
| | - Junying Deng
- Department of Obstetrics and Gynecology, Chengdu Shuangliu Distract Maternal and Child Health Hospital, Chengdu, China
| | - Yan Chen
- Department of Obstetrics and Gynecology, Chengdu Shuangliu Distract Maternal and Child Health Hospital, Chengdu, China
| | - Jionglin Ye
- Department of Obstetrics and Gynecology, Chengdu Shuangliu Distract Maternal and Child Health Hospital, Chengdu, China
| | - Yanqin Li
- Department of Obstetrics and Gynecology, Chengdu Shuangliu Distract Maternal and Child Health Hospital, Chengdu, China
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Feng X, Li XC, Yang X, Cheng Y, Dong YY, Wang JY, Zhou JY, Wang JL. Metabolic syndrome score as an indicator in a predictive nomogram for lymph node metastasis in endometrial cancer. BMC Cancer 2023; 23:622. [PMID: 37403054 DOI: 10.1186/s12885-023-11053-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 06/09/2023] [Indexed: 07/06/2023] Open
Abstract
BACKGROUND Lymph node metastasis (LNM) is an important factor affecting endometrial cancer (EC) prognosis. Current controversy exists as to how to accurately assess the risk of lymphatic metastasis. Metabolic syndrome has been considered a risk factor for endometrial cancer, yet its effect on LNM remains elusive. We developed a nomogram integrating metabolic syndrome indicators with other crucial variables to predict lymph node metastasis in endometrial cancer. METHODS This study is based on patients diagnosed with EC in Peking University People's Hospital between January 2004 and December 2020. A total of 1076 patients diagnosed with EC and who underwent staging surgery were divided into training and validation cohorts according to the ratio of 2:1. Univariate and multivariate logistic regression analyses were used to determine the significant predictive factors. RESULTS The prediction nomogram included MSR, positive peritoneal cytology, lymph vascular space invasion, endometrioid histological type, tumor size > = 2 cm, myometrial invasion > = 50%, cervical stromal invasion, and tumor grade. In the training group, the area under the curve (AUC) of the nomogram and Mayo criteria were 0.85 (95% CI: 0.81-0.90) and 0.77 (95% CI: 0.77-0.83), respectively (P < 0.01). In the validation group (N = 359), the AUC was 0.87 (95% CI: 0.82-0.93) and 0.80 (95% CI: 0.74-0.87) for the nomogram and the Mayo criteria, respectively (P = 0.01). Calibration plots revealed the satisfactory performance of the nomogram. Decision curve analysis showed a positive net benefit of this nomogram, which indicated clinical value. CONCLUSION This model may promote risk stratification and individualized treatment, thus improving the prognosis.
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Affiliation(s)
- Xuan Feng
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China
| | - Xing Chen Li
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China
| | - Xiao Yang
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China
| | - Yuan Cheng
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China
| | - Yang Yang Dong
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China
| | - Jing Yuan Wang
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China
| | - Jing Yi Zhou
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China.
| | - Jian Liu Wang
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China.
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Li H, Wang J, Li L, Zhao L, Wang Z. Expression of EMT-related genes in lymph node metastasis in endometrial cancer: a TCGA-based study. World J Surg Oncol 2023; 21:55. [PMID: 36814242 PMCID: PMC9945723 DOI: 10.1186/s12957-023-02893-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 01/10/2023] [Indexed: 02/24/2023] Open
Abstract
BACKGROUND Endometrial cancer (EC) with metastasis in pelvic/para-aortic lymph nodes suggests an unsatisfactory prognosis. Nevertheless, there is still rare literature focusing on the role of epithelial-mesenchymal transition (EMT) in lymph node metastasis (LNM) in EC. METHODS Transcriptional data were derived from the TCGA database. Patients with stage IA-IIIC2 EC were included, constituting the LN-positive and LN-negative groups. To evaluate the extent of EMT, an EMT signature composed of 315 genes was adopted. The EMT-related genes (ERGs) were obtained from the dbEMT2 database, and the differentially expressed ERGs (DEERGs) between these two groups were screened. On the basis of DEERGs, pathway analysis was carried out. We eventually adopted the logistic regression model to build an ERG-based gene signature with predictive value for LNM in EC. RESULTS A total of 498 patients were included, with 75 in the LN-positive group. Median EMT score of tumor tissues from LN-negative group was - 0.369, while that from the LN-positive group was - 0.296 (P < 0.001), which clearly exhibited a more mesenchymal phenotype for LNM cases on the EMT continuum. By comparing expression profiles, 266 genes were identified as DEERGs, in which 184 were upregulated and 82 were downregulated. In pathway analysis, various EMT-related pathways were enriched. DEERGs shared between molecular subtypes were comparatively few. The ROC curve and logistic regression analysis screened 7 genes with the best performance to distinguish between the LN-positive and LN-negative group, i.e., CIRBP, DDR1, F2RL2, HOXA10, PPARGC1A, SEMA3E, and TGFB1. A logistic regression model including the 7-gene-based risk score, age, grade, myometrial invasion, and histological subtype was built, with an AUC of 0.850 and a favorite calibration (P = 0.074). In the validation dataset composed of 83 EC patients, the model exhibited a satisfactory predictive value and was well-calibrated (P = 0.42). CONCLUSION The EMT status and expression of ERGs varied in LNM and non-LNM EC tissues, involving multiple EMT-related signaling pathways. Aside from that, the distribution of DEERGs differed among molecular subtypes. An ERG-based gene signature including 7 DEERGs exhibited a desirable predictive value for LNM in EC, which required further validation based upon clinical specimens in the future.
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Affiliation(s)
- He Li
- Department of Obstetrics and Gynecology, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, Beijing, 100044, China
| | - Junzhu Wang
- The Big Data and Public Policy Laboratory, School of Government, Peking University, Beijing, China
| | - Liwei Li
- Department of Obstetrics and Gynecology, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, Beijing, 100044, China
| | - Luyang Zhao
- Department of Obstetrics and Gynecology, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, Beijing, 100044, China
| | - Zhiqi Wang
- Department of Obstetrics and Gynecology, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, Beijing, 100044, China.
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Qiang Y, Zhang Q, Dong L. Metabolic risk score as a predictor in a nomogram for assessing myometrial invasion for endometrial cancer. Oncol Lett 2023; 25:114. [PMID: 36844632 PMCID: PMC9950329 DOI: 10.3892/ol.2023.13700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 01/10/2023] [Indexed: 02/09/2023] Open
Abstract
The purpose of the present study was to investigate the predictive value of metabolic syndrome in evaluating myometrial invasion (MI) in patients with endometrial cancer (EC). The study retrospectively included patients with EC who were diagnosed between January 2006 and December 2020 at the Department of Gynecology of Nanjing First Hospital (Nanjing, China). The metabolic risk score (MRS) was calculated using multiple metabolic indicators. Univariate and multivariate logistic regression analyses were performed to determine significant predictive factors for MI. A nomogram was then constructed based on the independent risk factors identified. A calibration curve, a receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to evaluate the effectiveness of the nomogram. A total of 549 patients were randomly assigned to a training or validation cohort, with a 2:1 ratio. Data was then gathered on significant predictors of MI in the training cohort, including MRS [odds ratio (OR), 1.06; 95% confidence interval (CI), 1.01-1.11; P=0.023], histological type (OR, 1.98; 95% CI, 1.11-3.53; P=0.023), lymph node metastasis (OR, 3.15; 95% CI, 1.61-6.15; P<0.001) and tumor grade (grade 2: OR, 1.71; 95% CI, 1.23-2.39; P=0.002; Grade 3: OR, 2.10; 95% CI, 1.53-2.88; P<0.001). Multivariate analysis indicated that MRS was an independent risk factor for MI in both cohorts. A nomogram was generated to predict a patient's probability of MI based on the four independent risk factors. ROC curve analysis showed that, compared with the clinical model (model 1), the combined model with MRS (model 2) significantly improved the diagnostic accuracy of MI in patients with EC (area under the curve in model 1 vs. model 2: 0.737 vs. 0.828 in the training cohort and 0.713 vs. 0.759 in the validation cohort). Calibration plots showed that the training and validation cohorts were well calibrated. DCA showed that a net benefit is obtained from the application of the nomogram. Overall, the present study developed and validated a MRS-based nomogram predicting MI in patients with EC preoperatively. The establishment of this model may promote the use of precision medicine and targeted therapy in EC and has the potential to improve the prognosis of patients affected by EC.
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Affiliation(s)
- Yan Qiang
- Department of Gynecology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu 210000, P.R. China
| | - Qinfen Zhang
- Department of Obstetrics and Gynecology, Zhongda Hospital, Southeast University, Nanjing, Jiangsu 210009, P.R. China
| | - Lingyan Dong
- Department of Gynecology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu 210000, P.R. China,Correspondence to: Dr Lingyan Dong, Department of Gynecology, Nanjing First Hospital, Nanjing Medical University, 68 Changle Road, Nanjing, Jiangsu 210000, P.R. China, E-mail:
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Manchanda S, Subashree AB, Renganathan R, Popat PB, Dhamija E, Singhal S, Bhatla N. Imaging Recommendations for Diagnosis, Staging, and Management of Uterine Cancer. Indian J Med Paediatr Oncol 2023. [DOI: 10.1055/s-0042-1759519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
AbstractUterine cancers are classified into cancers of the corpus uteri (uterine carcinomas and carcinosarcoma) and corpus uteri (sarcomas) by the AJCC staging system (eighth edition). Endometrial carcinoma is the most common amongst these with prolonged estrogen exposure being a well-known risk factor. The FIGO staging system for endometrial carcinoma is primarily surgical and includes total hysterectomy, bilateral salpingo-oophorectomy, and lymphadenectomy. Imaging is useful in the preoperative evaluation of tumor stage, especially assessment of myometrial invasion and cervical stromal extension. Dynamic contrast enhanced MRI with DWI has a high staging accuracy and is the preferred imaging modality for primary evaluation with contrast-enhanced CT abdomen being indicated for recurrent disease. PET/CT is considered superior in evaluation of lymph nodes and extra pelvic metastases.
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Affiliation(s)
- Smita Manchanda
- Department of Radiodiagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi, India
| | - Anthoni Bala Subashree
- Department of Radiodiagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi, India
| | - Rupa Renganathan
- Department of Diagnostic and Interventional Radiology, Kovai Medical Center and Hospitals, Coimbatore, Tamil Nadu, India
| | - Palak Bhavesh Popat
- Breast Imaging and Interventions, Department of Radiology, Tata Memorial Hospital, Mumbai, Maharashtra, India
| | - Ekta Dhamija
- Department of Radiodiagnosis, All India Institute of Medical Sciences, New Delhi, India
| | - Seema Singhal
- Department of Obstetrics and Gynaecology, All India Institute of Medical Sciences, New Delhi, India
| | - Neerja Bhatla
- Department of Obstetrics and Gynaecology, All India Institute of Medical Sciences, New Delhi, India
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Fu R, Zhang D, Yu X, Zhang H. The association of tumor diameter with lymph node metastasis and recurrence in patients with endometrial cancer: a systematic review and meta-analysis. Transl Cancer Res 2022; 11:4159-4177. [PMID: 36523313 PMCID: PMC9745381 DOI: 10.21037/tcr-22-2595] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 11/25/2022] [Indexed: 02/07/2024]
Abstract
BACKGROUND Tumor diameter (TD)/original lesion area has been reported to have a certain predictive effect on lymph node metastasis (LNM) and recurrence of endometrial cancer (EC) patients, but there is still controversy about their relationship. Therefore, we conducted a meta-analysis to provide reference for clinical management and follow-up studies of patients with EC. METHODS The databases of PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP, and Wanfang were searched, from inception to 27 October 2022, for studies regarding the association of TD with LNM risk and recurrence rate in EC. The search strategy was developed using a combination of free terms and medical subject headings (MeSH). Stata 15.0 was used to conduct the statistical analysis. Odds ratio (OR) with the 95% confidence interval (CI) were calculated to evaluate the association of TD and the risk of LNM and recurrence in EC patients. The OR value obtained from the multivariate analysis is first extracted; the results of univariate analysis were extracted for articles without the results of multivariate analysis. Newcastle-Ottawa Scale (NOS) assessed the quality of the included articles, publication bias was evaluated by Egger's test with funnel plots. RESULTS There was a total of 69 studies 123,383 EC patients included. Meta-analysis showed higher LNM risk in EC patients with the TD >2 cm, which was 2.88 times higher than that in those with ≤2 cm, and the difference was statistically significant (OR =2.88; 95% CI: 2.12-3.89; P<0.001), publication bias had no effect on the results. The risk of recurrence in EC patients with a TD >2 cm was 2.45 times higher than that in those with ≤2 cm (OR =2.45; 95% CI: 1.73-3.48; P<0.001), publication bias exerted influence over the results. CONCLUSIONS TD is associated with LNM and recurrence in patients with EC. Therefore, TD should be considered in the scope of surgery and adjuvant therapy.
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Affiliation(s)
- Ruifang Fu
- Department of Gynecology, Huaihe Hospital of Henan University, Kaifeng, China
| | - Dongli Zhang
- Department of Gynecology, Huaihe Hospital of Henan University, Kaifeng, China
| | - Xiaohan Yu
- Department of Gynecology, Huaihe Hospital of Henan University, Kaifeng, China
| | - Hongxia Zhang
- Department of Gynecology, Huaihe Hospital of Henan University, Kaifeng, China
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Lu W, Chen X, Ni J, Li Z, Su T, Li S, Wan X. A Model to Identify Candidates for Lymph Node Dissection Among Patients With High-Risk Endometrial Endometrioid Carcinoma According to Mayo Criteria. Front Oncol 2022; 12:895834. [PMID: 35795035 PMCID: PMC9251056 DOI: 10.3389/fonc.2022.895834] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 05/17/2022] [Indexed: 12/24/2022] Open
Abstract
Background The Mayo criteria are the most widely accepted algorithm for predicting the risk of lymph node metastasis in endometrial endometrioid carcinoma (EEC). However, the clinical value of these criteria in high-risk patients is limited and inconclusive. Methods A total of 240 patients with EEC meeting the Mayo high-risk criteria between January 1, 2015, and December 31, 2018 were included in our study. We retrospectively collected the laboratory reports, basic clinical information, clinicopathological and immunohistochemistry (IHC) findings, and the sequences of molecular pathological markers of these patients. A nomogram for predicting the likelihood of positive lymph node status was established based on these parameters. Results Among the 240 patients, 17 were diagnosed with lymph node metastasis. The univariable analyses identified myometrial invasion >50%, aberrant p53 expression, microsatellite instable (MSI), and cancer antigen 125 (CA125) ≥35 U/ml as potential risk factors for lymph node metastasis. The multivariable analyses showed that aberrant p53 expression, MSI, and CA125 ≥35 U/ml were independent predictors of lymph node metastasis. The area under the curve (AUC) for the nomogram was 0.870, as compared to 0.665 for the Mayo criteria. Conclusions Our novel prediction model effectively identifies patients at high risk for lymphatic metastasis. This model is a promising strategy for personalized surgery in patients with high risk according to the Mayo criteria.
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Affiliation(s)
- Wen Lu
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tong Ji University, Shanghai, China
| | - Xiaoyue Chen
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tong Ji University, Shanghai, China
| | - Jingyi Ni
- Department of Clinical Research Center, Shanghai First Maternity and Infant Hospital, School of Medicine, Tong Ji University, Shanghai, China
| | - Zhen Li
- Department of Clinical Research Center, Shanghai First Maternity and Infant Hospital, School of Medicine, Tong Ji University, Shanghai, China
| | - Tao Su
- Department of Gynecology, The International Peace Maternity & Child Health Hospital of China Welfare Institute, Shanghai Jiaotong University, Shanghai, China
| | - Shuangdi Li
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tong Ji University, Shanghai, China
- *Correspondence: Shuangdi Li, ; Xiaoping Wan,
| | - Xiaoping Wan
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tong Ji University, Shanghai, China
- *Correspondence: Shuangdi Li, ; Xiaoping Wan,
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Yang XL, Yang FL, Kou LN, Wu DJ, Xie C. Prognostic model for the exemption of adjuvant chemotherapy in stage IIIC endometrial cancer patients. Front Endocrinol (Lausanne) 2022; 13:989063. [PMID: 36387854 PMCID: PMC9643711 DOI: 10.3389/fendo.2022.989063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 10/05/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND This study aimed to develop a nomogram to predict the survival for stage IIIC endometrial cancer (EC) patients with adjuvant radiotherapy (ART) alone and personalize recommendations for the following adjuvant chemotherapy (ACT). METHODS In total, 746 stage IIIC EC patients with ART alone were selected from the Surveillance, Epidemiology, and End Results (SEER) registry. Cox regression analysis was performed to identify independent risk factors. A nomogram was developed accordingly, and the area under the receiver operating characteristic curve (AUC) and C-index were implemented to assess the predictive power. The patients were divided into different risk strata based on the total points derived from the nomogram, and survival probability was compared between each risk stratus and another SEER-based cohort of stage IIIC EC patients receiving ART+ACT (cohort ART+ACT). RESULTS Five independent predictors were included in the model, which had favorable discriminative power both in the training (C-index: 0.732; 95% CI: 0.704-0.760) and validation cohorts (C-index: 0.731; 95% CI: 0.709-0.753). The patients were divided into three risk strata (low risk <135, 135 ≤ middle risk ≤205, and high risk >205), where low-risk patients had survival advantages over patients from cohort ART+ACT (HR: 0.45, 95% CI: 0.33-0.61, P < 0.001). However, the middle- and high-risk patients were inferior to patients from cohort ART+ACT in survival (P < 0.001). CONCLUSION A nomogram was developed to exclusively predict the survival for stage IIIC EC patients with ART alone, based on which the low-risk patients might be perfect candidates to omit the following ACT. However, the middle- and high-risk patients would benefit from the following ACT.
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Affiliation(s)
- Xi-Lin Yang
- Department of Radiation Oncology, Chengdu Women’s and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Feng-Leng Yang
- Department of Radiology, Chengdu Women’s and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Ling-Na Kou
- Department of Medical Oncology, Sichuan Cancer Hospital and Institute, Chengdu, China
| | - Da-Jun Wu
- Department of Radiation Oncology, Chengdu Women’s and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
- *Correspondence: Cong Xie, ; Da-Jun Wu,
| | - Cong Xie
- Department of Gynecology, Chengdu Women’s and Children’s Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
- *Correspondence: Cong Xie, ; Da-Jun Wu,
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