Study Objectives: To compare patient outcomes by surgical approach in the management of endometrial cancer (EC) in Washington State from 2008 to 2013.
Design: Population-based retrospective cohort study (Canadian Task Force classification II-2).
Setting: Washington State.
Patients: EC patients treated with robotic-assisted surgery (RAS), laparoscopy (LS), or laparotomy (XLAP).
Interventions: Comprehensive Hospital Abstract Reporting System to identify patients and assess the association of surgical approach with length of stay, readmissions, and perioperative complications.
Measurements And Results: We identified 3712 cases of EC managed with either RAS, LS, or XLAP. Mean length of stay was not clinically different for RAS (1.5 days) and LS (1.6 days) but was 2.31 days longer for XLAP compared with LS (p < .001). Odds of any readmission did not differ for either RAS or XLAP compared with LS; however, early readmissions were half as likely for RAS compared with LS (p = .014). Complications were more than 2.5 times as likely for XLAP versus LS (p < .001), whereas complications did not differ for RAS versus LS (p = .931).
Conclusions: RAS is as an alternative to LS in the treatment of EC and is preferable to XLAP. The use of RAS resulted in fewer early readmissions compared with LS and resulted in an increased proportion of cases via minimally invasive surgery.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.jmig.2018.01.010 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Development and Validation of a Nomogram Based on Multiparametric MRI for Predicting Lymph Node Metastasis in Endometrial Cancer: A Retrospective Cohort Study.
Acad Radiol
December 2024
Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China (Y.T., Y.W., Y.Y., X.Q., Y.H., J.L.); Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning 530021, Guangxi Zhuang Autonomous Region, PR China (J.L.). Electronic address:
Rationale And Objectives: To develop a radiomics nomogram based on clinical and magnetic resonance features to predict lymph node metastasis (LNM) in endometrial cancer (EC).
Materials And Methods: We retrospectively collected 308 patients with endometrial cancer (EC) from two centers. These patients were divided into a training set (n=155), a test set (n=67), and an external validation set (n=86).
Clinical and histopathological evaluation of patients with endometrial cancer in a University Hospital: Seven-year experience.
Malays J Pathol
December 2024
Universiti Sains Malaysia, School of Medical Sciences, Department of Obstetrics & Gynaecology, Health Campus, 16150 Kubang Kerian, Kelantan, Malaysia.
Introduction: Endometrial cancer is one of the leading gynaecological malignancies in developed countries and becoming more prevalent in Malaysia. These have significant impact in women and management of this disease. If it occurs on young women, and as a whole becomes a burden on the national economy and world.
View Article and Find Full Text PDFTEFM facilitates uterine corpus endometrial carcinoma progression by activating ROS-NFκB pathway.
J Transl Med
December 2024
Department of Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Background: Mitochondrial transcription elongation factor (TEFM) is a recently discovered factor involved in mitochondrial DNA replication and transcription. Previous studies have reported that abnormal TEFM expression can disrupt the assembly of mitochondrial respiratory chain and thus mitochondrial function. However, the role of TEFM on Uterine corpus endometrial carcinoma (UCEC) progression remains unclear.
View Article and Find Full Text PDFPMDA regulatory update on approval and revision of the precautions for use of anticancer drugs; approval of pembrolizumab for locally advanced uterine cervical cancer, and durvalumab and olaparib for advanced or recurrent endometrial cancer in Japan.
Int J Clin Oncol
December 2024
Japan Society of Clinical Oncology, Editorial Committee, Tokyo, Japan.
A machine learning-based immune response signature to facilitate prognosis prediction in patients with endometrial cancer.
Sci Rep
December 2024
Department of Laboratory Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China.
Endometrial cancer is the most prevalent form of gynecologic malignancy, with a significant surge in incidence among youngsters. Although the advent of the immunotherapy era has profoundly improved patient outcomes, not all patients benefit from immunotherapy; some patients experience hyperprogression while on immunotherapy. Hence, there is a pressing need to further delineate the distinct immune response profiles in patients with endometrial cancer to enhance prognosis prediction and facilitate the prediction of immunotherapeutic responses.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!