98%
921
2 minutes
20
Objective: To evaluate upstaging, lymph node (LN) metastasis, and recurrence in patients with presumed stage I endometrial cancer using preoperative magnetic resonance imaging (MRI) and positron emission tomography-computed tomography (PET-CT).
Methods: Retrospective review of 422 patients with presumed clinical stage I endometrial cancer diagnosed via MRI and PET-CT (July 2014-June 2023). Surgical staging included pelvic lymph nodes (PLNs) and para-aortic lymph nodes (PALNs), classifying patients as low/intermediate- or high-risk groups.
Results: Post-operative upstaging rate was 14.5% (8.8% low/intermediate-risk vs. 22.8% high-risk, p<0.001). LN metastasis occurred in 5.5% of patients (2.0% low/intermediate-risk vs. 10.5% high-risk, p<0.001), with a dual imaging negative predictive value of 0.945. PLN metastasis was 4.5% (2.0% low/intermediate vs. 8.2% high-risk, p=0.003), and PALN metastasis was 2.6% (0.4% low/intermediate-risk vs. 5.8% high-risk, p=0.001). In low/intermediate-risk group: tumors ≤2cm had 1.1% LN metastasis rate, endometrium-limited 0.8%, and ≤2cm with endometrium-limited 0.9%. Deep myometrial invasion (odds ratio [OR]=4.4; 95% confidence intervals [CIs]=1.6-12.4) and tumor size >2 cm on MRI (OR=2.9; 95% CI=0.8-9.9) increased LN metastasis risk. Median 48.5-month follow-up showed an 8.1% overall recurrence rate (4.0% low/intermediate-risk vs. 14.0% high-risk, p<0.001), with 2.4% nodal recurrences (1.2% low/intermediate-risk vs. 4.1% high-risk).
Conclusion: High-risk patients had significant upstaging, LN metastasis, and recurrence rates. Even in low/intermediate-risk groups, some patients exhibited LN metastasis and nodal recurrence, underscoring the importance of comprehensive surgical staging, including PALN evaluation, for precise diagnosis and treatment.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11964980 | PMC |
http://dx.doi.org/10.3802/jgo.2025.36.e25 | DOI Listing |
Eur J Surg Oncol
September 2025
Barzilai University Medical Center, Ashkelon, Israel; Faculty of Health Sciences, Ben-Gurion University of Negev, Beer-Sheva, Israel.
Objective: To compare the survival of women with high grade endometrial cancer between asymptomatic and women presenting bleeding symptoms.
Design: An Israel Gynecologic Oncology Group multi-center retrospective cohort study.
Methods: The study included women who underwent surgery for high-grade endometrial cancer.
Eur J Obstet Gynecol Reprod Biol
September 2025
Department of Biostatistics, Amrita Institute of Medical Sciences, Ponekkara Rd, Edappally, Kochi, Ernakulam 682041 Kerala, India.
Objective: This study compared the oncological outcomes of Pure Uterine Serous Carcinomas (p-USC) and p53-Abnormal Grade 3 Endometroid Endometrial Tumours (p53 Abn G3-EEC).
Methods: A retrospective study was conducted at Amrita Institute of Medical Sciences from February 1, 2015, to December 31, 2020, analysing patients diagnosed with P-USC and p53 Abn G3-EEC. The primary objective was to compare the 5-year Progression-Free Survival (PFS) between two groups.
Gynecol Oncol
September 2025
University of Chicago, Department of Obstetrics and Gynecology, Section of Gynecologic Oncology, Chicago, IL 60637, USA; University of Chicago, Department of Medicine, Section of Hematology/Oncology, Chicago, IL 60637, USA.
Objective: To identify associations between race, neighborhood disadvantage, and outcomes in women with stage I-III endometrioid endometrial cancer (EEC) treated at a tertiary referral center.
Methods: This retrospective tumor registry study included patients with stage I-III EEC between 1/2006 and 12/2022. Progression-free (PFS) and overall survival (OS) were analyzed by race and neighborhood disadvantage, stratified by Area Deprivation Index (ADI; national quartile).
J Robot Surg
September 2025
Department of Gynecology, European Institute of Oncology (IEO) IRCCS, Milan, Italy.
Obesity is closely linked to an increased incidence of several gynecological conditions and poses significant challenges to their surgical management. Among these, endometrial cancer stands out due to its high prevalence in patients with elevated body mass index, with nearly 60% of those requiring primary surgical treatment classified as obese or morbidly obese. The coexistence of multiple comorbidities in this population contributes to a heightened risk of perioperative and postoperative complications.
View Article and Find Full Text PDFExpert Rev Anticancer Ther
September 2025
AIBioMed Research Group, Taipei Medical University, Taipei, Taiwan.
Introduction: Deep learning (DL) is transforming cancer research by enabling data-driven drug discovery. However, its clinical translation, particularly in endometrial cancer (EC), faces significant challenges.
Areas Covered: This review discusses recent DL applications across drug discovery stages in EC, including target identification, virtual screening, and de novo drug design.